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All Journal Jurnal Pendidikan Terapan Journal of Embedded Systems, Security and Intelligent Systems Artificial Intelligence in Educational Decision Sciences
Muhammad Fikri Aqil
Universitas Negeri Makassar
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Social Sciences Other

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Clustering Multi-Indicator Learning Outcomes of Vocational High School Students: A Comparison of K-Means and DBSCAN Muhammad Fikri Aqil; Irwansyah Suwahyu
Artificial Intelligence in Educational Decision Sciences Vol 1 No 2 (2026): Artificial Intelligence in Educational Decision Sciences
Publisher : PT. Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/aieds.v1i2.24

Abstract

Purpose – This study aims to compare the performance of K-Means and DBSCAN algorithms in clustering vocational high school students’ learning outcomes in the Network Administration subject to support data-driven educational decision making.Methods – A quantitative experimental approach was employed using secondary academic data from vocational students. The variables analyzed included final examination scores, midterm examination scores, assignments, attendance, attitudes, and learning activities. Clustering was conducted using K-Means and DBSCAN algorithms implemented through data analysis software. Cluster quality and separation were evaluated using silhouette coefficients to assess the effectiveness of each algorithm in grouping student learning outcomes.Findings – The results show that K-Means produces relatively stable and interpretable clusters when student performance data exhibit more uniform distributions. In contrast, DBSCAN demonstrates stronger capability in handling noisy data and identifying students with extreme performance levels as outliers. Both algorithms successfully reveal meaningful patterns in student learning outcomes, but differ in their sensitivity to data distribution and noise.Research limitations – This study is limited to a single vocational subject and one institutional context, which may restrict the generalizability of the findings to other vocational domains.Originality – This study provides empirical evidence on the comparative performance of partition-based and density-based clustering algorithms using multi-indicator learning outcome data in vocational education.
Analisis Penerimaan MOOCs Dengan Model UTAUT Yang Telah Dimodifikasi Andika Isma; Sitti Hajerah Hasyim; Muhammad Fikri Aqil; Ananta Tri Mahardika; Dimas Prayoga
Jurnal Pendidikan Terapan Vol 2, No 2 May (2024)
Publisher : Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/jupiter.v2i2.208

Abstract

Dalam konteks pendidikan, akses dan keterlibatan menjadi kendala signifikan. Solusi yang muncul adalah Massive Open Online Courses (MOOCs), platform kursus daring terbuka yang menawarkan akses gratis dan fleksibilitas melalui teknologi informasi dan komunikasi (TIK). Penelitian ini bertujuan untuk menyelidiki penerimaan MOOCs, berfokus pada model UTAUT yang dimodifikasi, serta memahami sikap dan persepsi pengguna terhadap MOOCs dalam konteks pendidikan. Dengan menggunakan desain penelitian cross-sectional, data dikumpulkan melalui penggunaan kuesioner. Hasil analisis statistik deskriptif menunjukkan preferensi pengguna terhadap pendekatan pembelajaran yang ditawarkan oleh MOOCs daripada fokus pada kemudahan teknis penggunaannya. Mayoritas responden cenderung melihat MOOCs sebagai alat efektif dalam pendidikan. Studi ini menyoroti kecenderungan positif terhadap penggunaan MOOCs dalam meningkatkan hasil akademis. Tujuan utama penelitian ini adalah untuk menyelidiki penerimaan dan persepsi pengguna terhadap MOOCs dalam konteks pendidikan, serta untuk memahami preferensi pengguna terhadap model pembelajaran yang ditawarkan oleh MOOCs.
Improving Literacy Through Technology: An Agile Approach in the Development of the Redify Digital Reading Platform Muhammad Fikri Aqil; Rosidah; Muh Galang Nusantara; Siti Fatimah Azzahra Namar; Rafiqah Ameliah Kasim; Elma Nurjannah
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 2 (2024): July 2024
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v5i2.5312

Abstract

In the digital age, reading has evolved from a traditional physical book to a more dynamic and technology-integrated activity through e-books and other digital platforms. However, this progress also presents new challenges, such as a significant decline in reading interest in Indonesia, especially among the younger generation. Redify, an innovation in the digital reading ecosystem, addresses this challenge by offering a more engaging reading experience and incorporating a strong community approach. This article explores how Redify leverages the latest technologies and agile development methods to quickly adapt its features to meet readers' needs and preferences. By encouraging social interaction and discussion among readers, Redify aims to revive reading habits and improve the overall reading experience. The study also assesses the feasibility and effectiveness of Redify's strategy in overcoming the decline in reading interest among the younger generation in Indonesia.
Co-Authors Ananta Tri Mahardika Andika Isma Dimas Prayoga Elma Nurjannah Irwansyah Suwahyu Muh Galang Nusantara Rafiqah Ameliah Kasim Rosidah Rosidah Siti Fatimah Azzahra Namar Sitti Hajerah Hasyim