Dhea Zulis Syafitri
Universitas Islam Negeri Imam Bonjol Padang

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Penerapan Metode Topsis untuk Menentukan Menu Terfavorit Mie Gacoan Lubuk Buaya Padang Berdasarkan Data ShopeeFood Dhea Zulis Syafitri; Yaslinda Lizar
Jurnal SAINTEKOM (Sains dan Teknologi Komputasi) Vol 2 No 3 (2026): September 2026
Publisher : Lembaga Penelitian, Pengembangan, dan Pengabdian Kepada Masyarakat (LP3M) – Universitas Binaniaga Indonesia (UNBIN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jskom.v2i3.121

Abstract

Digital transformation in the culinary industry has encouraged the utilization of online transaction data as foundation for business decision-making. One of the challenges faced by culinary businesses is determining the most favored menu objectively based on multiple evaluation criteria. This study aimed to implement the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to identify the favorite menu at Mie Gacoan Lubuk Buaya Padang using ShopeeFood data. The study employed three primary criteria, namely the number of sales, price, and costumer preferences. The weighting process was conducted using the Rank Order Centroid  (ROC) method to obtain proportional importance values for each criterion. The research data consisted of five menu alternatives: Mie Hompipa Level 1, Mie Gacoan Level 1, Udang Rambutan. Udang Keju, dan Es Gobak Sodor. The calculation stages included constructing the decision matrix, normalizing the matrix, generating the weighted normalized matrix, determining positives and negative ideal solutions, calculating preference distances, and evaluating the relative closeness value of each alternative.  The results indicated that Udang Keju achieved the highest preference value of 0.933 and was therefore identified as the most favored menu based on the TOPSIS calculation. The findings demonstrate that the TOPSIS method is capable of providing systematic, measurable, and effective decision recommendations in multi-criteria menu evaluation processes.