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All Journal JURTEKSI Bulletin of Information Technology (BIT)
Sri Wahyuni, Meri
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Computer Science & IT

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ANALYSIS OF PSI METHOD IN DECISION SUPPORT SYSTEM TO SELECT THE FEASIBILITY OF COVID 19 PATIENT DATA SCANNER RESULTS Zulkarnain, Iskandar; Sri Wahyuni, Meri; Sonata, Fifin
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 4 (2025): September 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i4.4081

Abstract

Abstract: Hospitals play an important role in examining the scan results of patient data infected with the Covid 19 virus. However, there are problems when processing the scan results, namely that sometimes errors occur in the scan data, causing many failures and delays in sending data to the Health Office. The purpose of this study is to build a Desktop-based decision support system application that can facilitate hospitals in selecting the eligibility of the scan results of Covid 19 patient data. The urgency in examining the scan results of Corona patient data is a very pressing public health issue, because the long-term impact is very significant for patients. Thus, a scientific discipline is needed that can support the decision-making process, namely the Decision Support System using the Preference Selection Index (PSI) method. PSI is a simple and easy calculation method, based on statistical concepts without having to determine attribute weights. The results of this method are clear and firm values ​​​​based on the level of strength of the rules applied. The results of the research conducted on the PSI process can be concluded that valid Covid 19 patient data is Recap File I with a value of 0.2042 which is declared valid and accepted. Keywords: covid-19; decision support system; PSI
Analysis Of Item-Based Collaborative Filtering For Sales Of Processed Oil Palm Products Sitorus, Zulham; Sri Wahyuni, Meri; Rika Uli Samosir, Siska
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2195

Abstract

Abstract- The sales system for processed palm oil necessitates a recommendation system that offers product suggestions to users, facilitating their selection of sales items for processed palm oil products. This study used the Item-Based Collaborative Filtering approach, which identifies the similarity between items. The system will assess the rating of each item and compute the similarity value utilising the Pearson correlation-based similarity formula. Companies will exhibit greater interest in product sales that possess identical similarity values. This article presents recommendations for system development concerning processed products intended for the sale of technology-based items that employ item-based collaborative filtering methods. It specifies a recommended selling value for processed palm oil products, with a Mean Absolute Error (MAE) of 10.463126965591, derived from the equation 5/1, yielding a final result of -5. The execution of the sales suggestions for processed palm oil products indicates that the items with the highest similarity value calculations are i4 and i5. PT. Sugih Riesta Jaya employs the Item-Based collaborative filtering method to enhance sales of refined palm oil products, thereby facilitating sales assistance and providing the public with sales information and recommendations for essential refined palm oil products..
Co-Authors Muhammad Luthfi Rika Uli Samosir, Siska Sitorus, Zulham Sonata, Fifin -