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Klasifikasi Penjualan Provider Pulsa di Kecamatan Masbagik Lombok Timur Menggunakan Metode Naïve Bayes

DOI: https://doi.org/10.20956/ejsa.v4i2.27890
Article History

Submited : July 26, 2023
Published : August 4, 2023

Keywords:
The rapid development of technology causes the use of mobile phones and the need for pulses to increase. East Lombok is the area with the largest population in NTB and high users of information technology. East Lombok also has an internet network or smooth communication signal, which shows that there are many providers in the area. To see the types of providers that are widely used in Masbagik District, East Lombok, taking into account the largest population, a classification is made of whether these providers are in demand or not using the Naïve Bayes method. This study aims to determine the classification results and the accuracy of the sales classification of credit providers. The data is split into two categories: training data (90%) and testing data (10%). According to the findings of the study, 225 of the 309 testing data were correctly classified. The resulting APER value is 27.2%, which indicates that the accuracy of the classification results using the Naïve Bayes method is 72.8%. An AUC value of 0.804 was also obtained, which means that the accuracy of the classification of selling pulse providers that are in demand, moderately in demand, and not in demand was sufficient.

References

  1. Hamidin, D., Pranawukir, I., Mulyana, A., Susilawati, E., Ikhram, F., Novalia, N., Ruminda, M., Dawis, A.M., Kurniawan, R., & Pandriadi. Strategi Pemasaran Di Era Digital. Sukabumi: Haura Utama. 2022.
  2. Palupi, E.S. Prediction Of Android Handphone Sales During Pandemic Using Naïve Bayes and K-NN Methods Based On Particle Swarm Optimization. Jurnal Riset Informatika, 23-28. 2021.
  3. Arifin, T., & Ariesta, D. Prediksi Penyakit Ginjal Kronis Menggunakan Algoritma Naive Bayes Classifier Berbasis Particle Swarm Optimization. Jurnal Tekno Insetif , 26-30, 2019.
  4. Nawangsih, I., & Setyaningsih, A. Penerapan Algoritma Naïve Bayes Untuk Menentukan Klasifikasi Produk Terlaris Pada Penjualan Pulsa. Jurnal Teknologi Pelita Bangsa, 195-207, 2020.
  5. Devita, R.N., Herwanto, H.W., & Wibawa, A.P. Perbandingan Kinerja Metode Naive Bayes dan K-Nearest Neighbor Untuk Klasifikasi Artikel Berbahasa Indonesia. Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK), 427-434, 2018.
  6. Arhami, M., & Nasir, M. Data Mining Algoritma dan Implementasi. Ed.1. Yogyakarta: Andi. 2020.
  7. Prasetyowati, E. Data Mining: Pengelompokkan Data untuk Informasi dan Evaluasi. Pamekasan: Duta Media. 2017.
  8. Muflikhah, L., Ratnawati, D.E., & Putri, R.R.M. Data Mining. Malang: UB Press. 2018.
  9. Freund’s, J.E., & Walpole, R.E. Mathematical Statistics with Applications. 8th Edition. USA: Pearson Education Limited. 2014.
  10. Johnson, A.R., & Wichern, D. W. Applied Multivariate Statistical Analysis. Sixth Edition. Upper Saddle River: New Jersey. 2007.
  11. Gorunescu, F. Data Mining: Concepts, Models, and Techniques. Verlag Berlin Heidelberg: Springer. 2011.
  12. Arifin, S. Sales Management: Strategi Menjual dengan Pendekatan Personal. Yogyakarta: Salma Idea. 2020.
  13. Putri, M.P., Budiman, E., & Taruk, M. Analisis Kualitas Jaringan Seluler Terhadap Jasa Provider di Kota Samarinda. Jurnal Politeknik Negeri Balikpapan, 322-325, 2017.
  14. Priyantomo, B. Panduan Startup Server Pulsa: Panduan Untuk Anda Yang Ingin Berbisnis Server Pulsa. Malaysia: Mobile Outlet, 2016.
  15. Sugiyono. Metode Penelitian Pendidikan Pendekatan Kuantitatif, Kualitatif, dan R&D. Bandung: Alfabeta. 2012.

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