Data Mining Tingkat Kepatuhan Pasien Tuberkulosis dalam Menjalani Pengobatan Mengunakan Agloritma C4.5
DOI:
https://doi.org/10.37034/jsisfotek.v5i2.170Keywords:
Data Mining, Compliance Rate, Tuberculosis (TB), C4.5, Decision TreeAbstract
The high number of TB cases in the work area of the Bukittinggi City Health Service Puskesmas Nilam Sari. The number of patients who do not comply with TB treatment. This study was conducted to determine the level of patient compliance in undergoing TB treatment so that the results of the study become input for medical personnel in charge of TB at Nilam Sari Health Center in policy making. The C4.5 method was used in this study to classify the data of compliant and non-adherent TB patients in undergoing treatment at the Nilam Sari Health Center. The data from TB patient visits to the Puskesmas were analyzed using the C4.5 method to obtain new knowledge from the TB patient visit data to the Puskesmas. The data analyzed consisted of attributes of the visit schedule, environmental distance, age which influenced the decision criteria for the level of adherence of TB patients in undergoing treatment at the Nilam Sari Health Center. The decision criteria for the results of TB patient visits consist of "Complied" and Non-Complied" which refers to the decision criteria for the TB patient's visit schedule. Tests conducted on the training data of the visit schedule of the attribute that most influence the decision on the level of adherence of TB patients in undergoing treatment. The implementation of the results using Weka 3.6.9 software and produces an accuracy of compliant patients of 13.4615% and accuracy of non-adherent patients of 86.5385%. The results of the classification method C.4.5 were greater in patients who were not compliant than patients who were obedient in undergoing TB treatment at the Nilan Sari Health Center. The test results have been able to help medical personnel in the Bukittinggi City Health Office work area in undergoing treatment to be able to make a policy for handling TB cases in the future.
References
Kasron, K., Susilawati, S., & Subroto, W. (2021). PKM Penanganan Stunting Desa Kawunganten Lor Kecamatan Kawunganten Kabupaten Cilacap: Sasaran Keluarga Dengan Anak Stunting. Abdi Geomedisains, 87-91. https://doi.org/10.23917/abdigeomedisains.v1i2.207
Sugiyanto, H. S., & Musfirati, A. (2021). Pengaruh Dana Alokasi Umum, Dana Alokasi Khusus, Dana Bagi Hasil, Dan Dana Keistimewaan Terhadap Tingkat Kemandirian Keuangan Daerah. Substansi: Sumber Artikel Akuntansi Auditing Dan Keuangan Vokasi, 5(1), 20-36. https://doi.org/10.35837/subs.v5i1.1382
Annisa, K., Ginting, B. S., & Syari, M. A. (2022). Penerapan Data Mining Pengelompokan Data Pengguna Air Bersih Berdasarkan Keluhannya Menggunakan Metode Clustering Pada PDAM Langkat. Algoritma: Jurnal Ilmu Komputer Dan Informatika, 6(1). http://dx.doi.org/10.30829/algoritma.v6i1.11624
Susanto, S., & Nuri, N. (2022). Klasifikasi Hepatitis C Virus Menggunakan Algoritma C4. 5. Jurnal Disprotek, 13(2), 43-48. https://doi.org/10.34001/jdpt.v13i2.3052
Sauddin, A., & Ida, N. (2022). Penerapan Pohon Keputusan Dalam Memprediksi Masa Studi Mahasiswa Uin Alauddin Makassar. Jurnal INSTEK (Informatika Sains dan Teknologi), 7(2), 201-210. https://doi.org/10.24252/instek.v7i2.31390
Adriansa, M., Yulianti, L., & Elfianty, L. (2022). Analisis Kepuasan Pelanggan Menggunakan Algoritma C4. 5. Jurnal Teknik Informatika UNIKA Santo Thomas, 115-121. https://doi.org/10.54367/jtiust.v7i1.1983
Marisa, F., & Maukar, A. L. (2022). Analisa Prediksi Varietas Buah Salak yang Sesuai dengan Lahan Daerah Kabupaten Banjarnegara Menggunakan Algoritma C45. Jurnal Teknologi dan Manajemen Informatika, 8(1), 20-25. https://doi.org/10.26905/jtmi.v8i1.7521
Girsang, R., Ginting, E. F., & Hutasuhut, M. (2022). Penerapan Algoritma C4. 5 Pada Penentuan Penerima Program Bantuan Pemerintah Daerah. Jurnal Sistem Informasi Triguna Dharma (JURSI TGD), 1(4), 449-459. https://doi.org/10.53513/jursi.v1i4.5727
Zamra, N. (2022). T Tingkat Pengetahuan Masyarakat Tentang Penyakit Tuberkulosis di Kelurahan Rintis Pekanbaru: Level of Public Knowledge about Tuberculosis at Rintis Village Pekanbaru. Jurnal Penelitian Farmasi Indonesia, 11(1), 1-6. https://doi.org/10.51887/jpfi.v11i1.1414
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