Penggunaan Algoritma Support Vector Machine Untuk Penentuan Rekomendasi Penerima Beasiswa Di SMA Negeri 8 Kota Bogor

Scholarship is an assistance program in the form of educational funding in the form of beinggiven to assist students in obtaining proper education. SMA Negeri 8 Bogor City as aneducational unit that organizes formal education, participates in providing scholarships for itsstudents. The scholarship program at SMA Negeri 8 Bogor City has not used an effective andefficient method in determining the eligibility of students to receive scholarships so that errorsoften occur such as scholarships that are not on target. To overcome this, a website-basedscholarship prediction application was created to predict the eligibility status of students toreceive scholarships. Prediction is done using the classification method with the Support VectorMachine model. The results in the composition of 70% training data and 30% testing data get thehighest evaluation results with Accuracy 89%, Precision 91%, Recall 95%.

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Publication Details

Journal
IIKRA-ITH Informatika Jurnal Komputer dan Informatika
Published
2024-10-28
DOI
https://doi.org/10.37817/ikraith-informatika.v9i1.4381
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Penggunaan Algoritma Support Vector Machine Untuk Penentuan Rekomendasi Penerima Beasiswa Di SMA Negeri 8 Kota Bogor

Ionia Veritawati, Muhammad Rafly
IIKRA-ITH Informatika Jurnal Komputer dan Informatika
Data Mining and Machine Learning Applications
article

Penggunaan Algoritma Support Vector Machine Untuk Penentuan Rekomendasi Penerima Beasiswa Di SMA Negeri 8 Kota Bogor

Ionia Veritawati, Muhammad Rafly
article en

Abstract

Scholarship is an assistance program in the form of educational funding in the form of beinggiven to assist students in obtaining proper education. SMA Negeri 8 Bogor City as aneducational unit that organizes formal education, participates in providing scholarships for itsstudents. The scholarship program at SMA Negeri 8 Bogor City has not used an effective andefficient method in determining the eligibility of students to receive scholarships so that errorsoften occur such as scholarships that are not on target. To overcome this, a website-basedscholarship prediction application was created to predict the eligibility status of students toreceive scholarships. Prediction is done using the classification method with the Support VectorMachine model. The results in the composition of 70% training data and 30% testing data get thehighest evaluation results with Accuracy 89%, Precision 91%, Recall 95%.

IIKRA-ITH Informatika Jurnal Komputer dan InformatikaVol. 9(1)
Pancasila University (ID)
Openalex Percentile: Top 70%
Data Mining and Machine Learning Applications
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