Selection of Education Assistance Recipients Based on AHP and SAW

Gatot Tri Pranoto · Dwi Pebrianti · Muhammad Darwis · Yaddarabullah Yaddarabullah · Erneza Dewi Krishnasari

8 citations0/0 files storedInternational Seminar on Intelligent Technology and Its Applications

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Decision Support System Applications Multi-Criteria Decision Making Edcuational Technology Systems

Abstract

The final decision of the educational assistance recipient in GNOTA Foundation, Jakarta is still processed manually. They usually only look at the father’s occupation criteria without looking at other criteria such as the age of the child, the child’s orphan status, the occupation of mother, the age of father, the age of mother and other scholarships received. GNOTA Foundation needs to implement a Decision Support System (DSS) for the selection process, so the results are fast and on target. This research applies the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods for the selection of education assistance recipients so the criteria can be weighted and the prospective recipient students can be ranked. This research determines the priority weight and importance of each criterion, namely the age of child age (0.18), the status of child (0.22), the occupation of father (0.08), the occupation of mother (0.06), the age of father (0.05), the age of mother (0.04) and other scholarship assistance (0.36). The results of the weighting of these criteria have been tested and declared consistent through the Consistency Ratio (CR) value of 0.070. This study also produces a list of the best ranking students who are prospective recipients of educational assistance. The ranking results have been tested based on compliance with the provisions of the GNOTA Foundation of 92.91%. The system in this study was developed using a prototyping system development model and utilizing the Unified Modeling Language (UML) tool. The prototype functionality in this study works well by using the Blackbox Testing (BBT) model based on Equivalence Partitioning. In addition, the level of user acceptance of the prototype in this study was 81.2% using the Technology Acceptance Method (TAM).

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References

1987The analytic hierarchy process—what it is and how it is used 2015Accuracy and Effort of Decision-Making Strategies With Incomplete Information: Implications for Decision Support System Design 2018Sistem Pendukung Keputusan Penerima Bantuan Siswa Miskin Menerapkan Metode WASPAS dan MOORA 2017METODE SIMPLE ADDITIVE WEIGHTING SEBAGAI SISTEM PENDUKUNG KEPUTUSAN PENERIMA BEASISWA MURID BERPRESTASI 2020Students’ Acceptance of Digital Learning Tools in Programming Education Course using Technology Acceptance Model 2017PENERAPAN SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN DANA BANTUAN OPERASIONAL SEKOLAH PADA SISWA SMA N 1 SIDOMULYO MENGGUNAKAN METODE TOPSIS BERBASIS WEB

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