DECISION SUPPORT SYSTEM USING WEIGHTED PRODUCT METHOD IN CHIPS MATERIAL SELECTION (CASE STUDY: HASTI FAMILY CHIPS BUSINESS)

Luqman Nul Hakim
Safwandi
Risawandi

Multidiciplinary Output Research for Actual and International Issue (Morfai Journal)
Vol. 4 No. 4 (2024): Multidiciplinary Output Research For Actual and International Issue

This study designs a decision support system to help the owner of the Hasti Family chips business choose the optimal raw materials in making cassava, banana, and breadfruit chips. The Weighted Product (WP) method is used as a multi-criteria decision-making method by considering criteria such as chip color, chip texture, chip taste, chip durability and fruit price. Criteria data and alternative raw materials are processed using WP calculations to produce the best alternative ranking. The result is a web-based decision support system that implements the WP method, presents an interface for entering data and displays the best alternative ranking. This system improves the efficiency of decision-making, minimizes the risk of selecting inappropriate raw materials, improves product quality, and supports business growth. The results of the research on the decision support system for selecting chips ingredients show that this system determines the best ingredients by finding the final value of the V vector search from 3 cassava data, 3 banana data and 3 breadfruit data that will be entered into the system and get results from butter cassava, which has the highest V value of 0.38311467, followed by wak banana with an impressive V value of 0.398763354, and Bali breadfruit, which has a prominent V value of 0.350015233. The conclusion of this study is that the designed application is able to optimize the process of selecting raw materials for chip production more efficiently, quickly, and this system not only accelerates decision making but also ensures more structured and reliable data recording.