Implementasi Metode Simple Additive Weighting Dan Multi Attributive Border Approximation Area Comparison Pada Sistem Pendukung Keputusan Penerima Beasiswa Anak Tempatan
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Institusion
Politeknik Negeri Bengkalis
Author
Misriana, Sari
Subject
458 Teknik Informatika
Datestamp
2024-08-21 13:36:22
Abstract :
The Bengkalis Regency Education Office (Disdik) provides Local Children's Scholarships to students in an effort to help students to alleviate the dependents of the Single Tuition Fee (UKT) in pursuing education. In determining the recipients of the Local Children's Scholarship, the Education Office government carries out several stages manually such as holding deliberations. A website-based decision support system for local scholarship recipients is needed to help determine local scholarship recipients more quickly and accurately. This system is made using SAW and MABAC methods to facilitate the calculation and comparison of the value of each alternative in the system, by determining the ranking based on the largest value as the best alternative. The result of the application of the SAW and MABAC methods in the system is that the system displays alternative data sequentially based on rankings that can help in determining the recipient of the Tempatan Children Scholarship. From 60 field data, the application of SAW and MABAC on this system has an accuracy of 83.3%. The development method used is the Extreme Programming method.
The Bengkalis Regency Education Office (Disdik) provides Local Children's Scholarships to students in an effort to help students to alleviate the dependents of the Single Tuition Fee (UKT) in pursuing education. In determining the recipients of the Local Children's Scholarship, the Education Office government carries out several stages manually such as holding deliberations. A website-based decision support system for local scholarship recipients is needed to help determine local scholarship recipients more quickly and accurately. This system is made using SAW and MABAC methods to facilitate the calculation and comparison of the value of each alternative in the system, by determining the ranking based on the largest value as the best alternative. The result of the application of the SAW and MABAC methods in the system is that the system displays alternative data sequentially based on rankings that can help in determining the recipient of the Tempatan Children Scholarship. From 60 field data, the application of SAW and MABAC on this system has an accuracy of 83.3%. The development method used is the Extreme Programming method.
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