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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Applied Information System and Management
Shadiq, Jafar
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Computer Science & IT Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media

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Web-Based Decision Support System for Selecting Exemplary Teachers using TOPSIS Method Sumardiono, Sumardiono; Ismail, Norhafizah; Shadiq, Jafar; Nida, Zahra Qotrun; Solikin, Solikin; Suryani, Riska
Applied Information System and Management (AISM) Vol 8, No 1 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i1.45488

Abstract

This study creates an online Decision Support System (DSS) using the TOPSIS algorithm to fairly choose outstanding teachers from vocational schools in Bekasi City, which has 87 state and private vocational secondary schools with about 62,000 students. To tackle the current biased selection process, our research uses a multi-criteria approach that looks at discipline (25%), travel costs (20%), personality (20%), teaching administration (15%), and learning achievements (20%). Targeting this substantial educational population, our research addresses the current subjective selection process by implementing a multi-criteria approach evaluating discipline (25%), travel costs (20%), personality (20%), teaching administration (15%), and learning achievements (20%). The TOPSIS method was selected for its proven effectiveness in ranking alternatives based on geometric distance from ideal solutions, particularly valuable in large-scale educational contexts. Analysis of 14 teacher candidates from SMK Bina Karya Mandiri demonstrated the system's precision, with Didi Saputra, S.Pdi, emerging as top-ranked (preference value: 0.63). When extrapolated to Bekasi's 87 SMKs, the model shows potential to standardize teacher assessment citywide, reducing regional disparities in recognition practices. The web-based platform enhances accessibility, allowing principals across 21 sub-districts to input localized data while maintaining centralized benchmarking. Key findings reveal (1) discipline and personality collectively account for 45% of exemplary status determination, (2) cost-related factors show inverse correlation with remote school nominations, and (3) system implementation could reduce selection time by ≈68% compared to manual methods. This study contributes both a scalable framework for educational DSS and empirical data on vocational teacher excellence criteria in urban Indonesia.
Data-Driven Insights for Higher Education Marketing: Segmenting Applicant Pools Using K-Means Clustering Shadiq, Jafar; Wicaksono, Harjunadi; Budiarto, Rahmat; Salamah, Raisha Nur; Fakhrudin, Zidan Al Buqhori
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.11545

Abstract

This research aims to optimize marketing strategies for new student recruitment at Bina Insani University (BiU), which faces intense competition. The current marketing efforts are generic and inefficient. Utilizing the CRISP-DM framework, this study applies the K-Means clustering data mining method to analyze primary data from applicants from 2021 to 2024. The analysis focuses on the attributes of previous school major, information source, and location. The findings successfully identified four distinct segments of prospective students: the "Proactive Outreach Segment," reached through school presentations; the "Social Network & Affiliation Segment," influenced by friends and relatives; the "Academic Recommendation Segment," who rely on guidance from teachers; and the "Digital & Non-Technical Segment," who actively seek information on social media. Based on the unique profile of each cluster, this study provides recommendations for specific and targeted marketing strategies to improve the effectiveness and efficiency of student recruitment
Web-Based Decision Support System for Selecting Exemplary Teachers usingTOPSIS Method Sumardiono, Sumardiono; Ismail, Norhafizah; Shadiq, Jafar; Nida, Zahra Qotrun; Solikin, Solikin; Suryani, Riska
Applied Information System and Management (AISM) Vol. 8 No. 1 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i1.45488

Abstract

This study creates an online Decision Support System (DSS) using the TOPSIS algorithm to fairly choose outstanding teachers from vocational schools in Bekasi City, which has 87 state and private vocational secondary schools with about 62,000 students. To tackle the current biased selection process, our research uses a multi-criteria approach that looks at discipline (25%), travel costs (20%), personality (20%), teaching administration (15%), and learning achievements (20%). Targeting this substantial educational population, our research addresses the current subjective selection process by implementing a multi-criteria approach evaluating discipline (25%), travel costs (20%), personality (20%), teaching administration (15%), and learning achievements (20%). The TOPSIS method was selected for its proven effectiveness in ranking alternatives based on geometric distance from ideal solutions, particularly valuable in large-scale educational contexts. Analysis of 14 teacher candidates from SMK Bina Karya Mandiri demonstrated the system's precision, with Didi Saputra, S.Pdi, emerging as top-ranked (preference value: 0.63). When extrapolated to Bekasi's 87 SMKs, the model shows potential to standardize teacher assessment citywide, reducing regional disparities in recognition practices. The web-based platform enhances accessibility, allowing principals across 21 sub-districts to input localized data while maintaining centralized benchmarking. Key findings reveal (1) discipline and personality collectively account for 45% of exemplary status determination, (2) cost-related factors show inverse correlation with remote school nominations, and (3) system implementation could reduce selection time by ≈68% compared to manual methods. This study contributes both a scalable framework for educational DSS and empirical data on vocational teacher excellence criteria in urban Indonesia.
Co-Authors Fakhrudin, Zidan Al Buqhori Harjunadi Wicaksono, Harjunadi Ismail, Norhafizah Nida, Zahra Qotrun Rahmat Budiarto Salamah, Raisha Nur Solikin Solikin Sumardiono Sumardiono, Sumardiono Suryani, Riska