Journal of Applied Smart Electrical Network and Systems
type: channel
description: Journal of Applied Smart Electrical Network and Systems (JASENS) is a peer-review journal published by Indonesia Society of Applied Science (ISAS). Journal of applied smart electrical network and system aims to provide a forum for academic researchers, industrial professionals, engineers, educators and practitioners to contribute and disseminate innovative new work and research result on electrical engineering related smart electrical network and system. All accepted papers will be published twice a year which is available online (open access).
publisher: Indonesian Society of Applied Science (ISAS)
language: en
publication name: Journal of Applied Smart Electrical Network and Systems
issn: 2723-5467
items: Analisis Kerentanan Keamanan Chatbot Berbasis Large Language Model Terhadap Serangan SQL Injection
items: On-Board Diagnostic Tool menggunakan Mikrokontroler pada Kendaraan Listrik (EV) Terintegrasi dengan Speedometer
items: Model Deep Learning Hybrid CNN-AE untuk Klasifikasi Presisi Warna Buah Melon
items: Koordinasi Rele Arus Lebih di Perusahaan Nikel Indonesia Menggunakan Grasshopper Optimization Algorithm
items: Analisis Kinerja Sistem Kontrol Hybrid Electric Vehicle (HEV) Menggunakan Metode Neuro-fuzzy
items: Desain PLTS Off-Grid Dengan Teknologi Penyimpanan Energi Pumped Storage Di Mahakam Ulu
items: Analisa Ekonomi PLTS Off-Grid Dengan Teknologi Pumped Storage Di Mahakam Ulu
items: Sistem Monitoring Terdistribusi Berbasis ESP dengan Komunikasi CAN Bus dan Platform Blynk
items: Pengaruh Variasi Output Buck-Boost terhadap pH dan TDS pada Proses Elektrolisis Air
items: Simulasi Perbandingan Training Dataset YOLOv5 Dan YOLOv8 Menggunakan Prototipe AUV
items: Sistem Monitoring Listrik Tiga Phasa Berbasis Panel LED P10
items: Implementasi Deep Learning Dalam Prediksi Real-Time Iradian Surya
items: Simulasi Deteksi Marka Jalan Menggunakan Canny Edge Detection untuk Navigasi Kendaraan Otonom
items: Implementasi Logika Fuzzy dalam Perancangan Sistem Kontrol Kecepatan Motor Chain Conveyor
items: Deteksi Ikan Menggunakan MEtode Faster R-CNN
items: PULSE Energy: Solusi Portabel Hemat Energi untuk Sistem AC dan DC
items: Pembagian Daya pada Kendaraan Listrik Berbasis Sistem Hybrid Baterai dan Superkapasitor dengan Fuzzy Logic Controller
items: KOPISA: Rancang Bangun Sistem Otomatis Pengemasan Plastik untuk Biji Kopi dengan Fitur Pemantauan Suhu dan Berat
items: the Estimation of State of Charge for 4S2P Lithium-Ion Battery Using Kalman Filter and Coulomb Counting
items: Rancang Bangun Sistem Pelacak Posisi Human Indoor Location menggunakan ESP-Now
items: Sistem Input Output Inventaris Tools Menggunakan Long Range RFID Study Case di PLTA Sutami
items: PERENCANAAN TRANSFORMATOR PADA ELEKTRIFIKASI CONTAINER CRANE UNTUK OPERASI BONGKAR MUAT
items: Integrasi Sistem ESP32 dengan Pemantauan Cuaca Menggunakan Sensor Meteorologi
items: Peningkatan Akurasi Kontrol Arah Kapal Menggunakan Sensor Kompas BNO055
items: SIGAP: Sistem Informasi dan Peringatan Dini Kebakaran Berbasis IoT untuk Komunitas Disabilitas
items: Implementasi Sistem SCADA dan PLC S7-300 untuk Otomatisasi Koreksi Berat Semen Pada Checkweigher
items: Optimasi Klasterisasi Kubernetes untuk Peningkatan QoS pada Jaringan 5G
items: IMPLEMENTASI SISTEM MONITORING AIR DENGANSENSOR ULTRASONIK HC-SR04 DAN WATER FLOW DI ASONE HIDROPONIK BERBASIS INTERNET OF THINGS (IoT) MENGGUNAKAN ENERGI PANEL SURYA(PLTS)
items: Perancangan Alat Saklar Elektronik Menggunakan Metode Uji IC di Laboratorium Elektronika Dasar
items: Monitoring Dan Datalogger Untuk Daya Keluaran Sistem Pembangkit Listrik Tenaga Angin

Analisis Kerentanan Keamanan Chatbot Berbasis Large Language Model Terhadap Serangan SQL Injection
type: item
description: Perkembangan teknologi Large Language Model (LLM) telah mendorong pemanfaatan chatbot pada berbagai layanan digital. Integrasi chatbot dengan basis data dan layanan backend berpotensi menimbulkan risiko keamanan, terutama terhadap serangan SQL Injection. Penelitian ini bertujuan untuk menganalisis dan menguji kerentanan SQL Injection pada aplikasi chatbot berbasis LLM. Pengujian dilakukan menggunakan payload SQL Injection, Burp Suite, dan OWASP ZAP pada empat chatbot berbasis LLM, yaitu AlexAI, Gemini, Claude, dan Dola. Hasil penelitian menunjukkan bahwa seluruh target tidak memperlihatkan indikasi keberhasilan eksploitasi, tidak terjadi kebocoran informasi, serta tidak ditemukan akses tidak sah ke basis data. Meskipun demikian, ditemukan beberapa isu keamanan pada tingkat aplikasi yang berkaitan dengan konfigurasi keamanan web. Temuan ini menunjukkan bahwa keamanan chatbot berbasis LLM tidak hanya bergantung pada ketahanan model, tetapi juga pada keamanan aplikasi dan infrastruktur pendukung yang digunakan.
subject: Articles
  topic: section
subject: Large Language Model (LLM)
  topic: keywords
subject: Prompt Injection
  topic: keywords
subject: SQL Injection
  topic: keywords
subject: Black-box Penetration Testing
  topic: keywords
subject: Cybersecurity
  topic: keywords
creator: Bambang Harie Wiyono
creator: Filia Nur Anjaini
creator: Lukman Rosyidi
rights: Copyright (c) 2026 Bambang Harie Wiyono, Filia Nur Anjaini, Lukman Rosyidi https://creativecommons.org/licenses/by/4.0
date: 2026-06-30
publication date: 2026-06-30
starting page: 27
ending page: 39
doi: 10.52158/qy05dk06

On-Board Diagnostic Tool menggunakan Mikrokontroler pada Kendaraan Listrik (EV) Terintegrasi dengan Speedometer
type: item
description: Electric vehicles (EVs) are becoming a growing environmentally friendly transportation solution, but they still require an efficient and easily accessible vehicle condition monitoring system. Electric motorcycle users often experience difficulties in directly knowing the condition of the battery, motor, and drive system. Based on these problems, this study aims to develop an On-Board Diagnostic (OBD) system integrated with a speedometer to monitor the main parameters of two-wheeled electric vehicles in real-time. The research method includes designing a microcontroller-based system connected to a motor controller via UART and Controller Area Network (CAN) communication. The system is equipped with a DS3231 RTC module for time markers, an SD Card for data storage, and a 20x4 LCD to display voltage, current, power, temperature, and fault status (fault code). Testing was conducted on the Graha Merjosari Asri–Greenland at Tidar, Malang route, with speed variations between 0–45 km/h. The results show that the system is capable of detecting undervoltage conditions below 60 V, maintaining a stable maximum temperature of 41°C without overheating, and displaying vehicle data accurately and responsively. The developed OBD-speedometer system functions effectively as a portable and economical diagnostic tool for electric two-wheeled vehicles, with potential for development into an IoT-based intelligent monitoring system.
subject: Articles
  topic: section
subject: CAN bus
  topic: keywords
subject: electric vehicles
  topic: keywords
subject: microcontroller
  topic: keywords
subject: OBD
  topic: keywords
subject: speedometer
  topic: keywords
creator: Zakiyah Amalia
creator: Achsanul Khabib
creator: Talifatim Machfuroh
creator: Fica Aida Nadhifatul Aini
creator: Diama Rizky Septiawan
creator: Siti Duratun Nasiqiati Rosady
creator: Ahsani Maulidina
rights: Copyright (c) 2026 Zakiyah Amalia, Achsanul Khabib, Talifatim Machfuroh, Fica Aida Nadhifatul Aini, Diama Rizky Septiawan, Siti Duratun Nasiqiati Rosady, Ahsani Maulidina https://creativecommons.org/licenses/by/4.0
date: 2026-06-26
publication date: 2026-06-26
starting page: 16
ending page: 21
doi: 10.52158/zgs4tv61

Model Deep Learning Hybrid CNN-AE untuk Klasifikasi Presisi Warna Buah Melon
type: item
description: Melon fruit color classification is a critical step in assessing fruit ripeness and quality. This study proposes a hybrid deep learning model that integrates Convolutional Neural Network (CNN) and Attention Enhancement (AE) for accurate classification of melon fruit color. The model leverages CNN’s strength in visual feature extraction while enhancing focus on crucial image regions through the attention mechanism. A diverse image dataset of melon fruits was collected under various lighting conditions and angles. Pre-processing steps, including data augmentation, normalization, and image scaling, were applied to improve model generalization. The CNN-Attention hybrid architecture incorporates an attention module into the CNN layers to emphasize significant features. Comparative experiments between the standard CNN and the hybrid model demonstrate that the latter achieves superior classification accuracy, with an average improvement of 5%. Moreover, the hybrid model exhibits better robustness against image noise and lighting variations. These results indicate that incorporating Attention Enhancement can yield a more adaptive and reliable model for melon fruit color classification. The proposed approach is expected to support the development of automated systems for fruit sorting in agriculture and distribution, enhancing speed, accuracy, and efficiency for farmers, traders, and consumers.
subject: Articles
  topic: section
subject: Deep Learning
  topic: keywords
subject: CNN
  topic: keywords
subject: Attention Enhancement
  topic: keywords
subject: klasifikasi warna
  topic: keywords
subject: buah melon
  topic: keywords
creator: Yurni Oktarina
creator: Tresna Dewi
creator: Dini Septiyani AR
rights: Copyright (c) 2025 Yurni Oktarina, Tresna Dewi, Dini Septiyani AR https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 139
ending page: 146
doi: 10.52158/d3hydf28

Koordinasi Rele Arus Lebih di Perusahaan Nikel Indonesia Menggunakan Grasshopper Optimization Algorithm
type: item
description: Setiap sistem kelistrikan bergantung pada ketersediaan energi yang berkelanjutan untuk menjaga produktivitas industri tetap berjalan. Gangguan listrik akan merusak peralatan listrik. Sistem proteksi berfungsi untuk meminimalkan hingga menghilangkan gangguan secara cepat, selektif, dan terkoordinasi demi meminimalkan kerusakan sistem dan memastikan pasokan listrik yang tidak terputus. Khususnya untuk rele arus lebih, time dial setting (TDS) merupakan aspek penting yang harus dipertimbangkan perihal koordinasi proteksi. TDS mengatur waktu operasi rele untuk mengamankan sistem kelistrikan. Umumnya, perhitungan manual digunakan untuk menentukan nilai TDS. Metode trial and error sering digunakan untuk mengoordinasikan rele satu sama lain. Metode ini telah berkembang menjadi algoritma cerdas yang dapat menemukan solusi secara efektif dan cepat, salah satu algoritmanya adalah grasshopper optimization algorithm (GOA). Hasil dari simulasi pada penelitian ini didapatkan nilai koordinasi antara rele 4 bekerja pada 0,1 detik & rele 3 bekerja pada 0,3 detik saat timbul gangguan pada trafo 2, rele 3 bekerja pada 0,297 detik & rele 2 bekerja pada 0,496 detik saat timbul arus gangguan pada bus 4, rele 2 bekerja pada 0,492 detik & rele 1 bekerja pada 0,493 saat timbul arus gangguan pada bus 3 serta kinerja rele 1 yang hanya sebagai primer untuk mengamankan generator bekerja pada 0,354 detik saat timbul arus gangguan pada bus 2 telah menghasilkan nilai perhitungan TDS yang akurat serta masih mematuhi aturan pengaturan minimum nilai coordination time interval (CTI) antara rele primer dan rele backup yaitu 0,2 detik dalam satu rating tegangan dan mendekati 0 di rating tegangan yang berbeda.
subject: Articles
  topic: section
subject: sistem proteksi
  topic: keywords
subject: rele arus lebih
  topic: keywords
subject: time dial setting
  topic: keywords
subject: grasshopper optimization algorithm
  topic: keywords
subject: coordination time interval
  topic: keywords
creator: Riko Satrya Fajar Jaelani Putra
creator: Aulia Rahma Annisa
creator: Yudi Andika
creator: Sholahuddin Muhammad Irsyad
creator: Rahmat Basya Shahrys Tsany
rights: Copyright (c) 2025 Riko Satrya Fajar Jaelani Putra, Aulia Rahma Annisa, Yudi Andika, Sholahuddin Muhammad Irsyad, Rahmat Basya Shahrys Tsany https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 132
ending page: 138
doi: 10.52158/kn1tk933

Analisis Kinerja Sistem Kontrol Hybrid Electric Vehicle (HEV) Menggunakan Metode Neuro-fuzzy
type: item
description: Electric cars are an environmentally friendly vehicle alternative developed to reduce exhaust gas emissions and air pollution. One example is the Hybrid Electric Vehicle (HEV), which combines an Internal Combustion Engine (ICE) and an electric motor (DC motor) to improve efficiency and torque performance. HEVs generally have a smaller capacity compared to conventional vehicles, making them more fuel-efficient and energy-efficient. The system in an HEV is complex and nonlinear, requiring dynamic model approaches and appropriate control methods to maintain optimal performance. This research aims to analyze the performance of the inverse model neuro-fuzzy control system predictor implemented on an HEV. The test results show that applying a neuro-fuzzy controller can significantly improve the system's ability to achieve a response that matches the reference model. The performance of the DC motor is able to help reduce the speed error difference by up to 50 rpm with a Root Mean Square Error (RMSE) value of 0.582%. Additionally, there is a 1.411% decrease in error value compared to when the ICE is operating without using a neuro-fuzzy controller. Based on these results, the neuro-fuzzy method has proven effective in improving the accuracy and stability of the control system in HEVs.
subject: Articles
  topic: section
subject: Hybrid Electric Vehicle (HEV), Predictor Model, Neuro-fuzzy
  topic: keywords
creator: Aulia Rahma Annisa
creator: Yudi Andika
creator: Sholahuddin Muhammad Irsyad
creator: Dwi Sasmita Aji Pambudi
rights: Copyright (c) 2025 Aulia Rahma Annisa, Yudi Andika, Sholahuddin Muhammad Irsyad, Dwi Sasmita Aji Pambudi https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 125
ending page: 131
doi: 10.52158/f5y40s25

Desain PLTS Off-Grid Dengan Teknologi Penyimpanan Energi Pumped Storage Di Mahakam Ulu
type: item
description: This research presents the design of an off-grid Solar Power Plant (PLTS) integrated with pumped storage energy technology in Mahakam Ulu Regency, East Kalimantan, as a sustainable energy solution for remote regions. The main objective of this study is to develop a reliable, efficient, and environmentally friendly power generation system by utilizing local renewable energy potential. The research methodology includes identifying 24-hour load demand, analyzing PLTS capacity based on solar radiation potential, calculating hydrological parameters such as water head and flow rate, and determining the capacity and dimensions of key components, including turbines, penstock pipes, pumps, inverters, and storage reservoirs. The technical data show a reservoir volume of 566,784 m³, a head height of 100 meters, a penstock diameter of 1.9 meters, a PLTS capacity of 10.3 MWp using 13,734 solar panels, and a 15 MW inverter. The analysis results indicate that the designed system can maintain continuous electricity supply during nighttime or low-solar conditions through stored potential energy utilization. This configuration significantly reduces dependency on diesel generators, decreases carbon emissions, and supports the national clean energy transition agenda. The off-grid PLTS design integrated with pumped storage technology is proven to be a feasible and sustainable approach that can serve as a reference for developing similar renewable energy systems in other isolated 3T regions with comparable geographical and natural characteristics.
subject: Articles
  topic: section
subject: solar power plant, pumped storage energy, renewable energy, clean Energy Transition, rural electrification
  topic: keywords
creator: Muhamad Cahyo Samudro
creator: Widodo Pudji Muljanto
creator: Irmalia Suryani Faradisa
creator: Sotyohadi
rights: Copyright (c) 2025 Muhamad Cahyo Samudro, Widodo Pudji Muljanto, Irmalia Suryani Faradisa, Sotyohadi https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 118
ending page: 124
doi: 10.52158/sfhg7b24

Analisa Ekonomi PLTS Off-Grid Dengan Teknologi Pumped Storage Di Mahakam Ulu
type: item
description: Indonesia continues to face challenges in providing reliable and sustainable electricity, particularly in remote areas that are not yet connected to the main power grid. To support the transition toward clean energy, this study conducts a financial feasibility analysis for the planned development of an Off-Grid Solar Power Plant (PLTS) with Pumped Storage technology located in Batu Dinding, Ujoh Bilang, Long Bagun District, Mahakam Ulu Regency, East Kalimantan. The objective of this research is to evaluate the project’s economic feasibility using financial analysis methods, including calculations of Net Present Value (NPV), Internal Rate of Return (IRR), and Benefit-Cost Ratio (BCR). The study assumes a project lifetime of 50 years with a total investment cost of IDR 99,475,000,000, funded through a government grant. The analysis results show a positive NPV, an IRR of 11.2%, and a BCR of 2.60, indicating that the project is financially viable and profitable. Furthermore, the sensitivity analysis with variations in discount rates (3%–10%) and investment cost increases up to 8% demonstrates that the project remains stable and feasible under different economic conditions. Therefore, the development of the Off-Grid PLTS with Pumped Storage system can serve as a sustainable and clean energy solution for electricity supply in remote regions of Indonesia.
subject: Articles
  topic: section
subject: Off-Grid Solar Power Plant, pumped storage, financial analysis, renewable energy, economic feasibility.
  topic: keywords
creator: Rifqi Fajriyansyah
creator: Irmalia Suryani Faradisa
rights: Copyright (c) 2025 Rifqi Fajriyansyah, Irmalia Suryani Faradisa https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 110
ending page: 117
doi: 10.52158/7cp9b247

Sistem Monitoring Terdistribusi Berbasis ESP dengan Komunikasi CAN Bus dan Platform Blynk
type: item
description: Pemantauan kondisi air sungai secara real-time merupakan aspek penting dalam sistem peringatan dini banjir dan pengelolaan sumber daya air. Penelitian ini bertujuan mengembangkan sistem monitoring terdistribusi yang akurat dan dapat diakses secara remote untuk mendukung deteksi dini potensi banjir. Sistem menggunakan dua node ESP32 dengan komunikasi CAN Bus, dimana node pengirim mengintegrasikan sensor ultrasonik JSN-SR04T untuk pengukuran ketinggian air dan sensor flow meter berbasis Hall Effect untuk pengukuran kecepatan aliran. Node penerima berbasis LilyGo SIM800L mengirimkan data ke platform Blynk dan menampilkan informasi melalui display OLED. Komunikasi antar node menggunakan protokol CAN Bus 50 kbps dengan validasi checksum. Pengujian dilakukan selama 14 jam dengan interval 2 jam dari pukul 06.00-20.00 WIB, menghasilkan 8 sampel data monitoring. Data menunjukkan variasi ketinggian air 32-40 cm dengan rata-rata 35,5 cm, serta kecepatan aliran 0,22-1,50 m/s dengan rata-rata 0,82 m/s. Sistem mencapai akurasi pengukuran ±2,1% untuk ketinggian air dan ±3,4% untuk kecepatan aliran, dengan tingkat keberhasilan transmisi data 96,8% melalui GSM/GPRS. Interface OLED menyediakan monitoring lokal real-time, sedangkan platform Blynk memungkinkan akses remote melalui aplikasi mobile. Sistem terbukti efektif untuk monitoring kontinyu parameter hidrologi sungai dengan tingkat akurasi dan reliabilitas yang memadai untuk aplikasi peringatan dini banjir.
subject: Articles
  topic: section
subject: Blynk IoT, CAN Bus, ESP32, Ketinggian Air, Sistem Monitoring Terdistribusi
  topic: keywords
creator: Septyana Riskitasari
creator: Wahyu Aulia Nurwicaksana
creator: Indrazno Siradjuddin
creator: Gillang Al Azhar
creator: Fasha Rafi Islamey
rights: Copyright (c) 2026 Septyana Riskitasari, Wahyu Aulia Nurwicaksana, Indrazno Siradjuddin, Gillang Al Azhar, Fasha Rafi Islamey https://creativecommons.org/licenses/by/4.0
date: 2026-06-22
publication date: 2026-06-22
doi: 10.52158/3e910z95

Pengaruh Variasi Output Buck-Boost terhadap pH dan TDS pada Proses Elektrolisis Air
type: item
description: Penelitian ini bertujuan merancang dan menguji sistem monitoring kualitas air berbasis ESP32 dengan sensor pH 4502C dan sensor Total Dissolved Solids (TDS) selama proses elektrolisis menggunakan variasi tegangan dan arus output buck-boost converter. Rangkaian utama terdiri dari buck-boost converter yang diatur pada mode buck (5 V) dan boost (20 V), elektroda aluminium sebagai media elektrolisis, serta instrumen pengukuran pH dan TDS yang terintegrasi dengan mikrokontroler. Pengujian dilakukan dengan mencatat perubahan pH dan TDS pada interval waktu tertentu hingga 90 detik. Hasil pengujian menunjukkan bahwa sensor pH 4502C mampu mendeteksi kenaikan pH dari nilai awal 4,00. Pada kondisi 5 V 20 A (J = 4,03 mA/cm²) pH meningkat lebih cepat hingga 6,70, sedangkan pada kondisi 20 V 12 A (J = 2,41 mA/cm²) hanya mencapai 5,60. Hal ini membuktikan bahwa densitas arus berperan penting terhadap laju peningkatan pH akibat pembentukan ion OH⁻. Sensor TDS menunjukkan penurunan kadar zat terlarut dari nilai awal 169 ppm. Pada tegangan 5 V 20 A, TDS menurun lebih signifikan hingga 120 ppm, sedangkan pada 20 V 12 A hanya turun menjadi 139 ppm. Hasil ini menunjukkan variasi tegangan dan arus berpengaruh terhadap efektivitas penurunan zat terlarut dalam air.
subject: Articles
  topic: section
subject: Buck–Boost Converter, Densitas Arus, Elektrolisis, Kualitas Air, 4502C
  topic: keywords
creator: Septyana Riskitasari
creator: Deasy Shandiya Ekawati
creator: Wahyu Aulia Nurwicaksana
rights: Copyright (c) 2025 Septyana Riskitasari, Deasy Shandiya Ekawati, Wahyu Aulia Nurwicaksana https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 84
ending page: 89
doi: 10.52158/t5wzk262

Simulasi Perbandingan Training Dataset YOLOv5 Dan YOLOv8 Menggunakan Prototipe AUV
type: item
description: Penelitian ini mengevaluasi performa pelatihan model YOLOv5n dan YOLOv8n menggunakan dataset Kompetisi Robot Berbasis Kecerdasan Buatan (KRBAI) 2024 untuk deteksi objek pada prototipe Autonomous Underwater Vehicle (AUV). Dataset yang terdiri atas 4.114 citra dengan tiga kelas objek (gerbang, rintangan, drum) dilatih melalui Google Colab dengan konfigurasi 200 epoch, ukuran batch 16, dan resolusi citra 640x640. YOLOv5n memanfaatkan struktur berbasis anchor, sedangkan YOLOv8n menggunakan pendekatan tanpa anchor dengan modul C2f untuk efisiensi lebih tinggi. Hasil pelatihan menunjukkan YOLOv8n unggul dalam presisi (0,994 vs. 0,990) dan mAP50-95 (0,940 vs. 0,924), sementara YOLOv5n lebih baik pada recall kelas gerbang (0,999). Kedua model memiliki mAP50 serupa (0,993). Waktu pelatihan YOLOv8n sedikit lebih lama (3 jam 17 menit vs. 3 jam 31 menit). YOLOv8n terbukti lebih efektif untuk deteksi objek real-time pada AUV, mendukung navigasi dan pengenalan lingkungan bawah air. Penelitian mendatang perlu menguji dataset yang lebih beragam dan kondisi lingkungan yang lebih kompleks.
subject: Articles
  topic: section
subject: YOLOv5n
  topic: keywords
subject: YOLOv8n
  topic: keywords
subject: object detection
  topic: keywords
subject: AUV
  topic: keywords
creator: Ryan Yudha Adhitya
creator: Erutan Dwi Sajiwo
creator: Zindhu Maulana Ahmad Putra
creator: M. Yusuf Santoso
creator: M. Khoirul Hasin
creator: Adianto
creator: Dimas Pristovani Riananda
creator: Isa Rachman
creator: Agus Khumaidi
creator: Yuning Widiarti
rights: Copyright (c) 2026 Ryan Yudha Adhitya, Erutan Dwi Sajiwo, Zindhu Maulana Ahmad Putra, M. Yusuf Santoso, M. Khoirul Hasin, Adianto, Dimas Pristovani Riananda, Isa Rachman, Agus Khumaidi, Yuning Widiarti https://creativecommons.org/licenses/by/4.0
date: 2026-06-30
publication date: 2026-06-30
doi: 10.52158/pkrjg903

Sistem Monitoring Listrik Tiga Phasa Berbasis Panel LED P10
type: item
description: Abstract The increasing demand for electricity consumption monitoring in various sectors, including educational environments, requires an accurate, efficient, and real-time monitoring system. This study aims to design and develop a three-phase electricity monitoring system using a P10 LED Matrix panel controlled by an Arduino Mega microcontroller. The system is designed to display voltage, current, and frequency parameters directly through the LED panel, replacing conventional LCD displays with limited size and visibility. The design methodology includes problem identification, data collection through literature study and observation, hardware and software design, assembly, and system testing. The main components consist of three PZEM-004T sensors for electrical data acquisition, an Arduino Mega ATmega2560 as the processing unit, and three P10 LED Matrix panels as the visualization medium. Testing results show that the system can display real-time data with high accuracy. The average voltage measurement error was 0.0013%, and the current measurement error was 0.057%, both well below the 0.5% tolerance specified by the sensor. This system has proven reliable for monitoring three-phase electrical loads at the Politeknik Negeri Ketapang Laboratory Building. In conclusion, the developed system can enhance electricity monitoring efficiency, facilitate electrical condition analysis, and has the potential for further development by integrating Internet of Things (IoT) technology for remote monitoring. Keywords: Electrical monitoring system, three-phase, P10 LED panel, Arduino Mega, PZEM-004T.
subject: Articles
  topic: section
subject: Electrical monitoring system
  topic: keywords
subject: three-phase
  topic: keywords
subject: P10 LED panel
  topic: keywords
subject: Arduino Mega
  topic: keywords
subject: PZEM-004T
  topic: keywords
creator: ivan suwanda
rights: Copyright (c) 2025 ivan suwanda
date: 2025-08-19
publication date: 2025-08-19
starting page: 49
ending page: 54
doi: 10.52158/jasens.v5i2.1374

Implementasi Deep Learning Dalam Prediksi Real-Time Iradian Surya
type: item
description: Accurate prediction of solar irradiance plays a critical role in the planning and operation of renewable energy systems, particularly for photovoltaic integration and energy management. This study investigates the use of a deep learning approach based solely on Convolutional Neural Networks (CNN) to forecast short-term solar irradiance values. The model is trained using normalized multivariate time series data, which include several meteorological parameters as input features. The CNN architecture is designed to extract temporal patterns from the input sequences and predict radiation intensity at the next time step. Experimental results show that the proposed model achieves strong predictive performance, with a Mean Squared Error (MSE) of 0.0006, Root Mean Squared Error (RMSE) of 0.0242, Mean Absolute Error (MAE) of 0.0184, and a coefficient of determination (R²) of 0.9607. These findings demonstrate that CNN, despite its simplicity, is capable of effectively learning complex temporal relationships in solar irradiance data. Furthermore, the loss curves for both training and validation sets indicate stable convergence without signs of overfitting. The results suggest that CNN-based forecasting models can offer a lightweight and accurate solution for real-time solar prediction applications, especially when computational resources are limited.
subject: Articles
  topic: section
subject: Solar Irradiance Forecasting, Convolutional Neural Network, Deep Learning, Time Series Prediction, Renewable Energy.
  topic: keywords
creator: Angga Liwijaya
creator: Pola Risma
creator: Yurni Oktarina
creator: Tresna Dewi
rights: Copyright (c) 2025 Angga Liwijaya, Pola Risma, Yurni Oktarina, Tresna Dewi https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 90
ending page: 96
doi: 10.52158/pvdpsr36

Simulasi Deteksi Marka Jalan Menggunakan Canny Edge Detection untuk Navigasi Kendaraan Otonom
type: item
description: This study develops an automatic steering control system based on image processing using the Canny Edge Detection method. The system is implemented on a small-scale autonomous vehicle prototype, utilizing Raspberry Pi 5 as the main processor and a Pi Camera as the visual sensor. Video frames are processed through several stages, including color conversion, Grayscale, Gaussian blur, Edge Detection, Region of Interest (RoI), and lane center estimation. The results show an average lane detection accuracy of 96% with responsive steering control, indicating the system's potential for lightweight autonomous vehicle navigation.
subject: Articles
  topic: section
subject: Autonomous Vehicle, Canny Edge Detection, Lane Detection, Steering Control, Raspberry Pi
  topic: keywords
creator: Febrian Akbara
creator: Ii Munadhif
creator: Mohammad Abu Jami'in
creator: Ryan Yudha Adhitya
creator: Imam Sutrisno
rights: Copyright (c) 2026 Febrian Akbara, Ii Munadhif, Mohammad Abu Jami'in, Ryan Yudha Adhitya, Imam Sutrisno https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 69
ending page: 75
doi: 10.52158/1a6jvn12

Implementasi Logika Fuzzy dalam Perancangan Sistem Kontrol Kecepatan Motor Chain Conveyor
type: item
description: Dalam sistem produksi industri, chain conveyor merupakan komponen penting untuk memindahkan material secara efisien. Namun, variasi beban secara dinamis dapat menyebabkan gangguan pada kinerja motor penggerak, seperti peningkatan arus dan suhu yang berisiko menyebabkan kerusakan. Penelitian ini bertujuan merancang sistem kontrol kecepatan motor chain conveyor berbasis logika fuzzy dengan metode Sugeno untuk mengatasi permasalahan tersebut. Sistem mengandalkan input dari sensor Load Cell (berat material), PT100 (suhu motor), dan PZEM-004T (arus listrik) yang diproses menggunakan aturan fuzzy. Keluaran sistem berupa sinyal kontrol untuk mengatur kecepatan motor melalui inverter. Perancangan dilakukan dengan integrasi sensor, ESP32, serta aktuator seperti relay dan motor servo, dengan pengaturan sinyal PWM yang dikonversi menjadi tegangan analog. Simulasi sistem menggunakan software Matlab menunjukkan bahwa logika fuzzy Sugeno mampu menentukan set point kecepatan motor secara akurat berdasarkan input aktual. Pada pengujian dengan berat material 900 gram, suhu motor 37,4°C, dan arus listrik 2,29 A, sistem berhasil menghasilkan frekuensi motor sebesar 25 Hz yang sesuai dengan perhitungan manual. Hasil ini menunjukkan bahwa metode fuzzy efektif dalam menyesuaikan kecepatan motor secara adaptif, serta meminimalisasi risiko overload pada motor dalam kondisi operasional yang berubah-ubah.
subject: Articles
  topic: section
subject: fuzzy, kontrol, kecepatan, motor, konveyor
  topic: keywords
creator: Sofi Berliana Rizky
creator: Isa Rachman
creator: Ii Munadhif
rights: Copyright (c) 2025 Sofi Berliana Rizky, Isa Rachman, Ii Munadhif https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 97
ending page: 109
doi: 10.52158/j93p5q70

Deteksi Ikan Menggunakan MEtode Faster R-CNN
type: item
description: Automatic fish detection in video is a challenging task in the field of computer vision, which can be addressed using deep learning methods. This study proposes the use of the Faster Region-based Convolutional Neural Network (Faster R-CNN) to detect two types of fish, namely Manfish and Lemonfish, in video data. The dataset was constructed by extracting frames from video and processing them using the Roboflow platform. The model was trained and tested using pre-split training and testing sets. The training process was conducted over 40 epochs using the Adam optimization algorithm to improve detection accuracy. Model evaluation was carried out using several metrics, including Precision, Recall, mean Average Precision (mAP), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared (R²). The results show that the model achieved a precision of 94% and an accuracy of 87% for the Lemonfish class, and a precision of 95% and an accuracy of 89% for the Manfish class. These findings indicate that the model is capable of accurately detecting fish, delivering high detection performance, and effectively recognizing objects in video frames.
subject: Articles
  topic: section
subject: Fish Detection, Deep Learning, Faster R-CNN, Computer Vision, Model Evaluation.
  topic: keywords
creator: Yurni Oktarina
creator: Yolanda Eka Pratiwi
creator: Tresna Dewi Dewi
rights: Copyright (c) 2025 Yurni Oktarina, Yolanda Eka Pratiwi, Tresna Dewi Dewi
date: 2024-12-31
publication date: 2024-12-31
starting page: 41
ending page: 48
doi: 10.52158/jasens.v5i2.1132

PULSE Energy: Solusi Portabel Hemat Energi untuk Sistem AC dan DC
type: item
description: Tujuan penelitian ini adalah untuk mengembangkan unit daya hibrida portabel AC-DC yang mampu menyediakan konversi energi untuk beban resistif dan induktif. Desain menggunakan sistem konverter AC-DC hibrida, yang mengintegrasikan baterai yang dapat diisi ulang, inverter DC-AC, dan sistem kontrol pintar berbasis mikrokontroler. Aplikasi Android diterapkan untuk pemantauan dan pengendalian jarak jauh, memungkinkan pengguna untuk mengelola konsumsi daya dan mengisi ulang baterai. Penelitian ini menemukan bahwa unit daya hibrida efektif dalam mendukung beban resistif dan induktif tanpa kerugian energi yang signifikan. Sistem kontrol pintar, yang mencakup relay untuk pemutusan daya otomatis berdasarkan saldo yang tersedia. Fitur pemantauan jarak jauh meningkatkan kenyamanan pengguna dengan memberikan wawasan real-time tentang penggunaan energi dan saldo. Penelitian ini memberikan solusi yang dapat diskalakan untuk kebutuhan energi portabel, dengan implikasi untuk aplikasi rumah tangga maupun komersial. Fitur kontrol pintar juga berkontribusi pada penghematan energi dan otonomi pengguna yang lebih besar. Integrasi output AC dan DC serta kemampuan pengendalian jarak jauh membedakan solusi ini dari unit daya tradisional. Nilai penelitian ini terletak pada aplikasinya yang praktis untuk berbagai perangkat elektronik, menawarkan sumber daya yang andal, efisien, dan fleksibel.
subject: Articles
  topic: section
creator: Hendi Purnata
rights: Copyright (c) 2025 Hendi Purnata
date: 2024-12-31
publication date: 2024-12-31
starting page: 48
ending page: 53
doi: 10.52158/jasens.v5i2.1199

Pembagian Daya pada Kendaraan Listrik Berbasis Sistem Hybrid Baterai dan Superkapasitor dengan Fuzzy Logic Controller
type: item
description: This research discusses the application of Energy Management System on hybrid batteries and superkapasitors for power distribution as an effort to distribute the load on electric vehicles. The purpose of the research conducted is to determine whether the proposed Fuzzy Logic Controller-based control system can operate well as an effort to distribute power for the needs of operating electric vehicles. The driving cycle that will be used in the study is the Urban Dynamometer Driving Schedule (UDDS) cycle to determine the effect of power sharing on hybrid batteries and superkapasitors in the UDDS driving cycle. Testing was carried out under 2 different conditions, namely when the SOC condition of the battery and superkapasitor was 85% and when the SOC of the battery was 20% while the SOC of the superkapasitor was 85%. From the test, it was obtained that the proposed hybrid battery and superkapasitor system based on the Fuzzy Logic Controller was able to operate well under the specified conditions. Both energy storage devices were able to share power by maintaining the battery and superkapasitor SOC not exceeding the specified operating limits. This condition allows electric vehicles to be operated for a fairly long period of time.
subject: Articles
  topic: section
subject: Power Sharing, Fuzzy Logic Controller, UDDS
  topic: keywords
creator: Yudi Andika
creator: Aulia Annisa
creator: Aminatus Sa’diyah
creator: Hendro Widodo
rights: Copyright (c) 2025 Yudi Andika, Aulia Annisa, Aminatus Sa’diyah, Hendro Widodo
date: 2025-07-14
publication date: 2025-07-14
starting page: 63
ending page: 68
doi: 10.52158/jasens.v6i01.1217

KOPISA: Rancang Bangun Sistem Otomatis Pengemasan Plastik untuk Biji Kopi dengan Fitur Pemantauan Suhu dan Berat
type: item
description: Industri pada umumnya adalah aktivitas untuk menghasilkan produk. Dalam kegiatan industri terdapat beberapa proses seperti pengumpulan bahan baku, produksi, quality control, pengemasan, dan pemasaran. Salah satu masalah yang sering terjadi adalah pada tahap pengemasan. Jika proses pengemasan tidak efisien, hal ini akan menghambat hasil produksi karena membutuhkan banyak waktu dan tenaga. Oleh karena itu, tugas akhir ini bertujuan untuk merancang dan membuat alat pengemas plastik yang dapat mengubah plastik lembaran menjadi kemasan. Alat ini dilengkapi dengan fitur pemantauan suhu pada pemanas dan pemantauan berat kemasan untuk meningkatkan kualitas hasil kemasan. Sistem ini menggunakan mikrokontroler Arduino Mega2560 sebagai pusat kendali, motor servo untuk katup bak penampungan, sensor load cell untuk penimbangan, motor DC sebagai penggerak sealer, dan LCD untuk menampilkan data. Alat ini mengubah plastik lembaran menjadi kemasan yang direkatkan menggunakan pemanas. Komponen pendukung lainnya meliputi relay dan sensor suhu DS18B20. Hasil pengujian menunjukkan alat ini dapat bekerja optimal pada suhu 60-65°C dengan delay pengepresan 2500 ms. Pengemasan menunjukkan akurasi berat yang baik dengan persentase error rata-rata 8,75% untuk 100gram dan 5,05% untuk 200gram. Selisih berat rata-rata antara load cell dan timbangan konvensional adalah 1,29 gram, dan sensor suhu menunjukkan selisih rata-rata 0,878°C dengan error 1,818%.
subject: Articles
  topic: section
subject: Alat pengemas
  topic: keywords
subject: Arduino Mega2560
  topic: keywords
subject: Load Cell
  topic: keywords
subject: Sensor suhu DS18B20
  topic: keywords
subject: LCD
  topic: keywords
creator: Hendi Purnata
creator: Sugeng Dwi Riyanto
creator: Fadlian Adam
rights: Copyright (c) 2025 Hendi Purnata
date: 2025-06-30
publication date: 2025-06-30
starting page: 57
ending page: 62
doi: 10.52158/jasens.v6i01.1198

the Estimation of State of Charge for 4S2P Lithium-Ion Battery Using Kalman Filter and Coulomb Counting
type: item
description: State of Charge (SoC) estimation is crucial for the performance and safety of Battery Management Systems (BMS). This study evaluates and compares two SoC estimation methods—Kalman Filter and Coulomb Counting—based on numerical simulation of a 4S2P lithium-ion battery charging process using MATLAB. The methods are assessed using statistical metrics: RMSE, MAE, MAPE, and R², and are compared against both current-based reference calculations and normalized actual voltage. Kalman Filter consistently demonstrates superior performance, achieving lower RMSE (0.00067) and MAE (0.00045) against SoC reference, and RMSE (0.0376), MAE (0.0312), R² (0.978) against voltage reference. In contrast, Coulomb Counting shows increased error accumulation and lower correlation with system behavior. This confirms Kalman Filter's robustness in dynamic conditions, owing to its real-time correction mechanism and noise tolerance. The study highlights Kalman Filter as a more accurate and reliable method for modern BMS applications. Recommendations for future development include real-world testing and hybrid algorithm implementation.
subject: Articles
  topic: section
subject: kalman filter
  topic: keywords
subject: coulomb counting
  topic: keywords
subject: state of charge
  topic: keywords
subject: materai management system
  topic: keywords
subject: matlab simulation
  topic: keywords
subject: rmse
  topic: keywords
subject: mae
  topic: keywords
subject: voltage referance
  topic: keywords
subject: estimation accuracy
  topic: keywords
creator: Tiara Erly Syah Putri
creator: Mat Syai’in
creator: Ii Munadhif
rights: Copyright (c) 2025 Tiara Erly Syah Putri
date: 2025-06-30
publication date: 2025-06-30
starting page: 48
ending page: 56
doi: 10.52158/jasens.v6i01.1166

Rancang Bangun Sistem Pelacak Posisi Human Indoor Location menggunakan ESP-Now
type: item
description: This research aims to develop an Internet of Things (IoT)-based employee attendance and position tracking system using the ESP-NOW protocol integrated with a web database. This system is designed to automatically record attendance and monitor the position of employees in real-time using the Trilateration method with the Exponential Path Loss model. Data from the ESP32 device is sent to the MySQL database via the MQTT protocol and displayed in an easily accessible website interface. The results show that the system can efficiently recap daily, weekly, and monthly attendance data, as well as display the position history of employees and guests with sufficient accuracy. With the implementation of this system, the efficiency and accuracy of attendance management and employee monitoring at Sutami Hydroelectric Power Plant has increased significantly.
subject: Articles
  topic: section
subject: Iot
  topic: keywords
subject: ESP-Now
  topic: keywords
subject: Automatmatic Attendence
  topic: keywords
subject: MQTT
  topic: keywords
creator: Ega Adi Rachmawan
creator: Lilik Subiyanto
creator: Adianto
creator: Mat Syaiin
creator: Aulia Rahma Annisa
creator: Mustika Kurnia Mayangsari
rights: Copyright (c) 2025 Ega Adi Rachmawan, Lilik Subiyanto, Adianto, Mat Syaiin, Aulia Rahma Annisa, Mustika Kurnia Mayangsari
date: 2025-06-30
publication date: 2025-06-30
starting page: 32
ending page: 37
doi: 10.52158/jasens.v6i01.1150

Sistem Input Output Inventaris Tools Menggunakan Long Range RFID Study Case di PLTA Sutami
type: item
description: The problem faced by Sutami Hydroelectric Power Plant in the management and data collection of tools is that the data collection is still done manually, and some tools are not returned to their place due to negligence in use. To support the achievement of the 5S culture (Seiri, Seiton, Seiso, Seiketsu, Shitsuke) at Sutami Hydroelectric Power Plant, an automated tools management system is needed. In the application of the goods input and output system, many are still using low frequency RFID with a reading range of >5cm so that tapping must be done with an RFID Reader. This still has the potential for an unrecorded loan process if the item is not tapped. This research optimizes the tools management system with long range RFID. With the designed update, it is expected that the tools management system at Sutami Hydroelectric Power Plant can provide increased productivity and also achieve the 5S culture at Sutami Hydroelectric Power Plant.
subject: Articles
  topic: section
subject: 5S Culture
  topic: keywords
subject: Management Tools
  topic: keywords
subject: Long range RFID
  topic: keywords
subject: Sutami Hydroelectric Power Plant\
  topic: keywords
creator: Muhammad Fa'iz
creator: Joko Endrasmono
creator: Sholahuddin Muhammad Irsyad
creator: Lilik Subiyanto
creator: Anggar Juna Puncak Pujiputra
creator: Mustika Kurnia Mayangsari
rights: Copyright (c) 2025 Muhammad Fa'iz
date: 2025-06-30
publication date: 2025-06-30
starting page: 38
ending page: 47
doi: 10.52158/jasens.v6i01.1152

PERENCANAAN TRANSFORMATOR PADA ELEKTRIFIKASI CONTAINER CRANE UNTUK OPERASI BONGKAR MUAT
type: item
description: Sistem bongkar muat pelabuhan mencakup semua komponen atau peralatan penanganan muatan yang mendukung proses bongkar muat baik dari kapal ke pelabuhan maupun sebaliknya. Dalam penanganan pelabuhan, ini melibatkan pembongkaran dari kapal dengan memakai crane dan sling kapal ke daratan terdekat, umumnya dikenal sebagai dermaga. Crane adalah alat yang digunakan untuk mengangkat dan memindahkan material yang juga membutuhkan energi listrik. Untuk itu diperlukan sumber daya listrik untuk kegiatan operasional bongkar muat. Kebutuhan sumber daya listrik yang diperlukan, digunakan juga dalam menentukan kapasitas transformator distribusi yang terpasang. Untuk menentukan semua itu berdasar keberadaan beban yang digunakan sebagai acuan utama dalam beban listrik yang diharapkan. Beban diklasifikasikan sesuai dengan sifat, yaitu continue dan terputus-putus (intermittent). Beban terputus-putus (intermittent) tergantung faktor siklus kerja yang dapat ditambahkan pada beban kontinyu untuk mendapatkan beban rata-rata (average load). Beban listrik ditentukan berdasarkan konsep di atas, dengan margin ditambah 30% di atas beban rata-rata dengan memasukkan perubahan beban pada kerangka pemakai pada saat pengembangan dan implementasi perubahan diwaktu mendatang. Berdasarkan hasil studi lapangan pada operasional bongkar muat di Surabaya yang menjadi lokasi penelitian ini, menunjukkan transformator yang terpasang pada Container Crane (T4 2500 kVA/20/6,6 kV) dan transformator yang terpasang pada RTG Crane (T1 1250 kVA/20/0,4 kV) sudah sesuai dengan kapasitas transformator yang seharusnya.
subject: Articles
  topic: section
subject: Container Crane, Transformator, Daya Listrik, Beban Listrik, Effisiensi
  topic: keywords
creator: Edy Setiawan
creator: Annas Singgih Setiyoko
creator: Galih Anindita
creator: Yudi Andika
creator: Evi Nafiatus Sholikhah
rights: Copyright (c) 2026 EDY SETIAWAN, Annas Singgih Setiyoko, Galih Anindita, Yudi Andika, Evi Nafiatus Sholikhah https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 76
ending page: 83
doi: 10.52158/j5da7y85

Integrasi Sistem ESP32 dengan Pemantauan Cuaca Menggunakan Sensor Meteorologi
type: item
description: This study proposes an ESP32-based system integration for real-time weather monitoring using meteorological sensors including wind speed, wind direction, and rainfall sensors. ESP32 is chosen as the main platform because of its capability in wireless communication (Wi-Fi and Bluetooth) and its efficiency in processing sensor data with low power consumption. This system combines meteorological sensors to measure wind speed, wind direction, and rainfall, which are then displayed directly on the Nextion screen. The collected data will be updated in real-time, providing easily accessible information. The purpose of this study is to develop an effective and integrated weather monitoring system. The test results show that this system can collect and display data accurately on Nextion, providing an efficient and practical weather monitoring solution.
subject: Articles
  topic: section
subject: ESP32
  topic: keywords
subject: Wind Speed Sensor
  topic: keywords
subject: Wind Direction, Rainfall
  topic: keywords
subject: Weather Monitoring
  topic: keywords
subject: Nextion
  topic: keywords
subject: Internet of Things (IoT)
  topic: keywords
subject: Real-time Weather Monitoring System
  topic: keywords
creator: Yusma'el Khammi Prayoga
creator: Afif Zuhri Arfianto
creator: Dimas Pristovani Riananda
creator: Muhammad Khoirul Hasin
creator: Adianto
creator: Ryan Yudha Adhitya
rights: Copyright (c) 2025 Yusma'el Khammi Prayoga, Afif Zuhri Arfianto,ST.MT, Dimas Pristovani Riananda,S.ST.MT
date: 2025-06-30
publication date: 2025-06-30
starting page: 23
ending page: 31
doi: 10.52158/jasens.v6i01.1149

Peningkatan Akurasi Kontrol Arah Kapal Menggunakan Sensor Kompas BNO055
type: item
description: The accuracy of a ship's heading measurement is an important element in ensuring the ship moves towards its destination precisely and safely. One of the key parameters in this system is the ship's heading, which indicates the direction of the ship relative to a specific reference point, such as magnetic north. However, heading measurements are often affected by environmental disturbances, magnetic interference and sensor calibration errors, which can degrade measurement accuracy. This research proposes the use of the BNO055 sensor, which combines an accelerometer, gyroscope and magnetometer in a single module to measure ship orientation in three dimensions. An STM32 microcontroller is used to process the data from the BNO055 sensor and calculate the ship's heading and relative bearing with high precision. The calculation results are then displayed on the Nextion Display, providing visual information needed by the user. Test results show that the system provides high accuracy, with an average percentage error of 0.002% for heading and 0.208% for angle. The system can steer the ship with high precision, despite magnetic field disturbances. Thus, this BNO055 and STM32-based system is expected to improve efficiency and accuracy in ship direction measurement applications.
subject: Articles
  topic: section
subject: BNO055
  topic: keywords
subject: ship navigation system
  topic: keywords
subject: heading
  topic: keywords
subject: relative bearing
  topic: keywords
creator: Dwi Agus Setiyono
creator: Afif Zuhri Arfianto
creator: Dimas Pristovani Riananda
creator: Agus Khumaidi
creator: Noorman Rinanto
creator: Zindhu Maulana Ahmad
rights: Copyright (c) 2025 Dwi Agus Setiyono
date: 2025-06-30
publication date: 2025-06-30
starting page: 17
ending page: 23
doi: 10.52158/jasens.v6i01.1147

SIGAP: Sistem Informasi dan Peringatan Dini Kebakaran Berbasis IoT untuk Komunitas Disabilitas
type: item
description: Beberapa orang lahir dengan disabilitas seperti gangguan penglihatan, pendengaran, atau bicara. Saat ini, media dan alat bantu untuk penyandang disabilitas masih terbatas, terutama dalam situasi darurat seperti kebakaran. Misalnya, alarm kebakaran umumnya mengandalkan suara, yang tidak efektif bagi tunarungu. Sementara itu, tunawicara mungkin memerlukan alat untuk menghasilkan suara saat terjebak dalam situasi berbahaya. Untuk membantu penyandang tunarungu dan tunawicara, dibuatlah alat pendeteksi dan pemberi peringatan. Alat ini terdiri dari dua bagian: rangkaian pengirim dan penerima. Rangkaian pengirim menggunakan sensor api, Arduino sebagai mikrokontroler, dan modul WiFi ESP8266 untuk mengirim data ke internet melalui Thingspeak. Rangkaian penerima berbentuk jam tangan yang terdiri dari NodeMCU, motor DC mini sebagai indikator getar, LED sebagai indikator cahaya, OLED sebagai indikator bacaan, dan buzzer sebagai indikator suara. Alat ini berfungsi dengan baik dan mencapai efektivitas hingga 95%.
subject: Articles
  topic: section
creator: Hendi Purnata
rights: Copyright (c) 2026 Hendi Purnata https://creativecommons.org/licenses/by/4.0
date: 2026-06-22
publication date: 2026-06-22
doi: 10.52158/gqxpwv57

Implementasi Sistem SCADA dan PLC S7-300 untuk Otomatisasi Koreksi Berat Semen Pada Checkweigher
type: item
description: Checkweigher merupakan sebuah alat yang digunakan untuk mengoreksi penimbangan semen. Sistem ini dirancang untuk mengatasi masalah penimbangan dari Checkweigher lama yang penimbangannya sering dibawah setpoint, tidak stabil, dan kurang presisi. Pada Checkweigher yang lama mempunyai kelemahan yaitu penimbangannya tidak dapat dipantau secara jarak jauh. Pada Checkweigher yang dirancang ini display dan data penimbangan ditampilkan pada HMI di kontrol lokal dan terhubung ke sistem SCADA untuk pemantauan jarak jauh. Sistem Checkweigher yang dirancang memiliki 5 zona koreksi: Underweight, Tendency(-), normal (setpoint), Tendency(+), dan Overweight, dengan set point 40–40,3 kg. Hasil pengujian menunjukkan Checkweigher bekerja baik, dengan rata-rata error sensor load cell 0,118% dan penimbangan lebih banyak masuk ke zona setpoint. Sistem ini berhasil meminimalisir Underweight, dengan 30,88% penimbangan masuk zona 1 dan 2 (Underweight dan Tendency(-)), serta 69,12% masuk zona 3, 4, dan 5 (normal, Tendency(+), dan Overweight).
subject: Articles
  topic: section
creator: Dinda Ayu Permatasari
creator: Alfian Raid Jiddan Al Fath
creator: Edi Sulistio Budi
creator: Wahyu Tri Wahono
rights: Copyright (c) 2025 Dinda Ayu Permatasari, Alfian Raid Jiddan Al Fath, Edi Sulistio Budi, Wahyu Tri Wahono
date: 2025-06-21
publication date: 2025-06-21
starting page: 10
ending page: 16
doi: 10.52158/jasens.v6i01.1140

Optimasi Klasterisasi Kubernetes untuk Peningkatan QoS pada Jaringan 5G
type: item
description: Resource management, scalability, and Quality of Service are key challenges in deploying 5G networks, particularly regarding latency, throughput, and packet loss. Conventional network architectures often fail to meet the demands of high-speed and low-latency communication, especially for applications such as the Internet of Things and cloud computing. This study applies a Kubernetes-based clustering method to address these challenges to optimize 5G network performance through efficient resource allocation and load balancing. Experiments were conducted in a Containerized Network Function environment through simulations, demonstrating significant performance improvements. Test results recorded a 28.69% reduction in latency, a 34.52% increase in throughput, and a 32.14% reduction in packet loss compared to a non-clustered 5G network. These improvements are supported by Kubernetes features such as auto-scaling, traffic distribution, and real-time load balancing. This approach demonstrates that Kubernetes clustering effectively enhances Quality of Service, optimizes resource allocation, and improves the overall efficiency of 5G network systems. Keywords: 5G Networks, Clustering, Kubernetes, QoS, Resource Management
subject: Articles
  topic: section
subject: 5G Networks
  topic: keywords
subject: Clustering
  topic: keywords
subject: Kubernetes
  topic: keywords
subject: QoS
  topic: keywords
subject: Resource Management
  topic: keywords
creator: Ronald Adrian
creator: R. Deasy Mandasari
rights: Copyright (c) 2024 Ronald Adrian, R. Deasy Mandasari
date: 2025-05-14
publication date: 2025-05-14
starting page: 1
ending page: 9
doi: 10.52158/jasens.v5i2.1129

IMPLEMENTASI SISTEM MONITORING AIR DENGANSENSOR ULTRASONIK HC-SR04 DAN WATER FLOW DI ASONE HIDROPONIK BERBASIS INTERNET OF THINGS (IoT) MENGGUNAKAN ENERGI PANEL SURYA(PLTS)
type: item
description: The cultivation system using hydroponics is now widely popular among the community because it does not require large areas of land. Using the hydroponic system results in faster and optimal harvests. However, the busy activities of urban communities often cause them to fail in implementing it due to constraints in controlling and monitoring hydroponic plants. Additionally, PLN electricity is essential for operating the water pump, and the electricity load and tariff increases, along with sudden blackouts, significantly impact business actors. To address this problem, this research creates an Internet of Things (IoT)-based water monitoring system for ACONE Hydroponics partners with solar panel (PLTS) energy sources as an alternative energy in the event of a sudden PLN power outage. The sensors used in this system include the HCR-04 ultrasonic sensor to monitor water availability and the water flow sensor to measure water flow (discharge). Sensor data is processed by the ESP32 microcontroller and sent to the Blynk cloud platform via an internet connection and displayed on an LCD. System testing shows that the system can send sensor data to the cloud platform stably and in real-time. Data visualization on the cloud platform is easy to understand and helps hydroponic owners monitor water conditions in hydroponic systems. This water monitoring system can help users optimize water use in hydroponic systems.
subject: Articles
  topic: section
subject: Hydroponics,
  topic: keywords
subject: AsOne
  topic: keywords
subject: Solar Panels (PLTS)
  topic: keywords
subject: Internet of Things (IoT)
  topic: keywords
subject: Ultrasonic Sensor HCR-04
  topic: keywords
subject: Water Flow Sensor
  topic: keywords
subject: Water Monitoring
  topic: keywords
subject: Cloud Platform
  topic: keywords
subject: Blynk
  topic: keywords
subject: LCD
  topic: keywords
subject: ESP32
  topic: keywords
creator: Dewi Permata Sari
creator: Jhofy Ricardo P Sitindaon
creator: Dewi Permata sari
creator: RD. Kusumanto
rights: Copyright (c) 2024 Dewi Permata Sari, Jhofy Ricardo P Sitindaon, Dewi Permata sari, RD. Kusumanto
date: 2024-06-30
publication date: 2024-06-30
starting page: 22
ending page: 28
doi: 10.52158/jasens.v5i1.918

Perancangan Alat Saklar Elektronik Menggunakan Metode Uji IC di Laboratorium Elektronika Dasar
type: item
description: Komponen elektronika adalah bahan utama yang diperlukan untuk proses pembelajaran praktikum yang di lakukan oleh mahasiswa jurusan Teknik Elektro. Sering kali terjadi kegagalan pada saat praktikum , penyebab utama adalah kegagalan fungsi dari komponen yang digunakan, ketika serangkaian SOP telah dilakukan. Maka untuk mengurangi resiko kegagalan saat praktikum, komponen yang akan digunakan harus dipastikan kondisinya dalam keadan berfungsi dengan baik. Hal inilah yang melatarbelakangi dilakukannya penelitian dengan judul Perancangan Alat Saklar Elektronik Menggunakan Metode Uji IC (Integrated Circuit) di Laboratorium Elektronika Dasar. Alat Saklar Elektronik ini dirancang untuk dapat menguji beberapa komponen aktif antara Seven Segment Common Anode, Seven Segment Common Cathode, ADC 0804, Tansistor NPN BD 139 series, Transistor PNP BD 140 series, Mosfet N Channel IRF 540, Mosfet P Channel IRF 9540. Hasil dari penelitian ini adalah menghasilkan alat yang mampu menyeleksi beberapa komponen aktif yang sering digunakan oleh praktikan pada saat praktikum yang dilakukan di Laboratorium Elektronika Dasar. Dengan demikian, dalam merancang alat saklar elektronik menggunakan metode uji IC, penting untuk memperhatikan pemilihan komponen yang tepat, pengujian yang cermat, serta aspek keamanan dan kenyamanan pengguna. Integrasi antara perancangan sistem, pemilihan komponen, dan pengujian yang teliti akan membantu memastikan kualitas dan kinerja alat elektronik yang dihasilkan
subject: Articles
  topic: section
creator: Fauziah Sholikhatun Nisa
creator: Winda Rachmawati
creator: Rosita Ferdiyana
creator: Hariyanto
rights: Copyright (c) 2024 Fauziah Sholikhatun Nisa
date: 2024-08-20
publication date: 2024-08-20
starting page: 9
ending page: 15
doi: 10.52158/jasens.v5i1.870

Monitoring Dan Datalogger Untuk Daya Keluaran Sistem Pembangkit Listrik Tenaga Angin
type: item
description: Energi listrik dapat dihasilkan dari berbagai jenis energi primer dengan memanfaatkan energi terbarukan salah satunya yaitu angin, untuk memanfaatkan energi terbarukan tersebut membutuhkan peralatan, misalnya untuk tenaga angin membutuhkan peralatan utama turbin angin untuk memastikan bahwa perangkat sumber energi tersebut berjalan dengan baik maka memerlukan perawatan dan pemantauan. pematauan secara konvensional mengukur mengunakan multimeter dan perlunya pencatatan data agar bisa diolah. Fungsi dari memonitoring adalah untuk mengumpulkan data sebanyak-banyaknya untuk itu manusia bisa mengunakan teknologi Internet of Thing (IOT) sebagai media pemantauan dan pencatatan data. Sistem datalogger akan merekam Kecepatan angin, Tegangan dan Arus, secara real time untuk mengetahui kondisi serta korelasi antara lingkungan dan daya yang dihasilkan oleh turbin angin dengan memanfaatkan mikrokontroler. Berdasarkan hasil pengukuran toleransi kesalahan pada sensor yang di gunakan memiliki rata – rata berada dibawah 5%. Pada sensor kecepatan angin RS-FSJT-N01 error 0,089%. Pada sensor tegangan turbin angin error 0,08%. Pada sensor arus ACS712 5amp error 0,051%. Kemudian kecepatan total pengiriman data sebesar 2154 milidetik per 1 record data.
subject: Articles
  topic: section
subject: Internet of Thing
  topic: keywords
subject: Data Loger
  topic: keywords
subject: Monitoring
  topic: keywords
subject: Sensor
  topic: keywords
subject: Mikrokontroler
  topic: keywords
creator: Gery Prasetya
creator: Fitri
creator: Septyana Riskitasari
rights: Copyright (c) 2024 Gery Prasetya
date: 2024-06-30
publication date: 2024-06-30
starting page: 1
ending page: 8
doi: 10.52158/jasens.v5i1.808