Product Classification Based on Categories and Customer Interests on the Shopee Marketplace Using the Naïve Bayes Method

Muhammad Oase Ansharullah; Wirta Agustin; Lusiana; Junadhi; Susi Erlinda; Fransiskus Zoromi

doi:10.33372/jaia.v2i2.888

Muhammad Oase Ansharullah STMIK Amik Riau
Wirta Agustin STMIK Amik Riau
Lusiana STMIK Amik Riau
Junadhi STMIK Amik Riau
Susi Erlinda STMIK Amik Riau
Fransiskus Zoromi STMIK Amik Riau

DOI: https://doi.org/10.33372/jaia.v2i2.888

Keywords: Marketplace, classification, Naïve Bayes, Shopee, Weka

Abstract

Marketplace is an electronic product marketing platform that brings together many sellers and buyers to transact with each other. The large variety of products sold on Shopee is one of the reasons this application is in great demand by all walks of life. However, the weakness of the large variety of products sold in a marketplace causes buyers who have no potential to buy these products. To overcome this problem, it is necessary to do a classification to determine which products are most in demand by customers. Product categories consist of: Clothing, Beauty Products, Daily Goods, Electronics, and Accessories. The classification method used is Naïve Bayes and the software used is WEKA. The next data collection is done by distributing questionnaires to the existing customers on social media namely, Whatsapp and Instagram, the distribution of the questionnaire is conducted through Google form. There are 90 questionnaires that will be distributed in this study. Some of the indicators asked in the questionnaire namely, do you like shopping online? And what marketplaces are commonly used. These results will be the training data. Interest categories are divided into 4 categories, namely: Very interested, Interested, Not interested, Very not interested. The results obtained in this study are clothing products (72 respondents) are products that are in great demand, daily goods products (7 respondents) are products of interest, beauty and electronic products (5 respondents) are products that are not in demand, and accessories (1 respondents ) is a product that is not very attractive to customers on the Shopee marketplace

References

D.Apriadi, and A. Y. Saputra, "E-Commerce Berbasis Marketplace Dalam Upaya Mempersingkat Distribusi Penjualan Hasil Pertanian," Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi, pp. 1-8, 2017

E. R. Widyayanti, "Pengaruh Marketplace Terhadap Peningkatan Pendapatan Pada Ukm (Studi Pada Ukm Di Daerah Istimewa Yogyakarta," Jurnal Optimum, vol 9, 2019

S. Widaningsih and A. Suheri, "Klasifikasi Jurnal Ilmu Komputer Berdasarkan Pembagian Web Of Science Dengan Menggunakan Text Mining,"Jurnal SENTIKA, pp.320–328, 2018

Z. Zhang, "Naïve Bayes Classification In R. Annals Of Translational Medicine," Annals of Translational Medicine, vol 4, 2016

C. Fadlan, S. Ningsih and A. P. Windarto, "Penerapan Metode Naïve Bayes Dalam Klasifikasi Kelayakan Keluarga Penerima Beras Rastra,". Jurnal Teknik Informatika Musirawas, vol 3, 2018

R. N. Devita, H. W. Herwanto and A. P. Wibawa, "Perbandingan Kinerja Metode Naive Bayes dan K-Nearest Neighbor untuk Klasifikasi Artikel Berbahasa Indonesia," Jurnal Teknologi Informasi Dan Ilmu Komputer, vol. 5, no. 4, pp. 427, 2018

B.T. Pham, D. Tien Bui, H.R. Pourghasemi, P. Indra, M. B. D, "Landslide Susceptibility Assesssment In The Uttarakhand Area (India) Using GIS: A Comparison Study Of Prediction Capability Of Naïve Bayes, Multilayer Perceptron Neural Networks, And Functional Trees Methods," Springer, 2017

D. T. Bui, H. Shahabi, A. Shirzadi, K. Chapi, M. Alizadeh, W. Chen, A. Mohammadi, Ahmad, B. Bin, M. Panahi, H. Hong and Y. Tian, "Landslide Detection And Susceptibility Mapping By AIRSAR Data Using Support Vector Machine And Index Of Entropy Models In Cameron Highlands, Malaysia," Jurnal MDPI (Multidisiplin Digital Publishing Institute), vol. 10, no. 10, 2018

N. Dicky, E. Kamil and M. Ramadhan, "Penerapan Data Mining dengan Algoritma Naive Bayes Clasifier untuk Mengetahui Minat Beli Pelanggan terhadap Kartu Internet XL," Jurnal Ilmiah Saintikom, 2017

S. Nugroho, Adi and Y. A. Sari, "Implementasi Data Mining Menggunakan Weka," Malang, UB press, 2018

E. Syahputra, "Snowball Throwing Tingkatkan Minat dan Hasil Belajar" Sukabumi, Haura, 2020

N. I. Widiastuti, E. Rainarli and K. E. Dewi, "Peringkasan dan Support Vector Machine pada Klasifikasi Dokumen" Jurnal Infotel(Informasi Telekomunikasi dan Elektronika), vol. 9, no. 4, pp. 416-421, 2017

S. Yadav, and S. Shukla, "Analysis of k-Fold Cross-Validation over Hold-Out Validation on Colossal Datasets for Quality Classification". Semantic Scholar, vol. 6, 2016.