Pemanfaatan Citra SAR Sentinel-1 dan Metode Random Forest untuk Pemantauan Perubahan Lahan Sawah (Studi Kasus: Kabupaten Sragen Tahun 2019 dan 2024)

Zahra, Annisa' Yasfa Az Zahra (2026) Pemanfaatan Citra SAR Sentinel-1 dan Metode Random Forest untuk Pemantauan Perubahan Lahan Sawah (Studi Kasus: Kabupaten Sragen Tahun 2019 dan 2024). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Lahan sawah merupakan aset strategis nasional yang berperan penting dalam mendukung ketahanan pangan Indonesia. Kabupaten Sragen sebagai salah satu lumbung padi di Jawa Tengah menghadapi tantangan akibat perubahan penggunaan lahan yang berpotensi mengurangi luas lahan sawah. Penelitian ini memanfaatkan Citra SAR Sentinel-1 dan algoritma Random Forest untuk memantau perubahan lahan sawah di Kabupaten Sragen pada tahun 2019 dan 2024. Tahapan penelitian meliputi preprocessing citra, ekstraksi nilai backscatter VV dan VH, serta klasifikasi menggunakan metode Random Forest. Tujuan penelitian ini adalah menganalisis pola sebaran dan perubahan luas lahan sawah, serta mengevaluasi akurasi hasil klasifikasi menggunakan Confusion Matrix berdasarkan data ground truth. Hasil penelitian diharapkan dapat menghasilkan informasi spasial yang akurat mengenai dinamika lahan sawah sebagai bahan pendukung perencanaan tata ruang, evaluasi kebijakan pertanian, dan upaya menjaga ketahanan pangan berkelanjutan di Kabupaten Sragen.
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Rice paddy fields are a national strategic asset that play a crucial role in Indonesia's food security. Sragen Regency, as one of the main rice-producing regions in Central Java, faces serious challenges due to land use conversion. This study utilizes Sentinel-1 SAR imagery, which has the capability to penetrate clouds and adverse weather conditions, combined with the machine learning algorithm Random Forest to monitor rice paddy field changes in Sragen Regency in 2019 and 2024. The objectives of this research are to analyze spatial distribution patterns and compare the extent of rice paddy fields, identify land changes that have occurred, and evaluate the classification accuracy of the integration between Sentinel-1 SAR imagery and the Random Forest method. The classification results are validated using a Confusion Matrix based on field survey data. This research is expected to produce accurate spatial information on the dynamics of rice paddy field changes, which can serve as essential input for spatial planning and evaluation of the Regional Spatial Plan (RTRW) in supporting sustainable food security policies in Sragen Regency.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Citra SAR Sentinel-1, Random Forest, Perubahan Lahan Sawah, Kabupaten Sragen, Klasifikasi Tutupan Lahan, Sentinel-1 SAR imagery, Random Forest, Rice Paddy Field Change, Sragen Regency, Land Cover Classification
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.212 ArcGIS. Geographic information systems. G Geography. Anthropology. Recreation > G Geography (General) > G70.217 Geospatial data G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Annisa' Yasfa Az Zahra
Date Deposited:	08 Jul 2026 07:57
Last Modified:	08 Jul 2026 07:57
URI:	http://repository.its.ac.id/id/eprint/134457

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