Prediksi Penggunaan Obat Peserta Jaminan Kesehatan Nasional Menggunakan Algoritma Naïve Bayes Classifier

  • Tugiman Universitas Buddhi Dharma https://orcid.org/0000-0003-1986-2922
  • Lily Damayanti Universitas Buddhi Dharma
  • Alexius Hendra Gunawan Universitas Buddhi Dharma
  • Samuel Ryon Elkana Universitas Buddhi Dharma
Keywords: Naive Bayes Classifier, User Acceptance Test, Prediction, National Health Insurance

Abstract

Currently, most of the patients seeking treatment at the hospital use the National Health Insurance (JKN) organized by the Healthcare and Social Security Agency (BPJS Kesehatan). In some hospitals, the figure is above 80%. Considering the very high number of BPJS Kesehatan participant seeking treatment at the hospital, a good data management method is needed, especially regarding the management of drug. Drug supply needs to be analyzed from time to time so that it can help predict future needs. An adequate supply of drugs and as needed is one of the things that affect service to patients. The availability of sufficient stock is expected to accelerate service to patients so that they do not have to wait long. Patients who are served quickly are expected to be satisfied. The impact of this patient satisfaction will increase the number of patient visits to the hospital. To support this, it is necessary to create a system that can estimate drug needs. The system can predict drug demand by using drug sales data to JKN participant patients for five years. Drug data used as research samples and then processed using an algorithm is the Naive Bayes Classifier. The Naive Bayes Classifier method is a method used to predict future opportunities using the basis of previous experience. A distinctive feature of this method is that it uses a very strong assumption of the independence of each event. While software testing uses the User Acceptance Test (UAT) model. Based on testing using this method, the system can be well received by users with a score of 78.64% (good).

 

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References

BPJS, Peraturan Badan Penyelenggara Jaminan Sosial nomor 4 tahun 2019. 2019.

Perpres, Peraturan Presiden Republik Indonesia Nomor 82 Tahun 2018 tentang Jaminan Kesehatan. 2018.

BPS, “Statistik Telekomunikasi Indonesia 2019,” 2019, [Online]. Available: https://www.bps.go.id/publication/2020/12/02/be999725b7aeee62d84c6660/statistik-telekomunikasi-indonesia-2019.html.

J. Suntoro, Data Mining Algoritma dan Implementasi dengan Pemrograman PHP. Jakarta: PT. Elex Media Komputindo, 2019.

M. Haldi Widianto, “Algoritma Naive Bayes,” 2019. [Online]. Available: https://binus.ac.id/bandung/2019/12/algoritma-naive-bayes/.

H. Derajad Wijaya, “Implementasi Data Mining dengan Algoritma Naive Bayes pada Penjualan Obat,” J. Inform., 2020, [Online]. Available: https://ejournal.bsi.ac.id/ejurnal/index.php/ji/article/viewFile/6203/pdf.

F. Tjiptono and G. Chandra, Pemasaran Strategik, Edisi 2. Yogyakarta: Andi Offset, 2012.

A. Amriana, Y. Y. Joefrie, and F. N. Meidji, “Penerapan Data Mining Untuk Pengelompokan Hasil Diagnosa Penyakit Pasien Pengguna BPJS Kesehatan (Studi Kasus Pada Rsud Undata Palu),” Sci. Comput. Sci. Informatics J., vol. 1, no. 1, p. 51, 2019, doi: 10.22487/j26204118.2018.v1.i1.11901.

Sudaryono, Metodologi Riset di Bidang TI. Yogyakarta: Andi Offset, 2014.

M. Yusuf, Metode Penelitian Kuantitatif, Kualitatif & Penelitain Gabungan, Edisi Pert. Jakarta: Frenadamedia Group, 2014.

O’Brien James, Sistem Informasi Manajemen, Edisi 9. Jakarta: Salemba Empat, 2014.

Suyanto, Data Mining Untuk Klasifikasi Dan Klasterisasi Data, Edisi Revi. Bandung: Informatika, 2019.

Afrizal, Metode Penelitian Kualitatif Supaya mendukung penggunaan penelitian kualitatif dalam berbagai disiplin ilmu. Raja Frafindo Persada, 2014.

A. Basri, V. Kuswanto, and A. Leo, “Rancang Bangun Bridging Sistem Pendaftaran dan Aplikasi Mobile Jaminan Kesehatan Nasional ( JKN ),” vol. 5, pp. 11–20, 2022.

Published
2022-06-04
How to Cite
[1]
Tugiman, Lily Damayanti, Alexius Hendra Gunawan, and Samuel Ryon Elkana, “Prediksi Penggunaan Obat Peserta Jaminan Kesehatan Nasional Menggunakan Algoritma Naïve Bayes Classifier”, J. Appl. Comput. Sci. Technol., vol. 3, no. 1, pp. 144 - 150, Jun. 2022.
Section
Articles
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