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All Journal Information Technology Education Journal Journal of Education for Creativity and Innovation
Muhammad Ilham Suherman
Universitas Negeri Makassar
Computer Science & IT Education Languange, Linguistic, Communication & Media Other

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Analisis Sentimen Ekspresi Wajah : Pendekatan Deep Learning dan OpenCV dengan Python Muhammad Ilham Suherman; Risha Febrianti; Fauziah; Novita Nurhidayah; Fadila Husnul Khatimah; Marwan Ramdhany Edy
Information Technology Education Journal Vol. 3, No. 3, September (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v3i3.5755

Abstract

Penelitian ini mengeksplorasi pendekatan Deep Learning dan OpenCV untuk mengembangkan sistem analisis sentimen ekspresi wajah menggunakan bahasa pemrograman Python. Ekspresi wajah merupakan bentuk komunikasi non-verbal yang penting dalam menggambarkan pikiran dan emosi seseorang. Dengan memanfaatkan teknologi Deep Learning dan OpenCV, penelitian ini bertujuan untuk memahami dan mengklasifikasikan emosi yang tersirat dalam ekspresi wajah dengan lebih akurat. Dataset gambar ekspresi wajah dikumpulkan dan digunakan untuk melatih model Deep Learning seperti Convolutional Neural Network (CNN) dan Deep Hybrid CNN (DHCNN). OpenCV dimanfaatkan untuk mendeteksi dan melacak wajah dalam gambar atau video. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan dapat mengklasifikasikan ekspresi wajah seperti bahagia, sedih, marah, takut, dan terkejut dengan akurasi yang cukup baik. Evaluasi performa dan visualisasi hasil juga disajikan untuk memberikan wawasan tentang keakuratan dan keterbatasan sistem.
Technology Acceptance Model of Perplexity AI and Its Impact on Student Academic Achievement: A PLS-SEM Approach Muhammad Ilham Suherman; Haripuddin; Ninik Rahayu Ashadi; Wirawan Setialaksana; Muhammad Riska
Journal of Education for Creativity and Innovation Vol. 1 No. 2 (2026): Februari
Publisher : PT. Global Research Collaboration

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Abstract

This study aims to analyze the effect of using Perplexity AI on the academic achievement of students in the Informatics and Computer Education Study Program at Makassar State University using the Technology Acceptance Model (TAM) framework. The background of this study is based on the increasing use of artificial intelligence in higher education, particularly the use of Perplexity AI, which helps students complete academic assignments and search for references. Although it offers convenience, the use of AI also poses challenges related to critical thinking and academic integrity, while research examining its influence on student academic achievement is still limited. This study uses a quantitative approach with an ex-post facto design. The research sample consisted of 249 students from the 2022–2023 cohort, determined using probability sampling techniques. Data were collected through questionnaires and analyzed using Partial Least Square–Structural Equation Modeling (PLS-SEM). The results show that Perceived Ease of Use (PEOU) has a significant effect on Perceived Usefulness (PU) with a value of β=0.800, t=27.297, p<0.001, but no significant effect on Behavioral Intention (BI) with a value of β=0.038, t=0.465, p=0.642. Furthermore, PU significantly affects BI with a value of β=0.685, t=8.724, p<0.001 and Academic Achievement (PA) with a value of β=0.368, t=4.220, p<0.001. BI significantly affects Actual System Usage (ASU) with a value of β=0.758, t=17.614, p<0.001, and ASU significantly affects PA with β=0.489, t=5.847, p<0.001. Therefore, it can be concluded that the use of Perplexity AI has a positive impact on improving student academic achievement through perceived benefits and actual usage intensity.
Co-Authors Fadila Husnul Khatimah Fauziah Haripuddin Marwan Ramdhany Edy Ninik Rahayu Ashadi Novita Nurhidayah Risha Febrianti Riska, Muhammad Setialaksana, Wirawan -