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Irwansyah Suwahyu
Universitas Negeri Makassar
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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.
Co-Authors Abd. Rahman Patta Abdal, Nurul Mukhlisa Ainun Zahra Adistia Amiruddin Hambali Amri Rahman Anam, Muh. Yusril Andi Ahmad Taufiq Andi Baso Kaswar Andi Baso Kaswar Andi Dio Nurul Awalia Andi Faiz Nabiel Rasyid Andi Muhammad Taufik Ali Angga Adit Pratama Anisa M, Nurul Annajmi Rauf Aqsha, Ismail Ari Andrian Waratman Arifin Bando, Ushwa Dwi Masrurah Ashadi, Nini Rahayu Ashadi, Ninik Rahayu Asham Bin Jamaluddin Ashari, Hilda Aslinda, Ummu Asriati Asriati, Asriati Ayudia Ria Sofiana Ayudia Ria Sofiana Bando, Arifin Daud Mahande, Ridwan Dedi Faizal Suwahyu Dedi Faizal Suwahyu Dewi, Shabrina Syntha Dyah Vitalocca Edy, Marwan Ramdhany Hanum Zalsabilah Idham Hisnuddin, Hisnuddin Ikrananda Imran Indah Amaliah Ismail Rosyid Ismail Rosyid Jamaluddin Jamaluddin M. Al Ihlas M. Miftach Fakhri Mahmudi, Akhsan Marzuki, Kartini Masni Masni Masrurah, Ushwa Dwi Ma’ruf , Muhammad Miftahul Huda Miru, Alimuddin Sa'ban Muh. Agung Sidiq Muh. Reyhansyah Syahrir Muh. Yusril Anam Muhammad Asriadi Muhammad Fajar B Muhammad Fikri Aqil Muhammad Haristo Rahman Muhammad Ma’ruf Muhtar Muhtar Mukhlisah Abdal, Nurul Muliaty Yantahin Muttaqia Muttaqia Nasrah Natsir Ninik Rahayu Ashadi Nur Syafitra Ramadhani Nurfadilah Istiqamah Nurhilaliyah Nurhilaliyah Nurhilaliyah, Nurhilaliyah Nurmila Nurmila Nurrahmah Agusnaya Nurrahmah Agusnaya Nurul Fajriani Rasid Nurul Mukhlisah Abdal Nurul Mukhlisah Abdal Pramudya Asoka Syukur Putri Maharani, Geby Putri Nirmala Putri Nirmala Ramli Rasjid, A. Riana T. Mangesa Ricky Saputra Rosidah Rosidah Rosidah Sanatang Setialaksana, Wirawan - Shabrina Syntha Dewi Sidik Sidin, Udin Sitti Muthmainnah Sitti Muthmainnah Sofyan Taurid Ode Madi suhaeb, Sutarsi Suhartono, Suhartono Sulaiman, Dwi Rezky Anandari Syahrul Syukur, Pramudya Asoka Udin Sidik Sidin Ushwa Dwi Masrurah Arifin Bando Veronika Asri Tandirerung Wahyudi Gani, Andika Wardani, Ayu Tri Yasin Anil Hakim Gobel Yohana Rara Yuanita B Zahra Humairah H. S. Pongkapadang