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Developing Data Mining Prediction System for Health Center Medicine Inventory using Naïve Bayes Classifier Algorithm

*Roziana Roziana orcid  -  Department of Information Systems, Postgraduate Faculty, Universitas Diponegoro, Indonesia
Aris Puji Widodo orcid  -  Department of Informatics, Faculty of Science and Mathematics, Universitas Diponegoro, Indonesia
Adi Wibowo orcid  -  Department of Informatics, Faculty of Science and Mathematics, Universitas Diponegoro, Indonesia
Open Access Copyright (c) 2024 Jurnal Sistem Informasi Bisnis

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Abstract

Public health centers mostly use conventional methods in managing drug supply, usage, and demand data, without a system that can predict the number of drug requests. This research aims to develop a data mining solution by implementing a prediction system using the Naïve Bayes Classifier algorithm to predict drug supplies from the Koni Health Center, Jambi, to the Health Office Pharmacy Installation. The method applied in this research is a quantitative approach through the experimental method. The research data includes inventory, usage, and remaining stock of various types of drugs from 2017 to 2021 which are divided into four quarters. The results of this study show that the classification system using the Naïve Bayes Classifier method is able to classify data quickly and efficiently according to drug supply. The system test results show an accuracy of 73.91%, recall of 85.71%, and precision of 54.54%. These findings can help Puskesmas in optimizing drug inventory management, reducing errors in inventory estimates, and increasing accuracy in meeting patient drug requests.

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Keywords: Naïve Bayes Classifier Algorithm; Medicine Supply; Puskesmas; Prediction system

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  1. Abdianto, D., Elisawati, Tawakal, F., Masrizal. 2021. Prediksi Stok Obat Menggunakan Metode Learning Vector Quantization Studi Kasus Puskesmas Dumai Barat. Prosiding Seminar Nasional Sains dan Teknologi, 1(1), 68-74. http://dx.doi.org/10.36499/psnst.v1i1.5093
  2. Barus, S.P., 2021. Implementation of Naïve Bayes Classifier-based Machine Learning to Predict and Classify New Students at Matana University. Journal of Physics: Conference Series, 1842(1). https://doi.org/10.1088/1742-6596/1842/1/012008
  3. Danianty, M.D., Suhery, C., Hidayati, R., 2020. Prediksi Jumlah Kebutuhan Obat Menggunakan Metode Least Square Berbasis Website (Studi Kasus: UPTD Puskesmas Pontianak Selatan). Coding: Jurnal Komputer dan Aplikasi, 8(2), 33-42. https://dx.doi.org/10.26418/coding.v8i2.41495
  4. Hidayatullah, S., Khouroh, U., Windhyastiti, I., Patalo, R.G., Waris, A., 2020. Implementasi Model Kesuksesan Sistem Informasi DeLone and McLean terhadap Sistem Pembelajaran Berbasis Aplikasi Zoom di Saat Pandemi Covid-19. Jurnal Teknologi dan Manajemen Informatika, 6(1), 44-52. https://doi.org/10.26905/jtmi.v6i1.4165
  5. Jaya, T.S., Yusman, M., 2021. Predicting the Quality of Pineapple Using the Naive Bayes Classifier Method. IOP Conference Series: Earth and Environmental Science, 1012(1). https://doi.org/10.1088/1755-1315/1012/1/012088
  6. Jin, G., Wang, D., Yang, D., Hong, D., Dong, Q., Wang, Y., 2020. Role and Object Domain-Based Access Control Model for Graduate Education Information System. Procedia Computer Science, 176, 1241-1250. https://doi.org/10.1016/j.procs.2020.09.133
  7. Kurniawan, A., Tamtomo, D., Murti, B., 2017. Evaluation of Community Health Center Management Information System (SIMPUS), Primary Care (P Care), and Bridging Data System in Sukoharjo District. Journal of Health Policy and Management, 2(2), 157-164. https://doi.org/10.26911/thejhpm.2017.02.02.07
  8. Mentang, J.J., Rumayar, A.A., Kolibu, F.K., 2018. Hubungan Antara Kualitas Jasa Pelayanan Kesehatan dengan Kepuasan Pasien di Puskesmas Taratara Kota Tomohon. Jurnal KESMAS, 7(5)
  9. Saputra, A.M., 2020. Sistem Prediksi Persediaan Obat pada Apotek Menggunakan Metode Naive Bayes (Studi Kasus: Apotek Seger Waras, Cianjur). Disertasi. Jakarta: Universitas Teknologi
  10. Sembiring, M.T., Tambunan, R.H., 2021. Analysis of graduation prediction on time based on student academic performance using the Naïve Bayes Algorithm with data mining implementation (Case study: Department of Industrial Engineering USU). IOP Conference Series: Materials Science and Engineering, 1122(1), 012069. https://doi.org/10.1088/1757-899x/1122/1/012069
  11. Siburian, L., 2021. Data Mining Memprediksi Kebutuhan Vaksin Imunisasi dengan Menggunakan Metode Naive Bayes (Studi kasus UPT Puskesmas Teladan). RESOLUSI: Rekayasa Teknik Informatika dan Informasi, 1(5), 282-290. https://doi.org/10.30865/resolusi.v1i5.164
  12. Siregar, I.A.M., Elvianna, Saepul, N., 2018. Sistem Informasi Persediaan Obat dengan Metode Naïve Bayes Pada RSUD Tanjungpinang. Jurnal Bangkit Indonesia, 7(1), 188-195. https://doi.org/10.52771/bangkitindonesia.v7i1.168
  13. Tabsoba, L.S.K., Traore, Y., Malo, S., 2023. Interoperability Approach for Hospital Information Systems Based on the Composition of Web Services. Procedia Computer Science, 219, 1161-1168. https://doi.org/10.1016/j.procs.2023.01.397
  14. Tugiman, Damayanti, L., Gunawan, A.H., Elkana, S.R., 2022. Prediksi Penggunaan Obat Peserta Jaminan Kesehatan Nasional Menggunakan Algoritma Naïve Bayes Classifier. Journal of Applied Computer Science and Technology, 3(1), 144-150. https://doi.org/10.52158/jacost.v3i1.295
  15. Wahyuni, S., Marbun, M., 2020. Implementation of Data Mining in Predicting the Study Period of Student Using the Naïve Bayes Algorithm. IOP Conference Series: Materials Science and Engineering, 769(1). https://doi.org/10.1088/1757-899X/769/1/012039
  16. Wardani, A.T., Putri, O.L.A., Yuliani, R.D., 2022. Design of a Service Information System at Posyandu in Glagah, Mertoyudan. Restorica: Jurnal Ilmiah Administrasi dan Ilmu Komunikasi, 8(2), 32-36. https://doi.org/10.33084/restorica.v8i2.3631
  17. Yogananda, A.A., 2021. Hubungan Kualitas Sistem Informasi Farmasi dengan Pengguna dalam Mendukung Pengelolaan Obat di Puskesmas Kota Yogyakarta. Jurnal Ilmiah Kefarmasian. 2(1), 77-85. http://dx.doi.org/10.36760/jp.v2i1.167
  18. Zheng, J., Yang, W., Wang, C., Jiang, D., Wang, D., Yang, Q., Zhang, Y., 2022. Research on complaint prediction based on feature weighted Naive Bayes. IOP Conference Series: Earth and Environmental Science, 983(1). https://doi.org/10.1088/1755-1315/983/1/012117
  19. , 1161-1168. https://doi.org/10.1016/j.procs.2023.01.397
  20. Tugiman, Damayanti, L., Gunawan, A.H., Elkana, S.R., 2022. Prediksi Penggunaan Obat Peserta Jaminan Kesehatan Nasional Menggunakan Algoritma Naïve Bayes Classifier. Journal of Applied Computer Science and Technology, 3(1), 144-150. https://doi.org/10.52158/jacost.v3i1.295
  21. Wahyuni, S., Marbun, M., 2020. Implementation of Data Mining in Predicting the Study Period of Student Using the Naïve Bayes Algorithm. IOP Conference Series: Materials Science and Engineering, 769(1). https://doi.org/10.1088/1757-899X/769/1/012039
  22. Wardani, A.T., Putri, O.L.A., Yuliani, R.D., 2022. Design of a Service Information System at Posyandu in Glagah, Mertoyudan. Restorica: Jurnal Ilmiah Administrasi dan Ilmu Komunikasi, 8(2), 32-36. https://doi.org/10.33084/restorica.v8i2.3631
  23. Yogananda, A.A., 2021. Hubungan Kualitas Sistem Informasi Farmasi dengan Pengguna dalam Mendukung Pengelolaan Obat di Puskesmas Kota Yogyakarta. Jurnal Ilmiah Kefarmasian. 2(1), 77-85. http://dx.doi.org/10.36760/jp.v2i1.167
  24. Zheng, J., Yang, W., Wang, C., Jiang, D., Wang, D., Yang, Q., Zhang, Y., 2022. Research on complaint prediction based on feature weighted Naive Bayes. IOP Conference Series: Earth and Environmental Science, 983(1). https://doi.org/10.1088/1755-1315/983/1/012117
  25. Mentang, J.J., Rumayar, A.A., Kolibu, F.K., 2018. Hubungan Antara Kualitas Jasa Pelayanan Kesehatan dengan Kepuasan Pasien di Puskesmas Taratara Kota Tomohon. Jurnal KESMAS, 7(5)
  26. Saputra, A.M., 2020. Sistem Prediksi Persediaan Obat pada Apotek Menggunakan Metode Naive Bayes (Studi Kasus: Apotek Seger Waras, Cianjur). Disertasi. Jakarta: Universitas Teknologi
  27. Sembiring, M.T., Tambunan, R.H., 2021. Analysis of graduation prediction on time based on student academic performance using the Naïve Bayes Algorithm with data mining implementation (Case study: Department of Industrial Engineering USU). IOP Conference Series: Materials Science and Engineering, 1122(1), 012069. https://doi.org/10.1088/1757-899x/1122/1/012069
  28. Siburian, L., 2021. Data Mining Memprediksi Kebutuhan Vaksin Imunisasi dengan Menggunakan Metode Naive Bayes (Studi kasus UPT Puskesmas Teladan). RESOLUSI: Rekayasa Teknik Informatika dan Informasi, 1(5), 282-290. https://doi.org/10.30865/resolusi.v1i5.164
  29. Siregar, I.A.M., Elvianna, Saepul, N., 2018. Sistem Informasi Persediaan Obat dengan Metode Naïve Bayes Pada RSUD Tanjungpinang. Jurnal Bangkit Indonesia, 7(1), 188-195. https://doi.org/10.52771/bangkitindonesia.v7i1.168
  30. Tabsoba, L.S.K., Traore, Y., Malo, S., 2023. Interoperability Approach for Hospital Information Systems Based on the Composition of Web Services. Procedia Computer Science,

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