Implementation of Data Mining Using C4.5 Algorithm on Customer Satisfaction in Tirta Lihou PDAM
DOI:
10.47709/cnahpc.v3i1.923Keywords:
C4.5 Algorithm, Data Mining, Customer Satisfaction, PDAM Tirta LihouDimension Badge Record
Abstract
This application applies the C4.5 Algorithm to decide customer satisfaction, the C4.5 algorithm is one of the algorithms used to classify or segment, or group and it is predictive. This type of research is a classification with the concept of data mining involving 150 customers of PDAM Tirta Lihou in Totap Majawa Kab. Simalungun can be categorized as: "Satisfied and Dissatisfied". The meaning of Data Mining is an interdisciplinary subfield of computer science and statistics with the overall objective of extracting information (with intelligent methods) from data sets and converting information into understandable structures for further use. There are 5 criteria that can affect customer satisfaction, among others: Service Facilities (x1), Price Rates (x2), Smooth Water (x3), Corporate Image (x4), and Location (x5). The results of processing the C4.5 method using the RapidMiner Studio 5.3 software mean that Rapid Miner is a solution for analyzing data mining, text mining, and predictive analysis. Rapid Miner uses various descriptive and predictive techniques in providing insight to users so that they can make the best decisions with the level of accuracy, namely, class recall and class precision values, it is explained that the "Satisfied" category produces a class recall of 97.80% and a class precision of 97.80%. 98.89% and the "Not Satisfied" category resulted in a class recall of 98.31% and a class of precision of 96.67%. And the above accuracy results from the calculation of the C4.5 algorithm is 98.0%.
Keywords: C4.5 Algorithm, Data Mining, Customer Satisfaction, PDAM Tirta Lihou
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References
Arifin, M. F., & Fitrianah, D. (2018). Penerapan Algoritma Klasifikasi C4.5 Dalam Rekomendasi Penerimaan Mitra Penjualan Studi Kasus?: PT Atria Artha Persada. InComTech, 8(2), 87–102. https://doi.org/10.22441/incomtech.v8i1.2198
Elisa, E. (2017). Analisa dan Penerapan Algoritma C4.5 Dalam Data Mining Untuk Mengidentifikasi Faktor-Faktor Penyebab Kecelakaan Kerja Kontruksi PT.Arupadhatu Adisesanti. Jurnal Online Informatika, 2(1), 36. https://doi.org/10.15575/join.v2i1.71
Febriyanto, D. B., Handoko, L., & Aisyah, H. (2018). Implementasi Algoritma C4 . 5 Untuk Klasifikasi Tingkat Kepuasan Pembeli Online Shop. 5(6), 569–575.
Junia, A., & Riandari, F. (2019). Data Mining Untuk Mengukur Tingkat Kepuasan Peserta BPJS Ketenagakerjaan. 1(1), 47–51.
Karlena Indriani, / Qonita Tanjung. (2017). Sistem Pendukung Keputusan Kelayakan Kredit Motor Menggunakan Metode NAÏVE BAYES Pada NSC FINANCE Cikampek. Publikasi Jurnal Penelitian Teknik Informatika Universitas Prima Indonesia, 1((UNPRI) Medan), 6–11.
Listriani, D., Setyaningrum, A. H., & Eka, F. (2018). Penerapan Metode Asosiasi Menggunakan Algoritma Apriori pada Aplikasi Analisa Pola Belanja Kosumen (Studi Kasus Toko Buku Gramedia Bintaro). Jurnal Teknik Informatika, 9(2), 120–127. https://doi.org/10.15408/jti.v9i2.5602
Listriani, D., Setyaningrum, A. H., & Eka, F. (2018). Penerapan Metode Asosiasi menggunakan Algoritma Apriori pada Aplikasi Analisa Pola Belanja Konsumen (Studi Kasus Toko Buku Gramedia Bintaro). Jurnal Teknik Informatika, 9(2), 120–127. https://doi.org/10.15408/jti.v9i2.5602
Muzakir, A., & Wulandari, R. A. (2016). Model Data Mining sebagai Prediksi Penyakit Hipertensi Kehamilan dengan Teknik Decision Tree. Scientific Journal of Informatics, 3(1), 19–26. https://doi.org/10.15294/sji.v3i1.4610
Oktafianto. (2016). Analisis Kepuasan MAahasiswa Terhadap Pelayanan Akademik Menggunakan Metode Algoritma C4 . 5. 02(01), 1–11.
Putri, A. D. (2019). Prediksi Kepuasan Mahasiswa terhadap Kinerja Dosen di Kota Batam menggunakan Algoritma C4 . 5. September, 235–240.
Rismayanti. (2018). Decision Tree Penentuan Masa Studi Mahasiswa Prodi Teknik Informatika ( Studi Kasus?: Fakultas Teknik dan Komputer Universitas Harapan Medan ). Query, 5341(April), 16–24.
Shiddiq, A., Niswatin, R. K., & Farida, I. N. (2018). Analisa Kepuasan Konsumen Menggunakan Klasifikasi Decision Tree Di Restoran Dapur Solo ( Cabang Kediri ). 2(1), 9–18.
Syahdan, S. Al, & Sindar, A. (2018). Data Mining Penjualan Produk Dengan Metode Apriori Pada Indomaret Galang Kota. Jurnal Nasional Komputasi Dan Teknologi Informasi (JNKTI), 1(2). https://doi.org/10.32672/jnkti.v1i2.771.
Yuli, M. (2017). Jurnal Edik Informatika Data Mining?: Klasifikasi Menggunakan Algoritma C4 . 5 Data mining merupakan bagian dari tahapan proses Knowledge Discovery in Database ( KDD ) . Jurnal Edik Informatika. Jurnal Edik Informatika, 2(2), 213–219.
Yuliana, A., & Pratomo, D. B. (2017). Memprediksi Kepuasan Mahasiswa Terhadap Kinerja Dosen Politeknik TEDC Bandung. 377–384.