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Journal : JOIN (Jurnal Online Informatika)

A Comparison of YOLOv8 Series Performance in Student Facial Expressions Detection on Online Learning Tresnawati, Dewi; Nurhidayanti, Shopi; Lestari, Nina
JOIN (Jurnal Online Informatika) Vol 10 No 1 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i1.1390

Abstract

Student engagement in online learning is an important factor that can affect learning outcomes. One indicator of engagement is facial expression. However, research on facial expression detection in online learning environments is still limited, especially in the use of the YOLOv8 algorithm. This study aims to compare the performance of several YOLOv8 variants, namely YOLOv8x, YOLOv8m, YOLOv8s, YOLOv8n, and YOLOv8l in recognizing six facial expressions: happy, sad, angry, surprised, afraid, and neutral. Student facial expression data was collected through the Moodle platform every 15 seconds during the learning process. All models were trained using 640x640 pixel images for 100 epochs to improve facial expression detection capabilities. The main contribution of this study is to provide a comprehensive analysis of the effectiveness of YOLOv8 in detecting student facial expressions, which can be used to improve the online learning experience. The evaluation results show that the YOLOv8s model has the best performance with the highest mAP of 0.840 and the fastest inference speed of 2.4 ms per image. YOLOv8m and YOLOv8x also performed well with mAP of 0.816 and 0.815, respectively. Although YOLOv8x had the slowest inference speed, it was superior in detecting fear, happiness, and sadness expressions with mAP above 0.9. YOLOv8n had mAP of 0.636, while YOLOv8l achieved mAP of 0.813 with an inference speed of 9.1 ms per image. This study shows that the YOLOv8 algorithm, especially YOLOv8s, can be an effective solution to analyze student engagement based on their facial expressions during online learning.
Plant Disease Detection Using Digital Image Processing: Opportunities and Challenges Fitriani, Leni; Fatimah, Dini Destiani Siti; Tresnawati, Dewi
JOIN (Jurnal Online Informatika) Vol 10 No 2 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i2.1330

Abstract

Diseases in plants affect the yield of the plant itself. Agriculture is essential in human life, and if plant conditions are left unchecked, it will result in crop failure, which can affect the economy. Many researchers have developed methods to detect plant diseases, ranging from expert systems to deep learning algorithms. Machine learning is particularly effective for this task as it relies on datasets composed of plant images, making image processing crucial for the identification process. This article reviews the current literature and identifies several research gaps, opportunities, and challenges that must be addressed. Specifically, the article outlines potential avenues for future research in detecting plant diseases using image processing techniques. A significant opportunity exists to develop more effective algorithmic models for detecting plant diseases.
Co-Authors Ade Sutedi Ade Sutedi, Ade Adinugraha, Yudistira Agas Moch Fauzan Agung Gumelar Agung Khofidin Agus Nugraha Ahdan, Alfin Muhamad Ahmad Arif Budiman Ai Adhayani Aldi Nur Puadi Alfi Saeful Milah Alim, Ikbal Nur Alsi Linda Sari Andi Fauzi Andri Ikhwana Anita Nurvitrya Apriadi, Ari Ardiansyah, Ryan Arief Pinasti Nugraha Ary Akbar Sidiq Ary Setijadi Prihatmanto Asep Deddy Supriatna Asri Mulyani Asyah, Cha Cha Nisya Ayu Latifah Cecep Saepuloh Cecep Sahlan Ma'rup Chandra Wijaya Dauni, Popon Dede Kurniadi Deden Nurul Hakim Dhami Johar Dhamiri Diki Setiadi Diki Silviadi Dimitri Mahayana Dindin Sihabudin Ahmad Wardi Dini Destiani Siti Fatimah Dini Destiani Siti Fatimah Dini Destiani Siti Fatimah Dini Destiani Siti Fatimah Edi Hidayat Egi Ramdani Eko Retnadi Eneng Wildayanti Eri Satria Eri Satria Eri Satria Eri Satria Erwin Gunadhi Fahmi Ilham Ardiansyah Fahreza, Muhammad Fajar Haiqal Farida Nuraeni Fassa Fatmalasari, Intan Sri Fauzan, Wildan Ahmad Nur Fikri Fahru Roji Fitriani, Ranti Fitriyani, Ranti Garnisa, Sandra Budi Gugum Gumilar Setia Permana Handayani, Nanda Haniyah, Hani Hanna Qurrotul Aini Hariyana Sanjaya Hidayatno, Fachrul Ramdaniar Hidayattuloh, Yusuf Husni Mubarok I Putu Satwika Indri Tri Julianto Intan Fadzilatunnisa Iqbal Maulana Iqbal Setyawan Irgi Muhamad Albani Kamal, Muhammad Abyan Karti, Karti Khoerudin Yusuf Kresnapatty, Duva Kusumah, Rullyanto Angga Latifah, Ayu Leni Fitriani Leni Fitriani, Leni Lestari, Nina Lukman Hakim M. Iqbal Ismail Safei Pamungkas Maharani, Larasyla Putriana Maulana, Randi Muhamad Firzan Desfriansyah Muhammad Bagja Sukriyansah Muhammad Fauzy Muhammad Rikza Nashrulloh Mujakki, Akmal Muttaqin, Epwan Nurul Nahdi Hadiyanto nanang nanang Nasrullah, Muhammad Rikza Novitasari, Sinta Nugraha, Alwi Iswahyudi Nukholis Abdul Majid Nurahman, Gia Nurhidayanti, Shopi Nurhisyam, Fahmi Nurohmah, Novita Fitri Nurul Fitriyani Pardiansyah, Irgi Rahma Melati, Tri Rahman, Ridwan Arif rahmat Soleh Rendi Nurdian Rian Fardian Rizqi Ridwan Arif Rahman Ridwan Setiawan Ridwan Setiawan Rifa Ferdiansyah Rinda Cahyana Rinda Cahyana Riri Ratna Utami Risa Aisyah Riyad Sabilul Muminin Rizal Mustofa Rizwan Faiz Rojani Rozak Rahmat Rostilawati, Detila Rusdiawan, Mohamad Mihradi Salsabil, Ilham Sandy Mawardi sandy mawardi Sania Alvi Alviah Septiana Firdaus Setiawan, Asep Trisna Silviadi, Diki Sopiah, Dede SRI RAHAYU Sri Rahayu Sumarto Dian Waluyo Taufik Sapta Nugraha Widi Gumelar Yomi Guno Yosep Septiana Yudistira Adinugraha Yulia Nuriyanti Yusep Moch Yusup Zikrifah, Amelia