SISTEM PAKAR DIAGNOSIS KECANDUAN GAME MOBILE LEGENDS BERDASARKAN GAMING DISORDER SYMPTOM QUESTIONNAIRE (GDSQ) MENGGUNAKAN METODE CERTAINTY FACTOR

Putri, Refi Mariska (2025) SISTEM PAKAR DIAGNOSIS KECANDUAN GAME MOBILE LEGENDS BERDASARKAN GAMING DISORDER SYMPTOM QUESTIONNAIRE (GDSQ) MENGGUNAKAN METODE CERTAINTY FACTOR. S1 thesis, Universitas PGRI Madiun.

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Abstract

The rapid growth of information and communication technology has influenced the lifestyle of adolescents, especially in their increasing use of online games such as Mobile Legends. Excessive gaming behavior has raised concerns due to its potential to cause psychological, social, and academic issues. This study aims to design and evaluate a web-based expert system that diagnoses Mobile Legends addiction among children and adolescents aged 10–18 using the Certainty Factor (CF) method and the Gaming Disorder Symptom Questionnaire (GDSQ). The system was developed using the Extreme Programming (XP) model with Laravel framework and MySQL database. The CF method was applied to manage uncertainty in diagnosis by combining expert and user confidence levels toward specific symptoms. System development followed stages including planning, design, coding, and testing. Functional testing was carried out through Black Box Testing across 10 system scenarios. The results showed that all 10 test scenarios achieved 100% success, demonstrating the system's functionality. Additionally, validation by psychological experts on 15 student users confirmed the system’s accuracy, identifying 12 users with moderate addiction and 3 with severe addiction. No users fell under the mild category. The highest diagnosis result reached a CF value of 0.9999 (99%), confirming the method’s reliability in determining addiction levels. While the system performed well, improvements in data security—especially in protecting critical diagnostic data—are still needed. Overall, the expert system proved effective and reliable for early detection of Mobile Legends addiction and offers a valuable tool for parents, teachers, and counselors.

Item Type:	Thesis/Skripsi/Tugas Akhir (S1)
Kata Kunci:	Sistem pakar, kecanduan game, Mobile Legends, Certainty Factor, GDSQ, diagnosis dini.
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Teknik Informatika
Depositing User:	PUTRI MARISKA REFI
Date Deposited:	26 Aug 2025 04:09
Last Modified:	26 Aug 2025 04:09
URI:	http://eprint.unipma.ac.id/id/eprint/4491

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