PENERAPAN DATA MINING UNTUK PREDIKSI PENINGKATAN JUMLAH ORANG DENGAN GANGGUAN JIWA (ODGJ) DI KOTA PADANG MENGGUNAKAN METODE K-MEANS
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Abstract
This study aims to apply the K-Means algorithm to predict the risk of an increase in the number of People with Mental Disorders (ODGJ) at Prof. Dr. HB. Saanin Mental Hospital. The focus is on clustering patient data based on primary diagnoses such as biological, psychological, and social factors to identify patterns that can predict low, medium, and high-risk increases. The research is motivated by the difficulties faced by relevant parties in analyzing ODGJ data in Padang City. The method used is data mining, specifically the K-Means algorithm, to identify patterns of increased ODGJ risk. The analyzed data includes inpatient and outpatient records for the year 2024. The results show that the K-Means algorithm can effectively cluster sub-districts in Padang City based on their risk of increase, with high-risk areas identified as Koto Tangah, Kuranji, and Lubuk Begalung. Testing using RapidMiner yielded results consistent with manual analysis. The implementation of a developed web-based system provides convenience for administrators in efficiently managing patient data, with features for recording the number of patient admissions. The findings of this study are expected to contribute to the development of information systems in the health sector and serve as a reference for future research.
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References
M. Audina, “Penerapan Data Mining Untuk Klasifikasi Gangguan Jiwa Menggunakan Metode Fuzzy Logic,” 2019.
M. Ghozi Ghozali, N. Mega Saraswati, R. Cipta Sigitta Hariyono, J. K. Raya Pagojengan, And P. Brebes, “Penerapan Algoritma K-Means Dan Algoritma Naive Bayes Dalam Pemilihan Konsentrasi Jurusan Siswa Di Sma Islam Ta’alumul Huda Bumiayu,” 2021.
R. Hidayatur And A. Arinda, “Penerapan Algoritma Naïve Bayes Untuk Mendiagnosis Dan K-Means Untuk Mengelompokkan Penyakit Gagal Jantung,” 2024.
S. Butsianto And N. T. Mayangwulan, “Penerapan Data Mining Untuk Prediksi Penjualan Mobil Menggunakan Metode K-Means Clustering,” J. Nas. Komputasi Dan Teknol. Inf., Vol. 3, No. 3, Pp. 187–201, 2020, Doi: 10.32672/Jnkti.V3i3.2428.
L. F. Narulita And Q. I. Ahmad, “Penerapan Metode Fuzzy Mamdani Dalam Rancang Bangun Sistem Informasi Prediksi Produksi Barang,” Mult. J. Glob. Multidiscip., Vol. 2, No. 1, Pp. 1016–1026, 2024, [Online]. Available: Https://Journal.Institercom-Edu.Org/Index.Php/Multipleinstitercompublisherhttps://Journal.Institercom-Edu.Org/Index.Php/Multiple
P. Soleh, A. Tholib, And M. N. F. Hidayat, “Penerapan Data Mining Untuk Analisa Pola Pembelian Produk Menggunakan Algoritma Frequent Pattern – Growth,” Rekayasa, Vol. 14, No. 3, Pp. 456–460, Jan. 2022, Doi: 10.21107/Rekayasa.V14i3.11365.
L. Rahmawati, “Penerapan Data Mining Untuk Menentukan Penyebab Kematian Di Indonesia Menggunakan Metode Clustering K-Means Tugas Akhir,” 2023.
M. R. Wijaya, “Implementasi Algoritma K-Means Clustering Dan Naïve Bayes Untuk Mengetahui Faktor Pemicu Dan Jumlah Penderita Stroke Otak Proposal Tugas Akhir,” 2022.
M. A. Rizky, A. S. Puspaningrum, And E. R. Susanto, “Rancang Bangun Sistem Pemenuhan Kebutuhan Gizi Pada Orang Sakit Berbasis Android,” J. Inform. Dan Rekayasa Perangkat Lunak, Vol. 4, No. 3, Pp. 319–325, 2023, Doi: 10.33365/Jatika.V4i3.3707.
D. Tr. Resti Misra Aini, “Analisis Sistem Informasi Akuntansi Penjualan Dalam Menunjang Efektivitas Pengendalian Internal Pada Cv. Surya Kuantan Singingi,” Anal. Sist. Inf. Akunt. Penjualan Dalammenunjang Ef. Pengendali. Intern. Pada Cv. Surya Kuantan Singingi, Vol. Vol. 8, No. No. 1, P. H. 193-207, 2019.
N. Setyorini Utami, “Analisis Rekam Medis Pasien Isolasi Sosial Dengan Menggunakan Algoritma C4.5 Di Rumah Sakit Jiwa Daerah Atma Husada Mahakam Samarinda.”
B. G. Sudarsono And M. I. Leo, “Analisis Data Mining Data Netflix Menggunakan Aplikasi Rapid Miner Analysis Data Mining Netflix Data Using The Rapid Miner,” Vol. 4, No. 1, Pp. 13–21, 2021.
K. P. Bani, “Pigen -A Personal Cloud Storage And File-Sharing Platform,” No. April, 2023.
M. Melany, R. Nur, And D. Aryani, “Pemodelan Basis Data Pada Sistem Informasi Laporan Kinerja Program Studi (Lkps) Berbasis Instrumen Akreditasi Program Studi (Iaps 4.0),” Semin. Nas. Tek. Elektro …, P. 6, 2020.
A. A. Bimantara, P. Korespondensi, And R. D. Gunawan, “Sistem Monitoring Produksi Menggunakan Laravel Dan Cork-Bootstrap,” J. Inf. Technol. Softw. Eng. Comput. Sci., Vol. 1, No. 4, Pp. 143–153, 2023.
Miftahul Huda, Boostrap 4 Belajar Crud Menggunakan Php Dan Mysql, No. 3 (3). 2020.
M. Muslihudin And A. Larasati, “Perancangan Sistem Aplikasi Penerimaan Mahasiswa Baru Di Stmik Pringsewu Menggunakan Php Dan Mysql,” J. Tam (Technology Accept. Model., Vol. 3, No. 1, Pp. 32–29, 2014.
A. Amarulloh, K. Kurniasih, And M. Muchlis, “Analisis Perbandingan Performa Web Service Rest Menggunakan Framework Laravel, Django, Dan Node Js Pada Aplikasi Berbasis Website,” J. Tek. Inform., Vol. 9, No. 1, Pp. 14–19, 2023.