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All Journal Dharmakarya : Jurnal Aplikasi Ipteks Untuk Masyarakat JOISIE (Journal Of Information Systems And Informatics Engineering) Jurnal Teknologi Dan Sistem Informasi Bisnis Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Pengabdian kepada Masyarakat Nusantara Majalah Ilmiah UPI YPTK Journal of Computer Scine and Information Technology Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Jurnal Ekonomika Dan Bisnis Jurnal Komtekinfo Sistem Pendukung Keputusan dengan Aplikasi Jurnal Pengabdian Masyarakat Dharma Andalas SATIN - Sains dan Teknologi Informasi The Indonesian Journal of Computer Science
Febri Hadi
Universitas Putra Indonesia YPTK Padang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Public Health Social Sciences Other

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Journal : Jurnal Ekonomika Dan Bisnis

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Analisis Pengelompokkan Pelanggan Menggunakan Algoritma K-Means diana, yusvi; Hadi, Febri; Hadi, Meswantri
Jurnal Ekonomika Dan Bisnis (JEBS) Vol. 5 No. 1 (2025): Januari - Februari
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jebs.v5i1.2485

Abstract

The development of technology today has a great influence in various fields. One of the fields that requires information technology data processing is the business field. Information technology data processing is very necessary to analyze data in the business world. Data analysis is needed to understand customers and group customers. One of the data analysis methods used for customer grouping is the K-Means algorithm. This method also helps companies analyze customer loyalty in sales transactions. The purpose of the study is to group customers as an analysis of a business. Data grouping in this study is grouped into 2, namely loyal and less loyal customers. The data in this study is 20 data samples taken from sales transaction data. The results of this study produce information about loyal customers and less loyal customers so that from this information the company can make decisions to improve relationships with customers in making sales transactions
Peningkatan Literasi Produk dalam Pembelian Handphone melalui Sistem Rekomendasi Berbasis Algoritma C4.5 Diana, Yusvi; Hadi, Febri; Rahman, Sepsa Nur; Yenila, Firna
Jurnal Ekonomika Dan Bisnis (JEBS) Vol. 5 No. 4 (2025): Juli-Agustus
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jebs.v5i4.3224

Abstract

Low levels of product literacy among consumers often cause a mismatch between the specifications of the purchased mobile phone and their actual needs. This problem is common, especially in stores that provide a wide selection of products with technical information that is poorly understood by prospective buyers. Lack of understanding of features such as processor type, camera quality, RAM capacity, and internal memory makes the purchasing process less than optimal. This study aims to improve consumer literacy by developing a mobile phone purchase recommendation system based on the C4.5 algorithm. The method used is a data mining approach with stages of collecting historical consumer purchase data, preprocessing data to eliminate noise, labeling purchase decisions, forming a decision tree model using the C4.5 algorithm, and evaluating model performance using a confusion matrix. The dataset used includes 19 types of mobile phones from a local store with attributes such as processor, main camera, front camera, RAM, internal memory, and price. The method used in this study uses the C4.5 algorithm. The results of the study show that the C4.5 algorithm is able to classify data with satisfactory accuracy and produce a relevant recommendation system. In addition to providing product suggestions, this system also includes a logical explanation of each decision taken, thereby increasing consumer understanding. Thus, this system not only helps the decision-making process, but also acts as an educational medium in increasing consumer literacy regarding mobile phone product specifications that suit their needs and budget.
Co-Authors , Shary Armonitha Lusinia Ariandi, Vicky Aulia Fitrul Hadi Defra Irawan Devia Kartika Dheatri Agrema Dodi Guswandi Eliza Eliza Febri Aldi Gushelmi Hadi Syahputra hadi syahputra Hadi, Meswantri Halifia Hendri Harma, Wahri Heri yanto irawan, Defra Irzal Arief Wisky Mayola , Liga Meswantri, Meswantri Meta, Monanda Rio Muhammad Afdhal Musli Yanto Musli Yanto Nadya Alinda Rahmi Paisal, Hena Utami Putri Pohan, Nurmaliana Pradani Ayu Widya Purnama Prayogi Wicaksana Rahman, Sepsa Nur Randy Permana Rima Liana Gema Rizky Rianda Sarjon Defit Satria Yulanda Shary Armonitha Lusinia Sumijan Syafri Arlis Syafrika Deni Rizki Vicky Ariandi Vicky Ariandi Wulan Ayu Safitri yanto, heri Yenila, Firna Yogi Wiyandra Yuhandri Yuhandri, Yuhandri Yusvi Diana Zefriyenni Zefriyenni, Zefriyenni