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All Journal MATHunesa: Jurnal Ilmiah Matematika Semeton Mathematics Journal
Fatanaya, Nafika
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Mathematics

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Analysis of Changes in Agricultural Land Area in Central Lombok Regency Using Google Earth Engine Ulatalita, Nabila Anzela; Fatanaya, Nafika; Ulfa, Kurnia; Robbaniyyah, Nuzla Af'idatur; Alfian, Muhammad Rijal
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.v2i2.317

Abstract

Agricultural land plays a vital role in supporting food security and the regional economy; however, rapid development often leads to land-use conversion. This study aims to analyze changes in agricultural land in Central Lombok Regency over the past ten years (2014–2023) using the Google Earth Engine (GEE) platform. The research utilized Landsat satellite imagery to classify land cover types and identify agricultural areas through supervised classification and change detection techniques. The analysis results show a significant decline in agricultural land area, from 29% in 2014 to 26% in 2023. This decrease indicates a conversion of agricultural land to other more economically profitable uses, such as infrastructure development and plantation expansion. The accuracy assessment yielded an overall accuracy of 99%, which is categorized as very good, demonstrating the reliability of the model in mapping land-use changes. The findings of this study are expected to provide useful insights for policymakers in promoting sustainable land-use planning and mitigating the negative impacts of land conversion on the agricultural sector in Central Lombok Regency.
RICE HARVEST AREA FORECASTING USING MOVING AVERAGE METHOD FOR FOOD SECURITY PLANNING Maharani, Andika Ellena Saufika Hakim; Andriani, Helmina; Robbaniyyah, Nuzla Af'idatur; Salwa; Fatanaya, Nafika
MATHunesa: Jurnal Ilmiah Matematika Vol. 13 No. 3 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v13n3.p29-36

Abstract

Ensuring food security is a key part of sustainable development in Indonesia, especially since rice remains the country's staple crop. In regions like West Nusa Tenggara (NTB) Province, where rice harvest areas can vary significantly, having accurate forecasts is essential for effective planning. This study explores historical data on rice harvest areas in NTB to forecast future trends, uncover seasonal patterns, and assess long-term changes. To do this, we apply and compare three forecasting methods: Simple Moving Average (SMA), Weighted Moving Average (WMA), and Exponential Moving Average (EMA). Their performance is evaluated using accuracy measures such as Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE), with results also presented visually to support data-driven decision-making. Among the methods tested, EMA with a 3-period window (EMA-3) produced the most accurate forecasts. This is reflected in its lower RMSE and MAPE values compared to the other methods. Based on the MAPE results, EMA-3 proves to be a reliable method for forecasting rice harvest areas in NTB.
Co-Authors Helmina Andriani Maharani, Andika Ellena Saufika Hakim Muhammad Rijal Alfian Robbaniyyah, Nuzla Af'idatur Salwa Ulatalita, Nabila Anzela Ulfa, Kurnia