Analisis Hubungan Durasi Penggunaan Smartphone dan Produktivitas Belajar Mahasiswa: Studi Eksploratif Monte Carlo
- Panca Ragil Prasetyo Universitas Amikom, Purwokerto, Indonesia
-
Purwadi Purwadi
*
Universitas Amikom, Purwokerto,
Indonesia
(*) Corresponding Author
Abstract
The rapid development of digital technology has made smartphones an essential part of students' academic activities. However, the high intensity of smartphone usage raises questions regarding its relationship with learning productivity. This study aims to analyze the relationship between smartphone usage duration and learning productivity among Informatics students and to explore the data using a Monte Carlo simulation approach. The study was conducted on 80 second- and fourth-semester Informatics students at Amikom University Purwokerto. Data analysis included descriptive statistics, validity testing, reliability testing, normality testing, Pearson correlation analysis, simple linear regression, and Monte Carlo simulation with 1,000 iterations using Python. The results revealed a Pearson correlation coefficient of with a significance value of indicating a negative but statistically insignificant relationship between smartphone usage duration and learning productivity. Simple linear regression analysis produced the regression equation with a coefficient of determination of , indicating that smartphone usage duration explains only a small proportion of the variance in students' learning productivity. Monte Carlo simulation was employed as an exploratory approach to illustrate the potential variation in learning productivity based on the characteristics of the observed data. The simulation results demonstrated variability in learning productivity scores across different smartphone usage scenarios; however, these findings cannot be interpreted as evidence of a significant effect between the two variables. This study concludes that the relationship between smartphone usage duration and learning productivity among Informatics students tends to be weak and is influenced by various factors beyond the scope of the proposed model. Therefore, further research with a larger sample size and additional explanatory variables is recommended to achieve a more comprehensive understanding of student learning productivity in the digital era. The contribution of this research lies in providing empirical evidence regarding the weak relationship between the two variables among informatics students, as well as demonstrating that the Monte Carlo simulation can be utilized as an exploratory approach to illustrate variations in possible outcomes based on empirical data characteristics, rather than as a conclusive predictive tool.
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