ANALISIS JENIS BUDIDAYA TEBU MENGGUNAKAN ALGORITMA RANDOM FOREST (STUDI KASUS KECAMATAN TAJINAN, KABUPATEN MALANG)

Muhammad Nurhadi; Prima Widayani; Sandy Budi Wibowo

doi:10.21776/ub.jtsl.2025.012.2.6

Authors

Muhammad Nurhadi Program Studi Magister Penginderaan Jauh, Fakultas Geografi, Universitas Gadjah Mada https://orcid.org/0009-0002-3604-9861
Prima Widayani Departemen Sains Informasi Geografi, Fakultas Geografi, Universitas Gadjah Mada https://orcid.org/0000-0003-0891-2074
Sandy Budi Wibowo Departemen Sains Informasi Geografi, Fakultas Geografi, Universitas Gadjah Mada https://orcid.org/0000-0002-0896-3413

DOI:

https://doi.org/10.21776/ub.jtsl.2025.012.2.6

Keywords:

Classification, Cultivation type, PlanetScope, Random Forest, Sugarcane

Abstract

Indonesia's national sugar demand continues to increase, while domestic production is still limited due to the lack of accurate data on the area and type of sugarcane cultivation. To address this issue, this research utilized the Random Forest (RF) algorithm on PlanetScope satellite imagery to classify the types of sugarcane cultivation, i.e. early planted sugarcane and pressed sugarcane. This study offers a more detailed approach than previous studies by dividing sugarcane based on its growth cycle into two main classes: < 3 times and ≥ 3 times. The results showed that the Random Forest (RF) method was able to increase the mapping accuracy to 94.52%, higher than conventional methods which are generally in the range of 85-91%. Of the three classification schemes tested, Scheme 3 produced the best performance with an accuracy of 94.52% and a Kappa coefficient of 43.87%. The mapping results also revealed that sugarcane cultivation of ≥ 3 squeezes dominated the study area with 93.08% coverage of the total sugarcane land, while sugarcane of < 3 squeezes only covered 7.55%. The difference between the classification results and the field data shows that the imbalance in the number of samples and spectral similarity between classes are the main challenges in mapping sugarcane cultivation. This finding proves that the Random Forest algorithm with PlanetScope images can significantly improve the accuracy of sugarcane cultivation type mapping compared to previous methods. The results of this study make an important contribution in providing more accurate spatial data to support sugarcane production estimation, optimization of plantation management, and strategic planning in achieving national sugar self-sufficiency.

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References

Badan Pusat Statistik Kabupaten Malang. 2024. Kabupaten Malang dalam Angka 2023. Kabupaten Malang: Badan Pusat Statistik Kabupaten Malang, 545 hal, ISSN:0215-5680

Durroh, B. (2018). Analisis program bongkar ratoon tanaman tebu untuk akselerasi peningkatan produktivitas gula (studi kasus di wilayah Pabrik Gula Semboro Kabupaten Jember Provinsi Jawa Timur). Agroista Jurnal Agroteknologi, 2(2). https://doi.org/10.55180/agi.v2i2.32

Hartoyo, B., & Harwanto. (2018). Kinerja Produksi Tebu pada Berbagai Teknologi Sistem Tanam di Kabupaten Blora Jawa Tengah. In B. Hariyanto Prosiding Seminar Nasional Status dan Inovasi Teknologi Tanaman Tebu (pp. 186-190). Balai Penelitian Tanaman Pemanis dan Serat Pusat Penelitian dan Pengembangan Tanaman Perkebunan Badan Penelitian dan Pengembangan Pertanian. http://repository.unitri.ac.id/1814/1/Prosiding%20Tebu%202018_compressed.pdf

Gunawan, S., Aju, P., Hidayat, A. (2018). Pengayaan Vinasse dengan Konsorsium Mikroba dan Pengaruhnya terhadap Pertumbuhan serta Produktivitas Tanaman Tebu (Saccharum officinarum L.). In B. Hariyanto Prosiding Seminar Nasional Status dan Inovasi Teknologi Tanaman Tebu (pp. 128-133). Balai Penelitian Tanaman Pemanis dan Serat Pusat Penelitian dan Pengembangan Tanaman Perkebunan Badan Penelitian dan Pengembangan Pertanian. http://repository.unitri.ac.id/1814/1/Prosiding%20Tebu%202018_compressed.pdf

Kadarwati, F. T., Santoso, B., & Khuluq, A. D. (2015). Peningkatan Produksi dan Rendemen Tebu Melalui Rawat Ratoon. Jurnal Litri, 21(4), 199-205. ISSN:0853-8212

Kementerian Pertanian. (2023). Outlook Komoditas Perkebunan Tebu. Pusat Data dan Sistem Informasi Pertanian Sekretariat Jendral - Kementerian Pertanian 2022, 95 hal, ISSN:1907-1507

Li, M., & Wu, J. (2023). Understanding the role of training sample size in the uncertainty of land use/land cover classification. Earth Science Informatics. https://doi.org/10.1007/s12145-023-01117-1

Mandala, M., Indarto, I., Hidayah, E., & Hakim, F. L. (2021). Mapping of Dry Marginal Agricultural Land Occupation and Change Using Landsat-8 and Sentinel-2. Journal of Engineering Science and Technology Review, 14(6), 211–219. https://doi.org/10.25103/jestr.146.24.

Magarey, R., Kristini, A., Goebel, R, F., Achadin, M, E. (2018). Pengayaan Vinasse dengan Konsorsium Mikroba dan Pengaruhnya terhadap Pertumbuhan serta Produktivitas Tanaman Tebu (Saccharum officinarum L.). In B. Hariyanto Prosiding Seminar Nasional Status dan Inovasi Teknologi Tanaman Tebu (pp. 33-35). Balai Penelitian Tanaman Pemanis dan Serat Pusat Penelitian dan Pengembangan Tanaman Perkebunan Badan Penelitian dan Pengembangan Pertanian. http://repository.unitri.ac.id/1814/1/Prosiding%20Tebu%202018_compressed.pdf

Naruputro, A dan Purwono. 2009. Pengelolaan Tanaman Tebu (Saccharum Officinarum L) Di Pabrik Gula Krebet Baru, PT. PG. Rajawali I, Malang, Jawa Timut; Dengan Aspek Khusus Mempelajari Produktivitas Pada Tiap Kategori Tanaman. Makalah Seminar Departemen Agronomi Dan Hortikultura. Institut Pertanian. Bogor. 5 h.

Nihar, A., Patel, N. R., Pokhariyal, S., & Danodia, A. (2022). Sugarcane crop type discrimination and area mapping at field scale using sentinel images and machine learning methods. Journal of the Indian Society of Remote Sensing, 1-9. https://doi.org/10.1007/s12524-021-01444-0

Nugroho, C. (2018). Penyakit Luka Api Tebu: Potensi Penyebaran dan Manajemen Pengendaliannya di Sulawesi Tenggara. In B. Hariyanto Prosiding Seminar Nasional Status dan Inovasi Teknologi Tanaman Tebu (pp. 186-190). Balai Penelitian Tanaman Pemanis dan Serat Pusat Penelitian dan Pengembangan Tanaman Perkebunan Badan Penelitian dan Pengembangan Pertanian. http://repository.unitri.ac.id/1814/1/Prosiding%20Tebu%202018_compressed.pdf

Singh, R., Patel, N. R., & Danodia, A. (2020). Mapping of sugarcane crop types from multi-date IRS-Resourcesat satellite data by various classification methods and field-level GPS survey. Remote Sensing Applications: Society and Environment, 19, 100340. https://doi.org/10.1016/j.rsase.2020.100340

Sulistiyanto, Q. T., Sinaga, M. S., & Suryanda, A. (2021). Pemahaman dan Perspektif Mahasiswa Mengenai Manfaat Air Tebu (Saccharum officinarum) dalam Prospek Kesehatan. Jurnal Pro-Life, 8(3), 199–204. https://ejournal.uki.ac.id/index.php/prolife

Wiranata, Y. S. (2014). Faktor-faktor yang mempengaruhi impor gula pasir di Indonesia tahun 1980-2010. Economics Development Analysis Journal, 3(4). https://doi.org/10.15294/edaj.v3i4.1041