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All Journal JURNAL ILMIAH MATEMATIKA DAN TERAPAN Jurnal Aplikasi Sains Data
Dinda Galuh Guminta
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Mathematics

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Comparison of ARIMA and SARIMA Methods for Non-Oil and Gas Export Forecasting in East Java Dinda Galuh Guminta
Jurnal Aplikasi Sains Data Vol. 1 No. 1 (2025): Journal of Data Science Applications.
Publisher : Program Studi Sains Data UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/jasid.v1i1.2

Abstract

Forecasting plays a pivotal role in economic planning, particularly in aligning supply with demand and informing production decisions. This study aims to compare the performance of the Autoregressive Integrated Moving Average (ARIMA) and Seasonal ARIMA (SARIMA) models in forecasting the non-oil and gas export values of East Java, a region known for its dynamic trade activity. Using monthly time series data spanning from January 2007 to January 2024, sourced from the Central Statistics Agency (BPS) of East Java Province, this research conducts an in-depth analysis of forecasting accuracy and model suitability. Before model implementation, the dataset underwent several preprocessing steps to ensure its quality, including the handling of missing values and outlier adjustments. Both ARIMA and SARIMA models were developed, calibrated, and evaluated using standard forecasting performance metrics, namely Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). The ARIMA model exhibited consistently lower error rates across all three metrics, indicating its robustness in capturing the underlying patterns within the export data. In contrast, while the SARIMA model incorporated seasonal components, its performance did not surpass that of ARIMA in this specific case. The comparative findings suggest that, despite the seasonal nature of trade, the ARIMA model is more suitable for short-term forecasting of East Java’s non-oil and gas exports. This research contributes to the broader literature on economic forecasting by emphasizing the importance of selecting appropriate models based on data characteristics. Furthermore, the results provide valuable insights for policymakers and stakeholders engaged in export planning and regional trade development In this result the ARIMA model overcome the SARIMA with MAPE 0.116 to 0.983.
Higher-order SEM-PLS Modeling of School Readiness Among Indonesian Senior High School Students Dinda Galuh Guminta; Hasanuddin Al-Habib; Ulfa Siti Nuraini; Kartika Chandra Dewi
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 23 No. 1 (2026)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2026.v23.i1.18060

Abstract

Improving the quality of secondary education is a strategic priority in Indonesia due to its impact on human wellbeing. Secondary education faces challenges in improving the quality of learning and students' psychological readiness. School preparation is widely acknowledged as a multifaceted concept that highlights the significance of social-emotional engagement, self-regulation, and cognitive-motivational engagement. Therefore, this study aims to examine the construct of school readiness in Indonesia senior high school students using higher-order SEM-PLS. Results indicate that behavioral regulation is the strongest predictor of academic achievement (0.385) and functions as the central mechanism transmitting social-emotional engagement into academic outcomes. However, cognitive-motivational factors exert a competitive mediating effect, indicating that academic grades do not always improve among students who show strong cognitive-motivational engagement (-0.130). The results of this study highlight the important role of behavioral regulation in academic achievement and indicate that social-emotional engagement exerts the strongest overall influence on cognitive-motivational engagement, thereby supporting a multidimensional integrated model of school readiness.
Co-Authors Hasanuddin Al-Habib Kartika Chandra Dewi Ulfa Siti Nuraini