Keywords
Skala ketergantungan AI
adaptasi instrumen
validitas
reliabilitas
mahasiswa
AI Dependency Scale
instrument adaptation
validity
reliability
university students
How to Cite
Abstract
Perkembangan teknologi Artificial Intelligence (AI) yang semakin pesat telah mendorong meningkatnya penggunaan AI dalam berbagai aspek kehidupan, khususnya di lingkungan pendidikan tinggi. Meskipun AI memberikan berbagai manfaat dalam mendukung proses belajar dan penyelesaian tugas, penggunaan yang berlebihan berpotensi menimbulkan ketergantungan terhadap teknologi tersebut. Oleh karena itu, diperlukan instrumen yang valid dan reliabel untuk mengukur tingkat ketergantungan individu terhadap AI. Penelitian ini bertujuan untuk mengadaptasi dan mengevaluasi kualitas psikometrik AI Dependency Scale versi Bahasa Indonesia. Penelitian menggunakan pendekatan kuantitatif dengan melibatkan 180 mahasiswa aktif di Indonesia yang pernah menggunakan aplikasi berbasis AI. Proses adaptasi instrumen dilakukan melalui tahapan forward translation, sintesis hasil terjemahan, expert judgment, validitas isi menggunakan indeks Aiken’s V, pilot testing, dan backward translation. Kualitas psikometrik instrumen dievaluasi menggunakan Confirmatory Factor Analysis (CFA). Hasil CFA menunjukkan bahwa model tiga faktor memiliki tingkat kesesuaian yang baik (CFI = 0,958; TLI = 0,949; GFI = 0,960; SRMR = 0,033; RMSEA = 0,079). Seluruh item memiliki loading faktor yang signifikan terhadap konstruk yang diukur. Temuan ini menunjukkan bahwa AI Dependency Scale versi Bahasa Indonesia merupakan instrumen yang valid dan memiliki kualitas psikometrik yang baik untuk mengukur tingkat ketergantungan terhadap AI pada mahasiswa Indonesia. The rapid advancement of Artificial Intelligence (AI) technology has significantly increased its use across various aspects of daily life, particularly in higher education settings. Although AI offers numerous benefits in supporting learning activities and task completion, excessive reliance on AI may lead to dependency on the technology. Therefore, a valid and reliable instrument is needed to assess individuals’ levels of AI dependency. This study aimed to adapt and evaluate the psychometric properties of the Indonesian version of the AI Dependency Scale. A quantitative approach was employed involving 180 Indonesian university students who had experience using AI-based applications. The adaptation process included forward translation, translation synthesis, expert judgment, content validity assessment using Aiken’s V, pilot testing, and backward translation. The psychometric evaluation was conducted using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). CFA results indicated a good model fit (CFI = 0.958, TLI = 0.949, GFI = 0.960, SRMR = 0.033, RMSEA = 0.079). All items showed significant factor loadings on their respective constructs. These findings suggest that the Indonesian version of the AI Dependency Scale is a valid instrument with satisfactory psychometric properties for assessing AI dependency among Indonesian university students.References
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