Sistem Pendukung Keputusan Untuk Mengukur Permintaan Produk Pada e-Commerce dengan Fuzzy Inference System: (Studi Kasus Orebae.com) - Fadil Indra Sanjaya; Dadang Heksaputra; Muhammad Fachrie; Sulistyo Dwi Sancoko; Nuzula Afini; Zahra Septa Hati (Fakultas Teknologi Informasi Universitas Merdeka Pasuruan, 2022)
Measuring product demand is an important process for e-commerce companies to assess product viability in the future production. Measuring product demand can assist e-commerce companies to produce and developing new products based on market potential. Decision maker usually only using their best seller product as indicator to estimate future market trend. But in the fact future market trend will not only based on best seller product, but also there several criteria which is needs attention too. In order to use several criteria to estimate market trend, need some analysis so it will take a long time. With Decision Support System (DSS), decision making will be easier and faster. In this research the DSS takes into consideration the following input variables: Total Sales (TS), Rating (R), Viewed (V), Total Comments (TC) and output Product Demand (PD). Once the Fuzzy Inference System model has been developed, an assessment of the variables is made through testing 1-years data, which allows verifying how the variables behave in the system under study, and their impact on the output variables. Through the application of Fuzzy Inference System in DSS regarding the modeling several criteria that impact product demand, it is possible to increased efficiency and maximizing profitKeyword— DSS, Fuzzy Inference System, Tsukamoto, e-Commerce, Product Demand