Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

1.286

P-Index

This Author published in this journals

All Journal Faktor Exacta Jurnal Riset Informatika Jurnal Lemhannas RI Inspiration: Jurnal Teknologi Informasi dan Komunikasi Jurnal Aruna Mengabdi (ARMI) InaBHS (Indonesian Journal of Biomedicine and Health Science)

nanang ruhyana

Unknown Affiliation

Author-ID : 3805160

Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Public Health Social Sciences Other

Published : 7 Documents Claim Missing Document

Claim Missing Document

Articles

Title

Approaches to Customer Types Classification Method in the Supermarket Nanang Ruhyana; Mardiana, Tati
Jurnal Riset Informatika Vol. 6 No. 1 (2023): December 2023
Publisher : Kresnamedia Publisher

The development of the retail industry in the economy is very rapid so it provides good economic growth, one of the retailers is supermarkets, in supermarkets consumers can buy goods directly, so consumers must be served well. The problem is how supermarkets can continue to increase their sales results, because there is a lot of competition from supermarket competitors, so the marketing team when creating events or promotions must be right on target so that loyalty for member or non-member customers can be measured, which will be used as the right marketing strategy and can increase customer satisfaction when the customer is satisfied with the services, products and promotional activities at the supermarket, the customer will continue to make purchases and will increase the results of achieving good sales. Based on this problem, how will this research apply the classification method, so that when we can make predictions from supermarket sales data for member and non-member customers, there will be a lot of insight for the marketing team, so that marketing activities are right on target for member or non-member customers. This research uses machine learning methods for data classification, using the Support Vector Machine (SVM) and Naïve Bayes algorithms. The results of this research are from the Support Vector Machine (SVM) algorithm. Accuracy is 0.493 while using the Naïve Bayes algorithm is 0.535. From the results of this research, the use of the Naïve Bayes algorithm is better than SVM so that it can approach the prediction of member and non-member customer classification in supermarket data in this research.

Implementation of the FP-Growth Algorithm on Spare Parts Supply Requests Amsury, Fachri; Nanang Ruhyana; Riyadi, Andri Agung; Bayhaqy, Achmad
Jurnal Riset Informatika Vol. 6 No. 3 (2024): June 2024
Publisher : Kresnamedia Publisher

Manufacturing companies rely on machines for operational activities to produce finished goods. Common factors constraining the demand and supply of spare parts are the high number of spare parts managed and irregular patterns of demand for spare parts. These varying quantities also require investment in spare parts inventory and longer response times than predicted. The research aims to apply the FP-Growth algorithm approach to find association rules and produce patterns of demand and supply of spare parts in lightweight brick manufacturing companies based on transaction data on demand and supply of spare parts from January – March 2023. The approach used is associated with the applied algorithm. In this research, the primary process of the FP-Growth algorithm is to create a combination of each item until no more combinations are formed using minimum support and minimum confidence parameters. Based on the results of making association rules using spare parts demand data from the machine maintenance department, it is stated that the regulations formed from processing the RapidMiner application with a confidence value of 100% recommend FD Regular Bolt spare parts, then the next rating with a confidence value of 94% is Steel Nuts, seven rules recommend Nuts. Steel. Therefore, it is recommended that FD Regular Bolts and Steel Nuts carry out safety stock to maintain stock availability and place them on shelves included in the fast-moving inventory category.

Co-Authors Ardhian Yudha Candra Pranowo Asrul Bayhaqy, Achmad Didi Rosiyadi Fachri Amsury Ida Ayu Putu Sri Widnyani Ika Kurniawati Riyadi, Andri Agung Rizki Fahdia, Muhammad Saputra, Irwansyah Siti Helmyati Tati Mardiana, Tati Thysa Thysmelia Affandi

Title Search

Found 2 Documents Search Journal : Jurnal Riset Informatika

Abstract

Abstract

Title

Found 2 Documents
Search
Journal : Jurnal Riset Informatika