Application of the C4.5 Algorithm to Predict Patient Service Satisfaction at Brangsong I Community Health Center
Abstract
The quality of health services is essential to public health center services. One of the influencing factors is the level of patient satisfaction with the services provided. This research aims to predict patient satisfaction at Brangsong I Community Health Center using the C4.5 algorithm and determine the accuracy of the results. The first step is the collection of data which is carried out by the distribution of questionnaires to be completed by patients, then secondly the results of the questionnaire are analyzed for a summary in Excel form. Perform calculations to find the gain and entropy. The results obtained by the service flow obtained the highest gain, which was 0.4974. Then, calculations are performed on the dimensions of the service flow until its completion. The research testing process used RapidMiner software to create a decision tree. The accuracy of the calculation results is 98%. The value of the gain can be influenced by the treatment reserved for the data used during the search. Based on the analysis results, it is hoped that it can improve the performance of Brangsong I Community Health Center by providing better services to patients.
References
[2] V. Sesrianty, R. Machmud, and F. Yeni, “Analisa Kepuasan Pasien Terhadap Mutu Pelayanan Keperawatan,” J. Kesehat. PERINTIS (Perintis’s Heal. Journal), vol. 6, no. 2, pp. 116–126, 2019, doi: 10.33653/jkp.v6i2.317.
[3] D. F. Eprilianto, Y. E. K. Sari, and B. Saputra, “Mewujudkan Integrasi Data Melalui Implementasi Inovasi Pelayanan Kesehatan Berbasis Teknologi Digital,” JPSI (Journal Public Sect. Innov., vol. 4, no. 1, p. 30, 2019, doi: 10.26740/jpsi.v4n1.p30-37.
[4] R. S. Wahono, Data Mining Data mining, vol. 2, no. January 2013. 2023. [Online]. Available: https://www.cambridge.org/core/product/identifier/CBO9781139058452A007/type/book_part
[5] Reza Fauzy, Riki Winanjaya, and Susiani, “Analisis Tingkat Kepuasan Pelanggan dengan Menerapkan Algoritma C4.5,” Bull. Comput. Sci. Res., vol. 2, no. 2, pp. 41–46, 2022, doi: 10.47065/bulletincsr.v2i2.162.
[6] A. S. Febriarini and E. Z. Astuti, “Penerapan Algoritma C4.5 untuk Prediksi Kepuasan Penumpang Bus Rapid Transit (BRT) Trans Semarang,” Eksplora Inform., vol. 8, no. 2, pp. 95–103, 2019, doi: 10.30864/eksplora.v8i2.156.
[7] A. R. Damanik, S. Sumijan, and G. W. Nurcahyo, “Prediksi Tingkat Kepuasan dalam Pembelajaran Daring Menggunakan Algoritma Naïve Bayes,” J. Sistim Inf. dan Teknol., vol. 3, pp. 88–94, 2021, doi: 10.37034/jsisfotek.v3i3.49.
[8] R. Septia Sari, Y. Desnita Tasri, and R. Shakila, “Sosialisasi Manajemen Klinis untuk peningkatan mutu pelayanan kesehatan bagi Profesional Perekam Medis,” ABDINE J. Pengabdi. Masy., vol. 1, no. 2, pp. 147–158, 2021, doi: 10.52072/abdine.v1i2.220.
[9] Jetslin Simbolon and Selviani Damayanti Sipayung, “Analisis Kualitas Pengelolaan Mutu Pelayanan Pendaftaran Pasien di Instalasi Rawat Inap Rumah Sakit Santa Elisabeth Medan,” SEHATMAS J. Ilm. Kesehat. Masy., vol. 1, no. 4, pp. 591–599, 2022, doi: 10.55123/sehatmas.v1i4.937.
[10] Y. Bastian et al., “Analisis Penerapan Algoritma C4.5 Dalam Mengukur Tingkat Kepuasan Pelanggan Indihome Pada Kota Pematangsiantar,” Januari, vol. 2, no. 1, pp. 62–69, 2021.
[11] I. Romli and A. T. Zy, “Penentuan Jadwal Overtime Dengan Klasifikasi Data Karyawan Menggunakan Algoritma C4.5,” J. Sains Komput. Inform. (J-SAKTI, vol. 4, no. 2, pp. 694–702, 2020.
[12] Irnanda, “Penerapan Klasifikasi C4.5 Dalam Meningkatkan Kecakapan Berbahasa Inggris dalam Masyarakat,” Semin. Nas. Teknol. Komput. Sains, pp. 304–308, 2020.
[13] R. Nofitri and N. Irawati, “Analisis Data Hasil Keuntungan Menggunakan Software Rapidminer,” JURTEKSI (Jurnal Teknol. dan Sist. Informasi), vol. 5, no. 2, pp. 199–204, 2019, doi: 10.33330/jurteksi.v5i2.365.
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