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All Journal Jurnal Teknologi Pendidikan Jusikom: Jurnal Sistem Informasi Ilmu Komputer Majalah Ilmiah Kaputama REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer MEANS (Media Informasi Analisa dan Sistem) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Media Informatika JURNAL TEKNOLOGI INFORMASI & KOMUNIKASI DALAM PENDIDIKAN Innovative: Journal Of Social Science Research Jurnal Sistem Informasi dan Teknologi Jaringan Jurnal Pengabdian Masyarakat (Jubdimas)
Hasugian, Penda Sudarto
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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DETEKSI EMOSI SISWA SMKS METHODIST 8 BERBASIS AI UNTUK MEMBANTU DALAM PEMBELAJARAN Panggabean, Erwin; Simanjorang, R. Mahdalena; Apriani, Wira; Sitohang, Amran; Hasugian, Penda Sudarto; Harefa, Jikarni; Arikhifo, Arikhifo
JUBDIMAS ( Jurnal Pengabdian Masyarakat) Vol 4 No 1 (2025): Jurnal Pengabdian Masyarakat, Maret 2025
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jubdimas.v4i1.383

Abstract

The research conducted through community service aims to develop artificial intelligence (AI)-based software capable of detecting students' emotions at SMKS Methodist 8 in real time, as an effort to support teachers in implementing a more adaptive and responsive learning approach. This system is designed by integrating facial recognition and emotional expression analysis through a camera, which is then processed using the Certainty Factor method to determine the confidence level of the detected emotional classification. This approach allows the system to generate emotional diagnoses with a reliable degree of confidence, based on predefined parameters. Test results have shown that the software is capable of detecting several basic emotions such as happiness, sadness, anger, and neutrality with an adequate level of accuracy. The implementation of this system in classrooms is expected to assist teachers in quickly identifying students’ emotional states, allowing learning strategies to be adjusted accordingly to improve the effectiveness of the learning process. Therefore, this technology offers an innovative solution in supporting the improvement of education quality through an approach that focuses on individual students.
Co-Authors Aispriyani Amallia, Dwi Novia Andika, Dhini Andriani, Santy Arikhifo, Arikhifo Bosker Sinaga Breukelen, Melisa Van Chandra Setiawan, Chandra Erwin Panggabean Eviyanti Br Barus, Eviyanti Br Barus Fitri Amalia Ginting, Feryanto Harefa, Jikarni Hutahaean, Harvei Desmon Jijon Raphita Sagala, Jijon Raphita Khairunnisa, Putri Kumar, Prasanth M, Melia Manurung, Oktaviani MARA UNTUNG RITONGA, MARA UNTUNG Marpaung, Endra Ary Prasasty N, Anisa Nantheni, W.S.Usha Nasution, Rizki Fadila Nuraisana, Nuraisana Romili Sitanggang, Kristiani Saragih, Diana Sari Muliani Sianipar, Baringin Sihotang, Hengki Tamando Simangunsong, Agustina Simangunsong, AgustinaS Simanjorang, R. Magdalena Simanjorang, R. Mahdalena Simbolon, Liber Sinaga, Dedi Candro Parulian Sitohang, Amran SITORUS, IRMA YOLANDA Sulindawaty T, Eliska Tarigan, Devri Wira Apriani