A Decision Support System for Determining the Level of Digital Addiction Among College Students Using the TOPSIS Method

Adi Solikhin Solikhin; Isna Dhiyaa’ Asiffa; Anfusa Salma; Mayla Ilalhaque; Mahda Nur Sabrina

doi:10.59934/jaiea.v5i3.2472

Authors

Adi Solikhin Solikhin Universitas Muhammadiyah Brebes
Isna Dhiyaa’ Asiffa Universitas Muhammadiyah Brebes
Anfusa Salma Universitas Muhammadiyah Brebes
Mayla Ilalhaque Universitas Muhammadiyah Brebes
Mahda Nur Sabrina Universitas Muhammadiyah Brebes

DOI:

https://doi.org/10.59934/jaiea.v5i3.2472

Keywords:

Digital Addiction, Decision suppot system, TOPSIS, University Students

Abstract

Excessive smartphone use among college students has the potential to lead to digital addiction, which can negatively impact academic performance, mental health, and the quality of social life. This issue requires a systematic and objective approach to accurately identify the level of digital addiction. This study aims to develop a decision support system using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to determine the level of digital addiction among students based on five criteria: daily smartphone usage duration, frequency of accessing social media, sleep disturbances caused by gadget use, the impact of smartphones on study focus, and the frequency of gadget use during lectures beyond academic needs. Data were collected via a questionnaire distributed to 30 active students. The results of the TOPSIS calculations showed that 63.3% of students fell into the moderate category, 23.3% into the high category, 10.0% into the low category, and 3.3% into the very high category, with an average preference value of 0.4210. These findings indicate that digital addiction is a real and fairly widespread problem among students. The TOPSIS-based decision support system has proven capable of producing objective and measurable classifications, making it an effective tool for educational institutions in designing targeted intervention programs to address student digital addiction.

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