Optimalisasi Penilaian Aset Tetap Berbasis AI, Analisis Akurasi Estimasi Nilai Wajar dan Penyusutan di Era Digital - Suci Putri Astiti; Halmi (Program Studi Pendidikan Akuntansi, Fakultas Ekonomi, Universitas Negeri Makassar, 2026)
This study aims to analyze the optimization of Artificial Intelligence (AI) in fixed asset valuation, particularly in improving the accuracy of fair value estimation and depreciation in the digital era in Makassar City. The research employs a quantitative approach with data collected through questionnaires distributed to 200 respondents consisting of accounting and finance practitioners. The research instrument uses a Likert scale with 40 items representing variables of AI usage, supporting factors, fair value accuracy, and depreciation accuracy. Data analysis was conducted using SPSS software, including validity and reliability tests, classical assumption tests, and multiple linear regression analysis. The results indicate that AI usage has a positive and significant effect on the accuracy of fair value estimation and depreciation of fixed assets. Furthermore, supporting factors such as data quality, technological infrastructure, and human resource competence also significantly influence the optimization of AI implementation. Simultaneously, independent variables explain more than 50% of the variation in dependent variables. These findings confirm that AI implementation enhances efficiency, consistency, and accuracy in fixed asset valuation and supports better decision-making in the digital era.