Implementasi Sistem Pakar Diagnosa Artificial Intelligance Addcition Berbasis Web Menggunakan Metode Certainty Factor Studi Kasus HIMAGIRI UNS

Authors

  • Bagas Riatma Putera Unpam
  • Badriah Nursakinah Universitas Pamulang

DOI:

https://doi.org/10.32493/jiup.v10i4.53717

Keywords:

Expert System; Certainty Factor; Artificial Intelligence Addiction; Diagnosis, Web-based; Students; HIMAGIRI UNS

Abstract

The development of modern Artificial Intelligence (AI) technology has enhanced human interaction with intelligent systems in daily life; however, excessive use of AI can lead to AI Addiction, particularly among university students. This study aims to design and develop a web-based expert system using the Certainty Factor (CF) method to identify early symptoms of AI addiction and calculate the likelihood level of dependence based on user input. The case study was conducted on students of the Informatics Student Association (HIMAGIRI), Universitas Sebelas Maret (UNS), with symptom data obtained from the adaptation of the AI Addiction Scale (AIAS-21) and interviews with psychological experts specializing in addiction, anxiety, and mood disorders. Testing using Black Box Testing and White Box Testing demonstrated that all system functions operated properly and produced consistent diagnostic calculations. From 77 respondents, addiction tendencies were dominated by the Continued Use Despite Harm category (38%), followed by Compulsive Use/Loss of Control (33%) and Withdrawal (29%). These results indicate that the Certainty Factor method is effective in detecting AI addiction tendencies and providing relevant treatment recommendations, making this expert system a useful early detection tool as well as an educational medium to increase students’ self-awareness of their dependence on AI.

Keywords: Expert System; Certainty Factor; Artificial Intelligence Addiction; Diagnosis, Web-based; Students; HIMAGIRI UNS

References

Himmatul Aliyyah, S., Laily Fithri, D., Irawan, Y., Muria Kudus Jl Lkr Utara, U., Kulon, K., Bae, K., Kudus, K., & Tengah, J. (2025). Implementasi Sistem Pakar Pendeteksi Tingkat Kecanduan Gadget Menggunakan Metode Certainty Factor. Jurnal Nasional Komputasi Dan Teknologi Informasi (JNKTI), 8(1).

Muhammad Robith Adani. (2021, April 27). Pengertian Sistem Pakar. Sekawab Media.

Nugroho, B. A., Sulistyohati, A., & Arfa, A. N. (2025). IMPLEMENTASI METODE CERTAINTY FACTOR PADA SISTEM PAKAR DIAGNOSA GANGGUAN KESEHATAN MENTAL. Jurnal Riset Dan Aplikasi Mahasiswa Informatika (JRAMI), 06.

Pakpahan, R. (2021). ANALISA PENGARUH IMPLEMENTASI ARTIFICIAL INTELLIGENCE DALAM KEHIDUPAN MANUSIA. Journal of Information System, Informatics and Computing Issue Period, 5(2), 506–513. https://doi.org/10.52362/jisicom.v5i2.616

Setiawi, A. P., Patty, E. N. S., & Making, S. R. M. (2024). Dampak Artificial Intelligence dalam Pembelajaran Sekolah Menengah Atas. Indo-MathEdu Intellectuals Journal, 5(1), 680–684. https://doi.org/10.54373/imeij.v5i1.826

Shahzad, M. F., Xu, S., Lim, W. M., Yang, X., & Khan, Q. R. (2024). Artificial intelligence and social media on academic performance and mental well-being: Student perceptions of positive impact in the age of smart learning. Heliyon, 10(8). https://doi.org/10.1016/j.heliyon.2024.e29523

Sulistyo, D. B., Saifulloh, S., & Nita, S. (2024). Implementasi Metode Certainty Factor dalam Sistem Pakar Diagnosa Kecanduan Media Sosial. Digital Transformation Technology, 4(1), 480–489. https://doi.org/10.47709/digitech.v4i1.4356

Wiyono, R. A., Dewi, E., Mulyani, S., Saputra, R. D., & Mulya, D. S. (n.d.). Aplikasi Sistem Pakar Diagnosis Kecanduan Media Sosial Berbasis Android Menggunakan Metode Forward Chaining Dan Certainty Factor.

Published

2025-12-20