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All Journal Semeton Mathematics Journal IJASDS: Indonesian Journal of Applied Statistics and Data Science
Apriliana, Baiq Nurul
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Economics, Econometrics & Finance Environmental Science Mathematics Public Health Social Sciences

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A Analisis Faktor Yang Mempengaruhi Ketergantungan Penggunaan Chatgpt Pada Pengerjaan Tugas Mahasiswa Universitas Mataram Zulhan Widya Baskara; Arbyati, Asri Mustika; Apriliana, Baiq Nurul; Putri, Devi Karina; Aisya, Hakiki Latifa; Putri, Dina Eka; Baskara, Zulhan Widya
Semeton Mathematics Journal Vol 2 No 2 (2025): Oktober
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v2i2.299

Abstract

The use of artificial intelligence technology, such as ChatGPT, is increasing among students to support their academic assignments. However, dependence on this technology needs to be analyzed to understand the factors that influence it. This study aims to analyze the factors that influence the dependence on the use of ChatGPT in completing assignments of Mataram University students. Sampling was carried out using the quota sampling method, involving 98 respondents who were Mataram University students and ChatGPT users. The method used was multiple linear regression to evaluate the effect of independent variables on dependence, and factor analysis to identify the structure of these variables. Based on the results of the analysis, one main factor was found which was formed from four variables, namely ChatGPT Ease of Use, ChatGPT Reliability, User Satisfaction, and Perceived Benefits. This main factor was able to explain 71.73% of the total data variation, which showed a significant contribution to students' dependence on using ChatGPT. Thus, this study shows that these variables are interrelated and influence the level of students' dependence on ChatGPT in completing academic assignments.
Meramal Produksi Padi Nasional: Pendekatan Moving Average dan Triple Exponential Smoothing Aisya, Hakiki Latifa; Apriliana, Baiq Nurul; Andriani, Helmina
Indonesian Journal of Applied Statistics and Data Science Vol. 2 No. 2 (2025): November
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v2i2.8494

Abstract

National rice production is a crucial indicator for maintaining food security in Indonesia. Seasonal fluctuations and annual trends in rice production require accurate forecasting methods to support strategic decision-making. This study aims to compare the forecasting accuracy of national rice production using the Moving Average and Triple Exponential Smoothing methods. Monthly rice production data from the 2020–2024 period were used as the basis of analysis. The forecasting results show that the Moving Average method tends to respond slowly to changes in actual production values, while the Triple Exponential Smoothing method is more responsive in capturing seasonal patterns and trends. Accuracy measurements indicate that Moving Average produced MAPE of 41.39%, MAD of 1,828,830 tons, and MSE of 6.24 , while the Triple Exponential Smoothing method provided better results with MAPE of 18.05%, MAD of 814,216 tons, and MSE of 1.13 . Based on these findings, the Triple Exponential Smoothing method is recommended as a more suitable and effective forecasting technique for national rice production data characterized by seasonal patterns.
Co-Authors Aisya, Hakiki Latifa Arbyati, Asri Mustika Dina Eka Putri Helmina Andriani Putri, Devi Karina Zulhan Widya Baskara