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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) INFOKUM Bulletin of Computer Science Research BEES: Bulletin of Electrical and Electronics Engineering Jurnal ABDIMAS Budi Darma Jurnal Pengabdian Mandiri Jurnal Sains dan Teknologi Informasi ORAHUA : Jurnal Pengabdian Kepada Masyarakat
Lince Tomoria Sianturi
Universitas Budi Darma, Medan
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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Journal : The IJICS (International Journal of Informatics and Computer Science)

 1 
Implementation of Weight Sum Model(WSM) in the Selection of Football Athletes Lince Tomoria Sianturi
The IJICS (International Journal of Informatics and Computer Science) Vol 3, No 1 (2019): March 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (237.988 KB) | DOI: 10.30865/ijics.v3i1.1358

Abstract

Every soccer team has a standard that is used by coaches in determining athletes that fit the criteria owned by athletes. In this study, researchers used a decision support system (SPK) with the Weight Sum Model (WSM) method, which assesses the results of the criteria needed in the selection of soccer athletes. Decisions made in applying the WSM method will produce recommendations according to the standards used by the trainer. The purpose of this research is to apply the WSM method in selecting soccer athletes based on the desired category. The existence of this system is expected to make selection more objective for trainers in making decisions
Decision Support System for Accepting Pre-Employment Cards during the Covid-19 Pandemic Using the Method Multi Objective Optimization on The Basic of Ratio Analysis (MOORA) Chandra Frenki Sianturi; Lince Tomoria Sianturi; Uswatun Hasanah; Khairunnisa Khairunnisa; Mesran Mesran
The IJICS (International Journal of Informatics and Computer Science) Vol 5, No 2 (2021): July 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v5i2.3218

Abstract

During the Covid-19 pandemic there were many impacts on the community such as social, educational and financial problems, therefore the government as the highest authority in society made a policy for the Pre-Work Card program as a solution to one of the problems, especially in the economic sector that was felt by the community, such as overcoming the problem of unemployment, layoffs, and poverty. With the help of the Decision Support System, it is hoped that they will be able to make the best decisions for prospective Pre-Employment Card recipients. This study aims to determine the best alternative that fits the criteria according to the requirements of the Pre-Work Card by using the MOORA (Multi Objective Optimization On The Basic Of Ratio Analysis) method
Analysis of Food Menu Purchasing Patterns in Campus Canteens Using the Apriori Algorithm in Data Mining Sianturi, Lince Tomoria; Murdani, Murdani; Fadlina, Fadlina
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 2 (2025): July
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i2.8919

Abstract

This study aims to identify purchasing patterns of food menus in the campus cafeteria of STMIK Mulia Darma by applying the Apriori algorithm within the data mining framework. The background of this research is based on the increasing volume of transaction data that remains underutilized in supporting managerial decision-making. The Apriori algorithm is employed to uncover associations between items frequently purchased together by calculating their support and confidence values. A dataset of 20 daily digital transactions was used as the basis for analysis. The results revealed a single valid association rule that met the minimum threshold: Nasi Goreng,Teh Manis with a support value of 15% and a confidence value of 60%. This finding indicates a strong tendency in student consumption behavior, which can be leveraged for marketing strategies such as menu bundling and predictive inventory management. The study demonstrates that the Apriori algorithm can offer practical and strategic insights in the context of a campus cafeteria and holds potential for further development using larger datasets and more advanced analytical methods.
Co-Authors Abdul Karim Bakti, Surya Bella Nabila Candra Frenki Sianturi Chandra Frenki Sianturi Fadlina Fince Tinus Waruwu Fitri Afriani Lubis Ginting, Permanan Ginting, Permanan Guidio Leonarde Ginting Handayani, Wenny Henry Kristian. Siburian Hery Sunandar Hotmian Gultom Ikwan Lubis Janisah Janisah Khairunnisa Khairunnisa Matias Julyus Sirait Mesran, Mesran Muhammad Syahrizal Muhammad Zainuddin Murdani Murdani Murdani Murdani, Murdani Nasution, Zuhria Ndruru, Eferoni Nelly Astuti Hasibuan Oktafrida Saragih Pristiwanto Pristiwanto Putri Kirana Ramayana Pasaribu Rivalri Kristianto Hondro Rizka Pratiwi Ronda Deli Sianturi Sianipar, Sri Handayani Sianturi, Hotman Jandri Vay Siburian, Henry Kristian Sirait, Matias Julyus Siregar, Agnes Siregar, Agnes Soeb Aripin Sri Handayani Sianipar Suginam Suhastra Indrawan Tegar Sabatia Tarigan Uswatun Hasanah Wenny Handayani