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Fuzzy TOPSIS for Post-Harvest Losses Drivers Evaluation in Fish Supply Chain: A Case Study Muhammad Faisal Ibrahim; Taufik Kurrahman; Prita Meilanitasari
Jurnal Teknik Industri Vol. 24 No. 2 (2023): August
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol24.No2.127-140

Abstract

Being highly susceptible to damage, fish result in significant post-harvest fish losses (PHFL) due to quality deterioration from inefficient harvesting and market dynamics. This study aims to identify the leading factors driving PHFL and construct a practical decision-making framework for the fisheries industry's development. Employing the fuzzy TOPSIS method, we scrutinized the critical causes of PHFL. Our literature review revealed four aspects and 13 operational processes contributing to PHFL across the supply chain. Among these processes, four drivers were the primary culprits: excessive fish capacity in shipping baskets, inadequate ice cooling during transportation to suppliers, insufficient ice cooling during supplier sorting, and the absence of appropriate tools for small retailers. To alleviate PHFL and enhance the fishery industry, priority should be given to addressing excessive fish capacity in shipping baskets, which poses a risk of physical damage during transit. Moreover, inadequate ice-cooling techniques, particularly in transportation and supplier sorting stages, raise public health and food safety concerns. Stakeholders must prioritize these critical factors for PHFL reduction.
Development of Integrated Warehouse Application for Retail Business with Multi-Echelon Demand using Open-source ERP System Prita Meilanitasari; Muhammad Faisal Ibrahim
Jurnal Sistem Informasi Vol. 19 No. 2 (2023): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jsi.v19i2.1294

Abstract

The Integrated Warehouse Application (IWA) is a platform that combines inventory management, order management, warehouse operations, shipping, logistics, and reporting and analysis. It helps users manage their inventory to meet supply and demand requirements. Although many large companies use IWA to increase their operational efficiency, its complexity, technology, and customization requirements make it too expensive for small and medium-sized enterprises (SMEs). Our study focuses on SMEs in the retail business, where fast and accurate order processing is important for customer satisfaction and loyalty. We researched how to accommodate multi-echelon demand for the retail industry. To address these challenges, we used an Open-source ERP System called Odoo to create the IWA. Our findings show that implementing an integrated warehouse inventory system like the one provided by Odoo can offer real-time visibility into inventory levels, orders, and shipments. Automating manual processes enhances speed and accuracy, which improves customer service and business performance.