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p-Index From 2021 - 2026
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All Journal International Journal of Management Science and Information Technology (IJMSIT)
Dewi Eka Yanti, Ni Putu
Unknown Affiliation
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Decision Support System for Asset Management using the Simple Additive Weighting Method Yeni Dwi Rahayu, Ni Made; Dewi Eka Yanti, Ni Putu
International Journal of Management Science and Information Technology Vol. 5 No. 2 (2025): July - December 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v5i2.5072

Abstract

Effective and efficient asset management is a crucial aspect in supporting the operational sustainability of an organization. However, the decision-making process in determining whether an asset should be retained, repaired, or replaced is often conducted subjectively and lacks structure. This study aims to develop a Decision Support System for asset management using the Simple Additive Weighting method to assist in evaluating assets objectively based on multiple criteria. The developed system includes features such as a master data menu, alternative data input, SAW-based calculation processes, and a recommendation result display. System testing results showed that the values for accuracy, precision, recall, and specificity were each 80%, with 4 True Positive, 4 True Negative, 1 False Positive, and 1 False Negative. Based on these results, the system is considered valid and suitable for use as a decision-making tool in structured and measurable asset management processes. This level of accuracy also reflects the system's ability to accurately identify and classify data under both positive and negative conditions. Therefore, it can be concluded that this decision support system has a good level of reliability and is suitable for use as a supporting tool in asset management decision-making.
Decision Support System for Asset Management using the Simple Additive Weighting Method Yeni Dwi Rahayu, Ni Made; Dewi Eka Yanti, Ni Putu
International Journal of Management Science and Information Technology Vol. 5 No. 2 (2025): July - December 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v5i2.5072

Abstract

Effective and efficient asset management is a crucial aspect in supporting the operational sustainability of an organization. However, the decision-making process in determining whether an asset should be retained, repaired, or replaced is often conducted subjectively and lacks structure. This study aims to develop a Decision Support System for asset management using the Simple Additive Weighting method to assist in evaluating assets objectively based on multiple criteria. The developed system includes features such as a master data menu, alternative data input, SAW-based calculation processes, and a recommendation result display. System testing results showed that the values for accuracy, precision, recall, and specificity were each 80%, with 4 True Positive, 4 True Negative, 1 False Positive, and 1 False Negative. Based on these results, the system is considered valid and suitable for use as a decision-making tool in structured and measurable asset management processes. This level of accuracy also reflects the system's ability to accurately identify and classify data under both positive and negative conditions. Therefore, it can be concluded that this decision support system has a good level of reliability and is suitable for use as a supporting tool in asset management decision-making.
Comparative Analysis of SAW and WP Methods for Employee Selection in MSMEs Yeni Dwi Rahayu, Ni Made; Dewi Eka Yanti, Ni Putu
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.6511

Abstract

The process of selecting new employees in Micro, Small, and Medium Enterprises (MSMEs) is often still carried out subjectively, which can lead to less optimal decision-making. This study aims to apply and compare the Simple Additive Weighting (SAW) and Weighted Product (WP) methods as decision support systems for new employee selection in MSMEs. The evaluation is conducted based on four criteria: education level, work experience, skill competency, and interview results. The dataset consists of ten job candidates that are processed through weight normalization, preference value calculation, and ranking stages. The results show that both methods are capable of providing objective and measurable recommendations for selecting the best employees, although differences appear in the final ranking of candidates because the SAW method calculates scores by summing weighted normalized values for each criterion, while the WP method multiplies each criterion value raised to its weight, making the influence of high or low scores more pronounced. The SAW method is simpler and easier to understand, while the WP method is more sensitive to criterion weights and better distinguishes candidates with varied performance levels. The best alternative tends to consistently rank at the top in both methods. Therefore, the implementation of the SAW and WP methods can assist MSMEs in making systematic and accurate employee selection decisions based on a dataset of ten candidates evaluated across four assessment criteria.
Co-Authors Yeni Dwi Rahayu, Ni Made