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All Journal J I M P - Jurnal Informatika Merdeka Pasuruan JURNAL TEKNOLOGI DAN OPEN SOURCE Infotek : Jurnal Informatika dan Teknologi
Sulistyo Dwi Sancoko
Universitas Teknologi Yogyakarta
Computer Science & IT Control & Systems Engineering Engineering

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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
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 7, No 1 (2022): MARET
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v7i1.404

Abstract

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
Penerapan Sistem Point Of Sale Berbasis Android Untuk Peningkatan Kinerja Usaha Handhira Bayu Pradhana Putra; Sulistyo Dwi Sancoko
Infotek: Jurnal Informatika dan Teknologi Vol. 7 No. 1 (2024): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v7i1.23934

Abstract

Micro, Small and Medium Enterprises in Presidential Decree No. 99 of 1988 are small-scale people's economic activities with business fields that are mostly small business activities. However, in MSMEs, there are several types of obstacles including data collection of stock of goods, transaction reports and financial statements that are not effective and efficient. Therefore, researchers want to change the way store management uses modern methods by designing a point of sale system as an android-based platform for MSMEs Established Stores. Point of Sales systems help various retail businesses make buying and selling transactions quickly, safely, and systematically. POS also includes modern cash registers commonly used in some stores or businesses. The design of this system uses technology from Firebase, namely the Realtime Database feature. The result of this study is an android-based point of sale application. Point of sale applications can simplify the management process at Established Stores. This can be seen from the system testing with the blackbox method which gets good results and all functions run well
Recommendations for Selection of Skincare Products Using the Promethee Method Muhammad Aufa Zaydan Azfar; Sulistyo Dwi Sancoko
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v7i2.3816

Abstract

This research aims to implement the Promethee method (Preference Ranking Organization Method for Enrichment Evaluation) in recommending appropriate skincare products based on facial skin type. With so many skincare products on the market, consumers may have difficulty choosing the right product. The Promethee method helps make multi-criteria decisions by considering various relevant factors such as skin type, price, user ratings, product quality, and price suitability based on the preferences of people who have used skincare products before as a reference in recommending skincare products. Recommendations are made based on data from the preferences of students who have used skincare products and provide an assessment of the products they have used. Researchers used the Promethee method as research to see how effective its use is in providing skincare product recommendations. The data used as a basis for manual calculations uses 10 data points for normal skin types. With the highest net flow value for normal skin types of 3.44444444 for Wardah Lightning and Ponds Men products. The highest net flow value for combination skin type is 24.250000, net flow for oily skin type is 14.222222, net flow for sensitive skin type is 14.722222, and net flow for dry skin type is 8.166667. The research results show that the Promethee method can provide appropriate recommendations regarding the selection of skincare products based on facial skin type.
Co-Authors Dadang Heksaputra Fadil Indra Sanjaya Handhira Bayu Pradhana Putra Muhammad Aufa Zaydan Azfar Muhammad Fachrie Nuzula Afini Zahra Septa Hati