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All Journal ELSE (Elementary School Education Journal) : Jurnal Pendidikan dan Pembelajaran Sekolah Dasar JOURNAL OF APPLIED INFORMATICS AND COMPUTING JSiI (Jurnal Sistem Informasi) Journal of Information Systems and Informatics Neo Teknika: Jurnal Ilmiah Teknologi International Journal of Advances in Data and Information Systems MEANS (Media Informasi Analisa dan Sistem) Jurnal UNITEK Journal La Multiapp Jurnal Pengabdian Masyarakat (ABDIRA) Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Jurnal Mandiri IT Jurnal Locus Penelitian dan Pengabdian Jurnal Algoritma Jurnal Masyarakat Madani Indonesia Indonesian Journal of Community Empowerment (IJCE) "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Jurnal Informatika dan Kesehatan INOVTEK Polbeng - Seri Informatika Jurnal Ilmu Komputer
Sri Mujiyono
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Decision Support System for Inventory Prediction using Fuzzy Tsukamoto Method (Case Study: UMKM Bayou Indonesia) Galih Agil Febri Hidayatullah; Sri Mujiyono
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/sfyymk96

Abstract

Bayou Indonesia, an MSME engaged in acrylic product manufacturing, faces overproduction issues due to manual production planning, leading to stockpiling and wasted resources. This study aims to develop a decision support system using the Fuzzy Tsukamoto method to predict production quantities more accurately by analyzing historical data such as orders, shipments, and final stock. Data processing is performed with fuzzy logic to generate reliable production forecasts for the upcoming periods. The novelty of this research lies in the real-world integration of the Fuzzy Tsukamoto method within a CodeIgniter-based web application, which is directly implemented in the MSME environment, moving beyond the purely theoretical simulations of prior studies. The system significantly improves production planning accuracy, reducing manual errors (MAPE) from 21.5% to 8.7%, with an RMSE of 11.2 units. Furthermore, it helps decrease excess production discrepancies by up to 30% per month, raises prediction precision to 85%, and accelerates the decision-making process from two to three days to real-time. The resulting operational efficiency gains are estimated at 60–70%. These findings indicate that the system provides a practical solution for MSMEs to minimize overproduction risks, optimize resource usage, and enhance production planning through data-driven methods.
A DECISION SUPPORT SYSTEM FOR DETERMINING THE BEST EMPLOYEE PERFORMANCE EVALUATION USING THE ANALYTICAL HIERARCHY PROCESS (AHP) METHOD Polinus Gulo; Sri Mujiyono
Jurnal Sistem Informasi Vol. 13 No. 1 (2026)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/hsza5003

Abstract

Employee performance appraisal plays a critical role in organizational decision-making, particularly in determining promotions, bonuses, and competency development. Conventional manual evaluation methods are often subjective, inconsistent, and lack systematic validation. While prior studies have applied multi-criteria decision-making methods in decision support systems (DSS) for employee evaluation, a critical gap remains: most existing systems omit consistency testing, use incomplete weighting procedures, or lack end-to-end system implementation—undermining the reliability of their outputs. To address this gap, this study proposes a novel DSS that integrates a complete Analytical Hierarchy Process (AHP) procedure, including pairwise comparison, normalization, priority weight calculation, and consistency validation, within a fully operational web-based system developed using the SDLC Waterfall model at PT Sam Sam Jaya Garments. Data were collected through observation and interviews to define evaluation criteria and system requirements. The results reveal that Discipline holds the highest weight (0.4391), followed by Target Achievement (0.2661) and Honesty (0.1507), with a Consistency Ratio (CR) of 0.029, confirming reliable judgments. The system successfully ranked ten employees, identifying Cahya Annsyiah as the top performer with a final score of 0.39116. The key contribution of this study lies in its end-to-end integration of AHP with consistency validation into a deployable DSS, directly addressing the methodological shortcomings identified in previous research and enhancing objectivity, accuracy, and transparency in employee performance evaluation.   Keywords: Decision Support System, Analytical Hierarchy Process, Employee Performance Evaluation, AHP, SDLC Waterfall
Co-Authors Abdul Rohman Ade Pratama Afif Faisal Yasin Amalia, Alifah Anton Anton Aripin, Ahmad Nurul Dewanto, Bernadus Ela Suryani Fahrizal Alfian Dante fifi maqfiroh Galih Agil Febri Hidayatullah Galih Agil Febri Hidayatullah Hani Latifah Heni Setyowati Hesti Yunitiara Rizqi Ilham, Dimas Muhammad Ismiriyam, Fiktina Fivri Iwan Setiawan Wibisono Kartika Yuni Purwanti Khafid, Ahmad Noor Lisa Virdinarti Putra Mita Halimatus Sa'diah Muhamad Hasanudin Nafi, Tri Maula Novan Syaiful Nugroho, Aventura Suryo Nugroho, Ivan Pangestu, Andi Polinus Gulo Puput Amanda Rasyid Purnamasari, Yessy Sabilla Sanjaya, Ucta Pradema Suamanda Ika Novichasari Syarifudin, Nanang Irfan Wahyu Kristiningrum Widayati Widayati Yeni Fitri Afidah Zulmi Roestika Rini