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All Journal KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) J-Icon : Jurnal Komputer dan Informatika
Yulison H Chrisnanto
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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SEGMENTASI PELANGGAN BERDASARKAN PRODUK MENGGUNAKAN METODE K- MEDOIDS Putri Eka Prakasawati; Yulison H Chrisnanto; Asep Id Hadiana
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 3, No 1 (2019): Smart Device, Mobile Computing, and Big Data Analysis
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v3i1.1610

Abstract

Market segmentation is a division of consumer groups that have different needs, characteristics and behaviors (heterogeneous) in a particular market so that it becomes a homogeneous market unit, in this case it is very helpful in a more targeted marketing process so that company resources can be used effectively and efficient for example makes it easy to distinguish markets and recognize competitors with the same segment. CV. Lampegan Jaya is a company engaged in the distribution of food and beverage products including Meses Tulip Chocolate, Vita Zone, Bintang Sobo Tea, Preso Tea, Okky Jelly Drink, Fruit Tea, Bima Energy Nails, Coptic Cappuccino, Mizon and My Tea. These products are distributed to outlets spread across Bandung, Cianjur, Cileunyi, Cimahi, Soreang and Sumedang. Distribution of products is carried out based on the demand for outlets for the product. In this study a system of classifying customer segmentation based on products. This system can classify customers based on the number of purchases and area. The process of this customer grouping system uses a K-Medoid clustring algorithm to classify customers based on segmentation on the product purchase amount and area. With test data of 6 regions, 600 customer data and 28 products. Keywords: Market Segmentation, k-Medoids, , Food Products
KLASIFIKASI KALIMAT PADA BERITA OLAHRAGA SECARA OTOMATIS MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK Asep Saepul Ridwan; Yulison H Chrisnanto; Ridwan Ilyas
J-Icon : Jurnal Komputer dan Informatika Vol 9 No 1 (2021): Maret 2021
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v9i1.3708

Abstract

Sports news is of great interest to today's society. This is because sports have grown into entertainment. There is a lot of sports news today that covers a wide range of sports, from branches that use the ball as objects for games like football, to sports in automotive race like formula 1. Beyond that, the substance of the sports news itself is as diverse as the news of managerial from a sports club, results matches, player injuries, et cetera. Surely such a thing would be difficult. The network wants one in the field of discussion in the news. Overlap data occurs in the sports news document because it mixes one sentence data with the other. Some of the content in the sports news is about managerial, players, schedules, previews, reviews, standings, statistics, champions, etc. Becomes a problem when the reader wants a topic on the news that focuses on one particular discussion. This study has built a book on sentence classification meaning Artificial Neural Network (ANN) with a method of learning Backpropagation. The feature used is the frequency of the occurrence of a term in the corresponding sentence and the calculating result of a distributed term. The testing of our proposed methods shows an accuracy of 99% to best results on training data and 57% on test data.
Co-Authors Asep Saepul Ridwan Hadiana, Asep Id Putri Eka Prakasawati Ridwan Ilyas