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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
Mugiarso Mugiarso
Universitas Bhayangkara Jakarta Raya
Computer Science & IT Decision Sciences, Operations Research & Management

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The Weighted Product Method and the Multi-Objective Optimization on the Basis of Ratio Analysis Method for Determining the Best Customer Mugiarso Mugiarso; Rasim Rasim
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol 11 No 1 (2023): March 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i1.6325

Abstract

The objective of this study is to compare the effectiveness of the Weighted Product (WP) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) methods in determining the best customers. Onesnet, the case study service provider, provides discounts and rewards to eligible customers to support this objective. The problem addressed in this study is how to determine the most relevant method for selecting eligible customers for bonuses. To achieve this, sensitivity testing was conducted by altering the weights of each criterion in both methods and observing the percentage changes of the results. The Weighted Product method multiplies the rating of each connected attribute, which is raised to the appropriate attribute weight, to decide. Data for this study was collected through interviews and observations at Onesnet and processed using the Rank Order Centroid (ROC) method for weighting, and the WP and MOORA methods for evaluating and selecting a decision. The WP and MOORA methods produced different total values and rankings, but the modeling with either method can be used equally for selecting the best customers. While there was a 60% similarity in data between the two methods, the WP method is recommended over MOORA, as it prioritizes customers with high loyalty criteria as the best customers.
The Weighted Product Method and the Multi-Objective Optimization on the Basis of Ratio Analysis Method for Determining the Best Customer Mugiarso Mugiarso; Rasim Rasim
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 11 No. 1 (2023): March 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i1.6325

Abstract

The objective of this study is to compare the effectiveness of the Weighted Product (WP) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) methods in determining the best customers. Onesnet, the case study service provider, provides discounts and rewards to eligible customers to support this objective. The problem addressed in this study is how to determine the most relevant method for selecting eligible customers for bonuses. To achieve this, sensitivity testing was conducted by altering the weights of each criterion in both methods and observing the percentage changes of the results. The Weighted Product method multiplies the rating of each connected attribute, which is raised to the appropriate attribute weight, to decide. Data for this study was collected through interviews and observations at Onesnet and processed using the Rank Order Centroid (ROC) method for weighting, and the WP and MOORA methods for evaluating and selecting a decision. The WP and MOORA methods produced different total values and rankings, but the modeling with either method can be used equally for selecting the best customers. While there was a 60% similarity in data between the two methods, the WP method is recommended over MOORA, as it prioritizes customers with high loyalty criteria as the best customers.
A Comparative Analysis of Sequential Search Algorithm Implementation within the Sales Information Systems of Wira Thrift Store and Rizky Snack Store Mugiarso Mugiarso; Marcellino Hutagalung; Miftahur Rizky; Rakhmat Purnomo; Dwipa Handayani; Rasim Rasim
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 14 No. 1 (2026): March 2026
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v14i1.12244

Abstract

This study evaluates the implementation of the Sequential Search algorithm to address manual data management challenges within Indonesian MSMEs, specifically regarding stock tracking inefficiencies. The search system was deployed across two distinct entities: Toko Wira Thrift (apparel sector) and Toko Rizky Snack (food sector) using PHP and MySQL. Blackbox testing was conducted through 14 scenarios covering both positive and negative conditions. The results demonstrate that the algorithm successfully enhanced real-time product search speeds for customers and optimized inventory management to prevent stock expiration, achieving a 100% functional success rate. The testing confirms the system's functionality, asserting that Sequential Search is an effective and flexible solution for improving operational efficiency across various MSME sectors.
Co-Authors Dwipa Handayani Marcellino Hutagalung Miftahur Rizky Rakhmat Purnomo Rasim Rasim Rasim Rasim Sugiyatno Sugiyatno