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All Journal JURNAL ILMIAH INFORMATIKA Jurnal Riset Informatika Infotech: Journal of Technology Information
Pusparini, Nur Nawaningtyas
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Computer Science & IT

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PREDIKSI MAHASISWA INSTITUT SOSIAL DAN TEKNOLOGI WIDURI JAKARTA BERPOTENSI DROP OUT MENGGUNAKAN ALGORITMA NAÏVE BAYES Sultan, Sultan; Pusparini, Nur Nawaningtyas; Kharisma, Nanda; Samuel, Samuel
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10310

Abstract

Universities are responsible for producing quality graduates and reducing dropout rates (DO), a serious challenge for the Widuri Institute of Social and Technology (ISTEK). This phenomenon has a negative impact on the quality of education and accreditation, making early identification of students who have the potential to drop out (DO) very crucial. This study aims to apply the Naïve Bayes algorithm to predict the potential for dropout (DO) of ISTEK Widuri students based on data on the activities of the 2021, 2022, and 2023 intakes. Naïve Bayes has proven effective in classifying students at risk of dropping out (DO). The Semester Credit Unit (SKS) attribute is the most dominant indicator, students with low SKS have a high potential for dropping out (DO). Model performance varies for each batch, in the 2021 batch it reached 90% accuracy (100% DO precision, 40% recall), the 2022 batch showed 93.75% accuracy (100% DO precision, 60% DO recall), and the 2023 batch had 86.67% accuracy (100% DO precision, 33.33% DO recall). This model is very good at validating students who are safe from DO (100% recall of Not DO in all batches). Even so, the model still needs to be improved so that it can find all students who are at risk of dropping out (DO) as a whole. The prediction results for students with the potential for DO at ISTEK Widuri Jakarta are expected to support more optimal prevention efforts and contribute to improving the quality of education.
Decision Support System for Outstanding Students’ Selection Using TOPSIS Suryani, Irma; Sani, Asrul; Budiyantara, Agus; Pusparini, Nur Nawaningtyas
Jurnal Riset Informatika Vol. 6 No. 2 (2024): March 2024
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v6i2.285

Abstract

In the school environment, determining outstanding students holds significant importance. High academic achievement among students and a low failure rate reflect the overall quality of education. Based on the interviews, it is known that the assessment process for outstanding students at school still needs to be revised, and the current decision-making system needs to consider other factors, resulting in suboptimal selection processes. To address this issue, implementing a Decision Support System (DSS) is necessary to assist the school in selecting the best students. DSS is an interactive system providing access to data and modelling information, designed to support decision-making in both structured and unstructured situations. This DSS will be designed using the Technique for Order of Preferences by Similarity to an Ideal Solution (TOPSIS) as the alternative ranking method. The final results indicate that using the TOPSIS method in this decision support system can improve efficiency and accuracy in selecting outstanding students in the school environment.
Co-Authors AA Sudharmawan, AA Addarda, Binan Asrul Sani Asrul Sani Bagaskara, Wisnu Budiyantara, Agus Irma Suryani Irwansyah Irwansyah Khalifah, Ummi Kharisma, Nanda Kusmawan, Oki Samuel Samuel Shosa, Andi Siti Aisyah Sofyan, Mochamad Sultan Sultan Supit, Merliani Ivone Surono, Galih Tanto Wijaya, Tanto Wibawa, Agusta Pratama