Implementasi Fuzzy Logic dalam Mengendalikan Input dan Output pada Penyiraman dan Pemupukan Tanaman Otomatis Berbasis IoT
DOI:
https://doi.org/10.52158/jasens.v3i02.520
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Keywords:
automatic farming, fuzzy logic controller, internet of things
Abstract
Salah satu tantangan dalam pertanian adalah masalah penyiraman dan pemupukan tanaman. Sebagian besar proses penyiraman dan pemupukan tanaman dilakukan secara konvensional. Penelitian ini menyajikan model sistem penyiraman dan pemupukan tanaman otomatis berbasis Internet of Things (IoT) menggunakan metode fuzzy mamdani untuk mempermudah melakukan penyiraman dan pemupukan tanaman. Paper ini membahas desain alat penyiraman dan pemupukan tanaman yang akan diaplikasikan pada bidang pertanian untuk menggantikan petani dalam menyiram dan memupuk tanaman, contohnya buah cabai. Paper ini menyajikan desain mekanis, elektris, dan mengaplikasikan Fuzzy Logic Controller sebagai kecerdasan buatan berbasis IoT.
References
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[18]Larasati N., Dewi T., and Oktarina Y., 2017. Object Following Design for a Mobile Robot using Neural Network. Computer Engineering and Application Journal, 6(1), pp. 5-14. doi:10.18495/COMENGAPP.V6I1.189.
[19]Dewi T., Risma P., Oktarina Y., and Roseno M.T., 2017. Neural Network Design for a Mobile Robot Navigation a Case Study. 4th Proc. EECSI. 23-24 Sep. 2017. Yogyakarta: Indonesia. doi:10.1109/EECSI.2017.8239168.
[20]Dewi T., Risma P., Oktarina Y., and Nawawi M., 2017. Neural Network Simulation for Obstacle Avoidance and Wall Follower Robot as a Helping Tool for Teaching-Learning Process in Classroom. 1st Proc. ICEAT, 29-30 November 2017, Mataram: Indonesia. doi:10.1088/1757-899X/403/1/012043
[21]Risma P., Dewi T., Oktarina Y., and Wijanarko Y., 2019. Neural Network Controller Application on a Visual based Object Tracking and Following Robot. Computer Engineering and Application Journal, 8(1). doi: 10.18495/COMENGAPP.V8I1.280.
[2]Y. Mases, T. Dewi, and Rusdianasari, Solar Radiation Effect on Solar Powered Pump Performance of an Automatic Sprinkler System. Paper presented at the Proceedings of 2021 International Conference on Electrical and Information Technology (IEIT), pp. 246-250, 2021.
[3]M. Liao, S. Chen, C. Chou, H. Chen, S. Yeh, Y. Chang, and J. Jiang, On precisely relating the growth of Phalaenopsis leaves to greenhouse environmental factors by using an IoT-based monitoring system, Computers and Electronics in Agriculture, Vol. 136, pp. 125-139, 2017. https://doi.org/10.1016/j.compag.2017.03.003.
[4]Kumar, V. Singh, S. Kumar, S. P. Jaiswal, and V. S. Bhadoria, IoT enabled system to monitor and control greenhouse, Materials Today: Proceedings, Vol. 49, No 8, pp. 3137-3141, 2022. https://doi.org/10.1016/j.matpr.2020.11.040
[5]G. Singh, P. P. Singh, P. P. Singh Lubana, and K.G. Singh, Formulation and validation of a mathematical model of the microclimate of a greenhouse, Renewable Energy, Vol. 31, No 10, pp. 1541-1560, 2006. https://doi.org/10.1016/j.renene.2005.07.011.
[6]H. Kim, D. H. Lee, S. W. Ahn, W. K. Kim, S. O. Hur, J. Y. Choi, S. Chung, Design and testing of an autonomous irrigation controller for precision water management of greenhouse crops, Engineering in Agriculture, Environment and Food, Vol. 8, No 4, pp. 228-234, 2015. https://doi.org/10.1016/j.eaef.2015.03.001
[7]D. S. Paraforos, H. W. Griepentrog, Multivariable greenhouse climate control using dynamic decoupling controllers, IFAC Proceedings Volumes, Vol. 46, No 18, pp. 305-310, 2013, https://doi.org/10.3182/20130828-2-SF-3019.00064.
[8]Chang, S. Chung, W. Fu, and C. Huang,Artificial intelligence approaches to predict growth, harvest day, and quality of lettuce (Lactuca sativa L.) in a IoT-enabled greenhouse system, Biosystems Engineering, Vol. 212, pp. 77-105, 2021. https://doi.org/10.1016/j.biosystemseng.2021.09.015.
[9]F. Hahn, Fuzzy controller decreases tomato cracking in greenhouses, Computers and Electronics in Agriculture, Vol. 77, No 1, pp. 21-27, 2011. https://doi.org/10.1016/j.compag.2011.03.003.
[10]H. Benyezza, M. Bouhedda, and S. Rebouh, Zoning irrigation smart system based on fuzzy control technology and IoT for water and energy saving, Journal of Cleaner Production, Vol. 302, p. 127001, 2021. https://doi.org/10.1016/j.jclepro.2021.127001.
[11]Dewi T., Nurmaini S., Risma P., Oktarina Y., and Roriz M., 2019, Inverse Kinematic Analysis of 4 DOF Pick and Place Arm Robot Manipulator using Fuzzy Logic Controller, IJECE, 10(2), pp. 1376-1386. doi:10.11591/ijece.v10i2.pp1376-1386.
[12]F. Septiarini, T. Dewi and Rusdianasari, Design of a solar-powered mobile manipulator using fuzzy logic controller of agriculture application, International Journal of Computational Vision and Robotics, Inderscience, Vol. 12, No. 5, pp. 506-531, 2022. https://doi.org/10.1504/IJCVR.2022.125356.
[13]Dewi T., Risma P., and Oktarina Y., 2018, Fuzzy Logic Simulation as a Teaching-learning Media for Artificial Intelligence Class, Journal of Automation Mobile Robotics and Intelligent Systems, 12(3), pp. 3-9.doi: 10.14313/JAMRIS_3-2018/13
[14]Dewi T., Oktarina Y., Risma P., and Kartini S., 2019, Desain Robot Pengikut Manusia Sederhana dengan Fuzzy Logic Controller, Proc. Annual Research Seminar (ARS), 5(1), pp. 12-16, 16 Nov 2019, Palembang: Indonesia.
[15]Oktarina Y., Septiarini F., Dewi T., Risma P., and Nawawi M., 2019, Fuzzy-PID Controller Design of 4 DOF Industrial Arm Robot Manipulator, Computer Engineering and Application Journal, 8(2), pp. 123-136. doi: 10.18495/COMENGAPP.V8I2.300.
[16]T. Dewi, C. Sitompul, P. Risma, and Y. Oktarina, R. Jelista, M. Mulyati M., Simulation Analysis of Formation Control Design of Leader-Follower Robot Using Fuzzy Logic Controller, Proc 2019 ICECOS, 2-3 Oct. 2019, Batam Island: Indonesia. doi:10.1109/ICECOS47637.2019.8984433
[17]Yudha H. M., Dewi T., Hasana N., Risma P., Oktarina, Y. Kartini S., 2019, Performance Comparison of Fuzzy Logic and Neural Network Design for Mobile Robot Navigation, Proc. 2019 ICECOS, 2-3 Oct. 2019, Batam Island: Indonesia. doi:10.1109/ICECOS47637.2019.8984577
[18]Larasati N., Dewi T., and Oktarina Y., 2017. Object Following Design for a Mobile Robot using Neural Network. Computer Engineering and Application Journal, 6(1), pp. 5-14. doi:10.18495/COMENGAPP.V6I1.189.
[19]Dewi T., Risma P., Oktarina Y., and Roseno M.T., 2017. Neural Network Design for a Mobile Robot Navigation a Case Study. 4th Proc. EECSI. 23-24 Sep. 2017. Yogyakarta: Indonesia. doi:10.1109/EECSI.2017.8239168.
[20]Dewi T., Risma P., Oktarina Y., and Nawawi M., 2017. Neural Network Simulation for Obstacle Avoidance and Wall Follower Robot as a Helping Tool for Teaching-Learning Process in Classroom. 1st Proc. ICEAT, 29-30 November 2017, Mataram: Indonesia. doi:10.1088/1757-899X/403/1/012043
[21]Risma P., Dewi T., Oktarina Y., and Wijanarko Y., 2019. Neural Network Controller Application on a Visual based Object Tracking and Following Robot. Computer Engineering and Application Journal, 8(1). doi: 10.18495/COMENGAPP.V8I1.280.
Published
2023-09-14
How to Cite
Rinaldi, R., Dewi, T., & Oktarina, Y. (2023). Implementasi Fuzzy Logic dalam Mengendalikan Input dan Output pada Penyiraman dan Pemupukan Tanaman Otomatis Berbasis IoT. Journal of Applied Smart Electrical Network and Systems, 3(02), 65-73. https://doi.org/10.52158/jasens.v3i02.520
Section
Articles
Copyright (c) 2023 Rinaldi Rinaldi, Tresna Dewi, Yurni Oktarina
This work is licensed under a Creative Commons Attribution 4.0 International License.
