Bulletin of Informatics and Data Science
Vol 4, No 2 (2025): November 2025

Weighted Multi-Criteria Assessment of Rice Quality Using The TOPSIS Method

Satria, Budy (Unknown)
Fadilah, Sandi (Unknown)



Article Info

Publish Date
29 Nov 2025

Abstract

Rice is a staple food for the Indonesian people, and its availability must be guaranteed by the government. The background of this research is based on the increasing demand for high-quality rice from consumers, thus challenging producers to set optimal rice quality standards. The process of selecting quality rice is still carried out using conventional methods in Bulog warehouses, namely by checking every rice data received by the quality control team tasked with assessing the quality of incoming rice. To overcome this problem, a decision support system is needed that can provide fair, objective, and efficient decisions. This study aims to evaluate the quality of rice from 10 alternatives using five criteria: milling degree, head grain, moisture content, broken grain, and grit grain, with a total weight of 100%. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is applied. This research was conducted by following a series of steps, including building a Decision Matrix, Normalizing the Decision Matrix, Calculating the Weighted Normalized Decision Matrix, Determining the Ideal Positive and Negative Solutions, Calculating the Distance to the Ideal Positive and Negative Solutions, and Calculating the Preference Score. The results of the study showed that from 10 alternative data, 5 types of rice were obtained with the highest preference values, namely Harum Solok Rice (0.8363), Anak Daro Rice (0.7955), Kuruik Kusuik Rice (0.7210), Ampek Angkek Rice (0.6919), and Saganggam Panuah Rice (0.6727). The conclusion of this study is that the application of the TOPSIS method is effective in objectively assessing rice quality. In further research, it is recommended to utilize a combination of other decision support methods to acquire new knowledge and refine preference values, as well as to develop these methods into user-friendly interfaces

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Journal Info

Abbrev

bids

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering Engineering

Description

The Bulletin of Informatics and Data Science journal discusses studies in the fields of Informatics, DSS, AI, and ES, as a forum for expressing research results both conceptually and technically related to Data ...