Klasifikasi Penderita Penyakit Diabetes Berdasarkan Decision Tree Menggunakan Algoritma C4.5
Abstract
Diabetes is a metabolic disease characterized by high blood sugar levels (hyperglycemia) caused by a lack of insulin or the ineffectiveness of insulin in regulating glucose metabolism. In addition there are other factors that cause diabetes such as heredity, weight, age, blood pressure and so on. It is estimated that the death rate caused by diabetes will continue to increase every year. Treatment of diabetes can be done by controlling blood sugar levels, eating a healthy diet, exercising regularly, and if necessary, carrying out early checks to reduce the risk of developing diabetes. Therefore it is necessary to have an early diagnosis which is expected to reduce diabetes and reduce complications of diabetes in the future. One thing that can be done is to apply the method contained in data mining, namely utilizing the classification method using the C4.5 algorithm which can produce more accuracy. Classification can be used as early treatment of this disease. Algorithm C4.5 is an algorithm that is used to form a decision tree. From the test results, it produces a fairly large accuracy, namely 85% Precision of 92%, and Recall of 85%.
Full Text:
downloadReferences
Alverina, Dea, Antonius Rachmat Chrismanto, and R. Gunawan Santosa. 2018. “Perbandingan Algoritma C4.5 Dan CART Dalam Memprediksi Kategori Indeks Prestasi Mahasiswa.” Jurnal Teknologi dan Sistem Komputer 6(2): 76–83.
Argina, Andi Maulida. 2020. “Penerapan Metode Klasifikasi K-Nearest Neigbor Pada Dataset Penderita Penyakit Diabetes.” Indonesian Journal of Data and Science 1(2): 29–33.
Baharuddin, Mus Mulyadi, Huzain Azis, and Tasrif Hasanuddin. 2019. “Analisis Performa Metode K-Nearest Neighbor Untuk Identifikasi Jenis Kaca.” ILKOM Jurnal Ilmiah 11(3): 269–74.
“Diabetes Mellitus.” 2020. Pusat Data Dan Informasi Kementrian Kesehatan Republik Indonesia. https://pusdatin.kemkes.go.id/article/view/20111800001/diabetes-melitus.html.
Eska, Juna. 2016. “Penerapan Data Mining Untuk Prekdiksi Penjualan Wallpaper Menggunakan Algoritma C4.5 STMIK Royal Ksiaran.” JURTEKSI (Jurnal Teknologi dan Sistem Informasi) 2: 9–13.
Ginantra, Ni Luh Wiwik Sri Rahayu et al. 2021. Data-Mining-Algoritma-Dan-Implementasi-1638852186.
Hadianto, Nur, Hafifah Bella Novitasari, and Ami Rahmawati. 2019. “Klasifikasi Peminjaman Nasabah Bank Menggunakan Metode Neural Network.” Jurnal Pilar Nusa Mandiri 15(2): 163–70.
Han, Jiwei, Micheline Kamber, and Jian Pei. 2012. Data Mining: Data Mining Concepts and Techniques. Thirrd. Morgan Kauffman Publishers.
Hapsari, R K, M I Utoyo, R Rulaningtyas, and H Suprajitno. 2020. “Iris Segmentation Using Hough Transform Method and Fuzzy C-Means Method.” Journal of Physics: Conference Series 1477: 022037. https://iopscience.iop.org/article/10.1088/1742-6596/1477/2/022037.
Iqbal, Muchamad, Wendi Usino, and Triono Triono. 2020. “Sistem Pendukung Keputusan Menentukan Hasil Budidaya Udang Vaname Dengan Metode Algoritma C4.5 (Pt Anugerah Sumber Laut Jaya).” Jurnal Tekno Insentif 14(1): 28–39.
Junaedi, Ifan, Ndaru Nuswantari, and Verdi Yasin. 2019. “Perancangan Dan Implementasi Algoritma C4 . 5 Untuk Data Mining.” Journal of Information System, Informatics and Computing 3(1): 29–44. http://journal.stmikjayakarta.ac.id/index.php/jisicom/article/view/203%0Ahttp://journal.stmikjayakarta.ac.id/index.php/jisicom/article/download/203/158.
Kadhm, Mustafa S, Doaa N Mhawi, Ikhlas Watan Ghindawi, and Duaa Enteesha Mhawi. 2018. “An Accurate Diabetes Prediction System Based on K-Means Clustering and Proposed Classification Approach.” International Journal of Applied Engineering Research 13(6): 4038–41. http://www.ripublication.com.
Khotimah, Nur, and Deden Istiawan. 2018. “Perbandingan Algoritma C4.5, Naïve Bayes Dan K-Nearest Neighbour Untuk Prediksi Lahan Kritis Di Kabupaten Pemalang.” Urecol 7(1): 41–50.
Lathifah, Nur Lailatul. 2017. “Hubungan Durasi Penyakit Dan Kadar Gula Darah Dengan Keluhan Subyektif Penderita Diabetes Melitus.” Jurnal Berkala Epidemiologi 5(2): 231–39. https://e-journal.unair.ac.id/JBE/article/view/4781.
Oktanisa, Irvi, and Ahmad Afif Supianto. 2018. “Perbandingan Teknik Klasifikasi Dalam Data Mining Untuk Bank Direct Marketing.” Jurnal Teknologi Informasi dan Ilmu Komputer 5(5): 567.
Pramadani, E, H Sunandar, and ... 2019. “Implementasi Data Mining Penjualan Koran Dengan Metode C4. 5 (Studi Kasus: Pt. Media Massa Cahaya Pembaharuan).” Informasi dan … 6: 11–15. https://www.ejurnal.stmik-budidarma.ac.id/index.php/inti/article/view/1012%0Ahttps://www.ejurnal.stmik-budidarma.ac.id/index.php/inti/article/download/1012/871.
Reza Noviansyah, M et al. 2018. “Penerapan Data Mining Menggunakan Metode K-Nearest Neighbor Untuk Klasifikasi Indeks Cuaca Kebakaran Berdasarkan Data Aws (Automatic Weather Station) (Studi Kasus: Kabupaten Kubu Raya).” Jurnal Coding, Sistem Komputer Untan 06(2): 48–56.
Simanjuntak, Krisna Ferdinan Leo, Annita Carolina Br Barus, and Anita. 2021. “Implementasi Metode Decision Tree Dan Algoritma C4.5 Untuk Klasifikasi Kepribadian Masyarakat.” JOISIE Journal Of Information System And Informatics Engineering 5(1): 51–59.
Sutoyo, Imam. 2018. “Implementasi Algoritma Decision Tree Untuk Klasifikasi Data Peserta Didik.” Jurnal Pilar Nusa Mandiri 14(2): 217.
Widyasari, Nina. 2017. “HUBUNGAN KARAKTERISTIK RESPONDEN DENGAN RISIKO DIABETES MELITUS DAN DISLIPIDEMIA KELURAHAN TANAH KALIKEDINDING.” Jurnal Berkala Epidemiologi 5(April 2017): 130–41.
Yunus, Muhamad, Hanandriya Ramadhan, Dimas Rizki Aji, and Agus Yulianto. 2021. “Penerapan Metode Data Mining C4.5 Untuk Pemilihan Penerima Kartu Indonesia Pintar (KIP).” Paradigma - Jurnal Komputer dan Informatika 23(2).
Zulma, G D M, and N Chamidah. 2021. “Perbandingan Metode Klasifikasi Naive Bayes, Decision Tree Dan K-Nearest Neighbor Pada Data Log Firewall.” Senamika (April): 679–88. https://conference.upnvj.ac.id/index.php/senamika/article/view/1396.
Refbacks
- There are currently no refbacks.
