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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Infotech: Journal of Technology Information AMMA : Jurnal Pengabdian Masyarakat Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Faldy Irwiensyah, Faldy
Departemen Obstetri & Ginekologi FKUI Rumah Sakit Cipto Mangunkusumo (RSCM) - Jakarta
Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

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Journal : JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)

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Implementasi Metode Teachable Machine Untuk Pengidentifikasian Ekspresi Wajah Secara Real-Time Pratama, Ridho Danang Budi; Irwiensyah, Faldy
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7819

Abstract

This study implements a direct facial expression detection system via the web using teachable machine and tensorflow.js. This system utilizes machine learning technology that operates directly in the browser without the need for a special server. With the transfer learning method, the model is trained to recognize various facial expressions such as happy, sad, angry, and neutral. This implementation uses a convolutional neural network (cnn) architecture that has been optimized for web activities. The results of the test show a detection accuracy level of 85-90% with a response time of under 200ms. This solution provides a lightweight option for emotion recognition applications that can be easily accessed via a web browser. The main advantages of this system are ease of implementation, cross-platform support, and maintaining data privacy because the process is carried out locally.
Analisis Sentimen Terhadap Ulasan Pengguna Pada Aplikasi BCA Mobile Menggunakan Metode Naïve Bayes Al Hakim, Muchammad Gamma; Irwiensyah, Faldy
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5343

Abstract

Technological developments have made the payment process easier, which has resulted in a plethora of smartphone applications. As mobile phones become more prevalent, commercial and public organizations are looking to improve the services they provide by implementing mobile-based solutions. The banking industry has seen tremendous expansion, as evidenced by the use of mobile banking solutions by companies such as BCA Bank. Especially in the midst of the pandemic, the BCA Mobile app is an important advancement in online banking that provides benefits and convenience to individuals who frequently transact online. Bank BCA can continue to offer the most useful features to customers while proactively improving services that are currently lacking. This study emphasizes the importance of improving sentiment analysis techniques to understand customer feedback more fully and provide better mobile banking services. This study uses the Naïve Bayes approach to analyze user sentiment towards the BCA Mobile application on the Google Play Store by finding and categorizing user reviews based on the sentiment they exhibit i.e. positive, negative, or neutral is the objective of this study. Through online data mining, 2000 user review data were collected on January 11, 2024, resulting in 1173 sentiments, 163 positive reviews and 1010 negative reviews in total. The Naïve Bayes algorithm produced an accuracy of 86.83%, precision of 52.78%, and recall of 46.91%.
Co-Authors Al Hakim, Muchammad Gamma Febriandirza, Arafat Firman Noor Hasan Pratama, Ridho Danang Budi Putri Lestari, Putri Rahman, Rafi Fadhlur Simamora, Silvia Damayanti Sunata, Muhamad Hafidz Ardian