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All Journal JOIN (Jurnal Online Informatika) Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika
Sandi Rahmadika
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Computer Science & IT

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Journal : Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika

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Pendeteksi Mood Mahasiswa Menggunakan Face Emotion Recognation Dengan Algoritma Haar Cascade Filinia Gusti; Ahmaddul Hadi; Sandi Rahmadika
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 2 (2025): Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i2.724

Abstract

Facial expressions are primary indicators of human emotions, often providing deeper insights than words (Oliver & Alcover, 2020). This study focuses on Mood as a natural response to past experiences, emphasizing its importance for psychological well-being. Over the past five years, the Covid-19 pandemic has triggered a significant global mental health crisis, affecting facial expressions and leading to varying degrees of depression and anxiety. Generation Z, particularly students, have been severely impacted, experiencing declines in academic abilities such as attention and memory (Qorik et al., 2020; Uswatun et al., 2020).In the educational context, the online learning systems adopted during the pandemic have introduced new challenges for students, including technical issues, lack of direct interaction, and less effective delivery of material, all of which contribute to increased academic stress (Rahmayinita, 2020; Utami et al., 2020). Enhancing the affective aspects of online education is crucial to better simulate face-to-face interactions (Bloom et al., 1984; Marzano & Kendall, 2007). This research aims to detect the Mood of students in online learning environments using advanced technology. The system is designed to assist educators in recognizing the academic stress levels of their students, enabling them to develop more creative and responsive teaching strategies (Zulfikri et al., 2023).
Co-Authors Ahmaddul Hadi Diena Rauda Ramdania Filinia Gusti Kweka, Bruno Joachim Maisevli Harika Ryan Fikri Winda Agustiarmi