Article Per Year (5 Year)
p-Index From 2021 - 2026
1.925
P-Index
This Author published in this journals
All Journal Jurnal Ortopedagogia Jurnal Penelitian Sains QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama Jurnal PG-PAUD Trunojoyo : Jurnal Pendidikan dan Pembelajaran Anak Usia Dini IJEBD (International Journal Of Entrepreneurship And Business Development) Community Development Journal: Jurnal Pengabdian Masyarakat Kreatif: Jurnal Pemikiran Pendidikan Agama Islam Inspirasi Ekonomi : Jurnal Ekonomi Manajemen Bulletin of Computer Science Research INTERNATIONAL JOURNAL OF EDUCATION, INFORMATION TECHNOLOGY, AND OTHERS Ezra Science Bulletin Jurnal Kewirausahaan dan Inovasi Asthadarma: Jurnal Pengabdian Kepada Masyarakat Jurnal Hukum dan Pembangunan Ekliptika: Jurnal Inovasi Teknologi Berkelanjutan
Agung Wijaya, Agung
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Bulletin of Computer Science Research

 1 
Penerapan Metode Fuzzy Sugeno Untuk Optimalisasi Persediaan Pakaian Wijaya, Agung; Putri, Raissa Amanda
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.770

Abstract

In the fashion retail industry, inventory management is a major challenge due to fluctuating and unpredictable customer demand. Errors in inventory planning may lead to overstocking or stockouts, increased storage costs, and decreased customer satisfaction. This study aims to develop a decision support system using the Sugeno fuzzy logic method to optimize clothing inventory. The input variables consist of initial stock, incoming goods, and outgoing goods, which are processed through fuzzification, inference, and defuzzification stages to produce the predicted final stock. Experimental results show that the Sugeno fuzzy model achieves better accuracy compared to conventional methods, with a Mean Absolute Percentage Error (MAPE) of 17.99%, equivalent to a prediction accuracy of 82.01%. The main contribution of this research lies in the application of the Sugeno fuzzy method to local fashion retail inventory management, which has generally been carried out manually. This approach enables the system to provide more precise stock recommendations, thereby helping stores reduce the risk of overstocking and stockouts, improve operational efficiency, and enhance business competitiveness.
Co-Authors Africano, Fernando Andi Candra Jaya, Andi Candra Anugrah, Muhammad Rizki Apandi, Khairul Ari Wahyudi Hertanto Armai Arief Daniar, Rima Effendy, Sahrul Fayadhilah, Muhammad Apta Febriana, Ida Islamia, Aulia KHOLIDAH, NURUL M. Sholeh Malindo, Tito Manggala, Agus Marlina, Seli Middya Boty, Middya Nana Meily Nurdiansyah Natasya Yunita Sugiastuti Oktaviani, Nadya Sisil Prasetyatama, Bintang Tegar Putra, Ghayana Aditya Putri Sartika Rahma, Aulya Raissa Amanda Putri Ramadhani, Fanny Ramadhani, Sigi Pegi Riandi, Muhammad Hafiz Riswanda, Jhon Rizki, Widya Selia Romadhan, Muhammad Fauzi Rony Wardhana Saiful Anam Saputra, Diego Setiawati, Anda Suryadi - Suryani, Hana Tomas Irianto, Tomas Yulia Tri Samiha