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Applying Data Mining to Classify Customer Satisfaction using C4.5 Algorithm Decision Tree
https://doi.org/10.22146/ijccs.83535 J. Prayoga(1), Zelvi Gustiana(2), Sabrina Aulia Rahmah(3*)
(1) Department of System Information, Universitas Dharmawangsa, Medan
(2) Department of Technology Information, Universitas Dharmawangsa, Medan
(3) Department of Technology Information, Universitas Dharmawangsa, Medan
(*) Corresponding Author
Abstract
Tight business competition demands business actors to make responsive, timely decisions to survive the uncertainty. Food business, especially cafes, has emerged as one of the most popular business types recently. One cafe concept that draws most customers' interest is modern concepts, friendly service, and affordable prices. Finn Coffee is one of the cafes providing a range of foods and beverages, especially coffee-based beverages. Customer satisfaction defines one's feelings when comparing performance. It denotes customer's responses to their satisfied needs. The term satisfaction itself is described as one's happy expression after receiving a quality product with affordable price and satisfying quality. The present study aimed to analyze cafe customer satisfaction using the C4.5 algorithm with predetermined criteria. Customer satisfaction was classified using C4.5. The algorithm displays the level of customer satisfaction based on the customers' response to the Google form distributed by the cafe employees/owner.
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[1] S. Takalapeta, “Penerapan Data Mining Untuk Menganalisis Kepuasan Konsumen Menggunakan Metode Algoritma C4.5,” J I M P - J. Inform. Merdeka Pasuruan, vol. 3, no. 3, pp. 34–38, 2018, doi: 10.37438/jimp.v3i3.186.
[2] Z. Gustiana, W. Satria, and J. Simon, “Penerapan Algoritma C 4.5 Pada Pengaruh Iklan Online Terhadap Minat Beli Konsumen di Masa Pandemic Covid-19,” J. SAINTIKOM (Jurnal Sains Manaj. Inform. dan Komputer), vol. 20, no. 2, p. 91, 2021, doi: 10.53513/jis.v20i2.3751.
[3] D. Yunita and I. H. Ikasari, “Perbandingan Metode Klasifikasi C4.5 dan Naïve Bayes untuk Mengukur Kepuasan Pelanggan,” vol. 6, no. 3, pp. 2622–4615, 2021, [Online]. Available: http://openjournal.unpam.ac.id/index.php/informatika456.
[4] F. Mubarok, S. Susanti, A. R. Sanjaya, A. R. Sanjaya, D. Tree, and D. Mining, “Cerbon Menggunakan Klasifikasi Decision,” Anal. Penjualan Terhadap Caffe Warung Cerbon Menggunakan Klasifikasi Decis. Tree, vol. 2, no. 1, pp. 130–134, 2021.
[5] Y. Indah, “Prediksi Tingkat Kepuasan Pelayanan Online Menggunakan Metode Algoritma C4.5,” J. Inform. Ekon. Bisnis, vol. 3, pp. 59–64, 2022, doi: 10.37034/infeb.v4i2.99.
[6] H. Dhika and F. Destiawati, “Penerapan Algoritma C45 Untuk Penilaian Karyawan Pada Restoran Cepat Saji,” no. September, pp. 55–59, 2018.
[7] Y. Indah Lestari and S. Defit, “Prediksi Tingkat Kepuasan Pelayanan Online Menggunakan Metode Algoritma C.45,” vol. 3, pp. 148–154, 2021, doi: 10.37034/infeb.v3i3.104.
[8] H. Hendri and D. Oscar, “Penerapan Algoritma C4.5 Dalam Mengukur Kepuasan Pengunjung Terhadap Fasilitas Di Taman Margasatwa Jakarta,” J. Infortech, vol. 3, no. 1, pp. 73–78, 2021, doi: 10.31294/infortech.v3i1.10504.
[9] A. K. Lalo, P. Batarius, and Y. C. H. Siki, “Implementasi Algoritma C4.5 Untuk Klasifikasi Penjualan Barang di Swalayan Dutalia,” J. Tek. Inform. UNIKA St. Thomas, no. March 2022, pp. 1–12, 2021, doi: 10.54367/jtiust.v6i1.1089.
[10] I. Ubaedi and Y. M. Djaksana, “Optimasi Algoritma C4.5 Menggunakan Metode Forward Selection Dan Stratified Sampling Untuk Prediksi Kelayakan Kredit,” JSiI (Jurnal Sist. Informasi), vol. 9, no. 1, pp. 17–26, 2022, doi: 10.30656/jsii.v9i1.3505.
[11] F. Ali Ma, A. Pratama, I. Sholihin, and A. Rizki Rinaldi, “Penerapan Model Prediksi Menggunakan Algoritma C.45 Untuk Prediksi Kelulusan Siswa SMK Wahidin,” vol. 1, no. 1, pp. 16–20, 2021.
[12] A. C. Adha, Y. Yuhandri, and G. W. Nurcahyo, “Prediksi Potensi Relawan Pendonor Darah Menjadi Pendonor Darah Tetap dengan Penerapan Metode Klasifikasi Decision Tree,” J. Inf. dan Teknol., vol. 3, pp. 233–238, 2021, doi: 10.37034/jidt.v3i4.158.
[13] L. N. Rani, “Klasifikasi Nasabah Menggunakan Algoritma C4.5 Sebagai Dasar Pemberian Kredit,” INOVTEK Polbeng - Seri Inform., vol. 1, no. 2, p. 126, 2016, doi: 10.35314/isi.v1i2.131.
[14] R. A. Syahfitri, A. P. Windarto, and H. Okprana, “Klasifikasi Calon Nasabah Baru Menggunakan C.45 Sebagai Dasar Pemberian Pertanggungan Asuransi di PT Asuransi Central Asia Pematangsiantar,” Bull. Data Sci. (Media Online), vol. 1, no. 1, pp. 40–48, 2021.
[15] N. Karolina, “Data Mining Pengelompokan Pasien Rawat Inap Peserta BPJS Menggunakan Metode Clustering ( Studi Kasus : RSU . Bangkatan ),” pp. 47–53, 2021.
[16] M. R. Matondang, M. R. Lubis, and H. S. Tambunan, “Analisis Data mining dengan Metode C.45 pada Klasifikasi Kenaikan Rata-Rata Volume Perikanan Tangkap,” Brahmana J. Penerapan Kecerdasan Buatan, vol. 2, no. 2, pp. 74–81, 2021, doi: 10.30645/brahmana.v2i2.68.
[17] P. Nuraini, J. Tata Hardinata, Y. Pranayama Purba Program Studi Sistem Informasi, S. A. Tunas Bangsa Jalan Jendral Sudirman Blok, and S. Utara, “RESOLUSI : Rekayasa Teknik Informatika dan Informasi Penerapan Algoritma C4.5 Untuk Klasifikasi Pola Kepuasan Pelayanan E-Ktp Di Kantor Camat Pematang Bandar,” Media Online), vol. 3, no. 2, pp. 138–144, 2022, [Online]. Available: https://djournals.com/resolusi.
[18] W. R. Sari Oktapia Ningse, S. Sumarno, and Z. M. Nasution, “C4.5 Algorithm Classification for Determining Smart Indonesia Program Recipients at MIS Al-Khoirot,” JOMLAI J. Mach. Learn. Artif. Intell., vol. 1, no. 1, pp. 65–76, 2022, doi: 10.55123/jomlai.v1i1.165.
[19] W. R. Fadillah et al., “Implementasi Data Mining C4.5 Dalam Mengukur Tingkat Kepuasan Mahasiswa Terhadap Kinerja Asisten Laboratorium Komputer,” Pros. Semin. Nas. Ris. Dan Inf. Sci., vol. 2, pp. 403–414, 2020.
[20] S. Haryati, A. Sudarsono, and E. Suryana, “Implementasi Data Mining Untuk Memprediksi Masa Studi Mahasiswa Menggunakan Algoritma C4.5 (Studi Kasus: Universitas Dehasen Bengkulu),” J. Media Infotama, vol. 11, no. 2, pp. 130–138, 2015.
DOI: https://doi.org/10.22146/ijccs.83535
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