Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA
Simanullang, Rahma Yuni
Unknown Affiliation
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Sistem Pendukung Keputusan Penerima Bantuan Covid-19 Menggunakan Metode Simple Additive Weighting (SAW) Simanullang, Rahma Yuni; Melisa, Melisa; Mesran, Mesran
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to determine the acceptance of covid19 assistance. The COVID 19 pandemic is devastating, resulting in a lot of unemployment. The poverty rate is increasing, and there are also cases of rampant mortality, the mobility of the community itself and security insecurity. With that, the government plans to provide special assistance for people who cannot afford to face the COVID 19 pandemic. The distribution of social assistance as a realization of the social safety net program during the COVID 19 pandemic has worried many homeworkers, starting from reduced income, setting targets to distribution. However, the mechanism for distributing aid often becomes very complicated, or the nominal amount decreases and there is often an inaccurate point of view because the criteria for beneficiaries do not match the data that is inaccurate / does not match the reality in the field, resulting in misunderstandings between the community. In essence, the Simple Additive Weighting (SAW) method is often known as the weighted method. The basic concept of the Simple Additive Weighthing (SAW) method is to find the weighted sum of the performance branches for each alternative on all criteria. The Simple Additive Weighting (SAW) method requires a decision matrix normalization process. So the author uses the Simple Additive Weighting method or it is often said with the term SAW. To solve this problem, namely by using one of the methods to obtain a multiple and complete assessment of criteria with a conferential thinking framework to carry out hierarchical considerations, then calculate the weight of each criterion to determine the priority recommendations for receiving COVID 19 assistance according to the data. On the results of this study.
Implementation of Apriori Algorithms to Analyze and Determine Consumer Purchase Patterns in Gadget Stores as Sales Increase Strategy Simanullang, Rahma Yuni; ', Khairunnisa; Wanny, Puspita; Utari, Utari; Novelan, Muhammad Syahputra
Journal of Computer System and Informatics (JoSYC) Vol 6 No 3 (2025): May 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i3.7355

Abstract

This study aims to identify the pattern of product purchases that often occur simultaneously at a gadget store in order to develop a more effective sales strategy. The research problem focuses on how to find associations between products based on sales transaction data. The proposed solution is to apply data mining techniques, specifically a priori algorithms, to analyze transaction data and find significant association rules. The A priori algorithm is used through several stages, including the calculation of support for each item, the elimination of items with support below the minimum threshold, the formation of itemset combinations, and the calculation of confidence to generate association rules. The results showed two association rules that met the minimum confidence threshold (60%), namely: (1) If customers buy USB-C, they tend to buy Powerbank (confidence: 67%), and (2) If customers buy Smartwatches, they tend to buy Screen Protectors (confidence: 67%), and (3) If customers buy Screen Protectors, they tend to buy Smartwatches (confidence: 100%). These patterns can be used by the store for strategic product placement and bundling promotions.
Co-Authors ', Khairunnisa Mesran, Mesran Muhammad Syahputra Novelan Nasution, Annio Indah Lestari Utari Utari Wanny, Puspita