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All Journal Journal of Tropical Soils JTSL (Jurnal Tanah dan Sumberdaya Lahan) BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Pengelolaan Laboratorium Pendidikan Jurnal HPT (Hama Penyakit Tumbuhan)
Riza, Sativandi
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Transportation

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KAJIAN KESUBURAN DAN KESESUAIAN LAHAN BERBASIS KOMODITAS DI KECAMATAN TUGU DAN KARANGAN KABUPATEN TRENGGALEK Arifin, Syamsul; Samudra, Ferdianto Budi; Utami, Kartika Budi; Putra, Aditya Nugraha; Setiawan, Adi; Riza, Sativandi; Andhika, Yosi; Maulidiyah, Nurul
Jurnal Tanah dan Sumberdaya Lahan Vol. 11 No. 2 (2024)
Publisher : Departemen Tanah, Fakultas Pertanian, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtsl.2024.011.2.18

Abstract

Drought is a major challenge in developing the integrated farming system (IFS) in Trenggalek Regency, making it one of the factors contributing to the construction of the Tugu Dam. Additionally, in developing the IFS area, it is necessary to assess soil fertility and land suitability evaluation for food and livestock feed commodities. The research was conducted in Tugu and Karangan Sub-Districts, Trenggalek Regency by conducting spatial analysis and soil survey at locations potentially affected by dam construction and soil samples analysis at the laboratory. The results of this study found that the level of soil fertility at the research site was included in the low to very low class with characteristics of acidic pH, very low C-organic, very low total N and low base saturation. While the results of the actual land suitability evaluation of rice, maize, and elephant grass showed the land suitability class S3 with limiting factors of C-organic, pH, total N, P2O5, and base saturation.
ANALISIS KELAYAKAN DETEKSI CEPAT PENYAKIT HAWAR DAUN TANAMAN KENTANG PADA FASE AKHIR MENGGUNAKAN UAV: LATE BLIGHT FEASIBILITY ANALYSIS IN POTATOES USING UAV FOR QUICK DETECTION IN LATE-STAGE Nita, Istika; Putra, Aditya Nugraha; Sektiono, Antok Wahyu; Riza, Sativandi; Wicaksono, Kurniawan Sigit; Sholikah, Dinna Hadi; Kristiawati, Wanda; Rahma, Melati Julia
Jurnal HPT (Hama Penyakit Tumbuhan) Vol. 11 No. 3 (2023)
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jurnalhpt.2023.011.3.2

Abstract

Produksi kentang di Indonesia berkontribusi + 0,3% dari total produksi dunia sebesar + 388.191.000 ton. Kentang merupakan komoditas hortikultura esensial di Indonesia dengan permintaan sekitar 2,82 kg ha-1 kapita-1 pada tahun 2021. Saat ini terjadi defisit ketersediaan kentang yang mencapai 4.845.910 ton yang diperparah dengan terus menurunnya produksi kentang nasional (1.164.738 ton). Penyakit hawar daun (Phytophthora infestans) merupakan salah satu masalah utama penyebab penurunan produksi kentang (kehilangan hasil antara 10-100%). Penyebaran penyakit hawar daun sulit untuk diidentifikasi secara real time, sehingga diperlukan teknologi tepat guna yang dapat memberikan informasi secara cepat dan akurat. Penelitian ini bertujuan untuk melihat bagaimana foto udara (dari UAV) memperkirakan sebaran penyakit hawar daun pada kentang. Foto UAV diubah menjadi indeks NDVI, RDVI, SAVI, SR, ARVI-2, DVI, IPVI, dan GCI. Data pengukuran indeks penyakit hawar daun akan dikorelasikan dan dipilih yang terbaik untuk mendapatkan rumus regresi distribusi spasial penyakit hawar daun. Lokasi penelitian berada di Kecamatan Bumiaji, Kota Batu, Indonesia. Titik pengamatan di lapangan sebanyak 50 titik pengamatan untuk setiap luasan 3 Ha. Hasil penelitian menunjukkan bahwa semua indeks berkorelasi positif (> r tabel 0,34). Korelasi tertinggi pada estimasi model dari indeks NDVI (0,72). Kondisi ini sejalan dengan koefisien regresi (R2) pada NDVI yang mencapai 0,51 dengan persamaan y = 20,779 * (angka indeks NDVI) + 49,146. Analisis t-paired menunjukkan bahwa t hitung pada model (-1,10) ada pada grafik t-tabel (2,16), dan ini menegaskan bahwa rumus tersebut dapat diandalkan untuk digunakan.
Invetarisasi Karakteristik Data Tanah Berbasis Formulir Digital dalam Kegiatan Praktikum Survei Tanah Andhika, Yosi; Riza, Sativandi; Putra, Aditya Nugraha
Jurnal Pengelolaan Laboratorium Pendidikan Vol.7, No.1, Januari 2025
Publisher : UPT Laboratorium Terpadu, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jplp.7.1.41-48

Abstract

Kegiatan praktikum survei tanah menggunakan metode konvensional dalam pengumpulan data, yaitu dengan mencatat data secara manual di lapangan. Pengamatan lapangan yang dicatat diantaranya fisiografi lahan dan morfologi tanah. Data yang telah dikumpulkan kemudian diolah dan disimpan dalam bentuk database. Database mampu memuat data dalam bentuk tabel, serta dapat ditambahkan dalam format lainnya, seperti gambar atau file dokumen. Namun, metode konvensional ini memiliki beberapa permasalahan, yaitu data yang dikumpulkan rentan terhadap kesalahan, proses pengolahan data memakan waktu lama, dan analisis data tidak dapat dilakukan secara langsung. ESRI Survey123 salah satu dari aplikasi mobile yang dapat digunakan untuk mengumpulkan data di lapangan secara real time. Data yang dikumpulkan dapat langsung diakses oleh analisis data di laboratorium, sehingga proses analisis data dapat dilakukan lebih cepat dan akurat. Dengan pemanfaatan ESRI Survey123, data yang dikumpulkan lebih akurat dan proses pengolahan data lebih cepat. Hal ini dapat meningkatkan efisiensi dan efektivitas kegiatan survei tanah. Sehingga perlu dilakukan pembuatan form Survey123 yang disesuaikan dengan daftar fisiografi lahan dan morfologi tanah, serta data yang sudah di himpun dari lapangan mampu dibuat dalam bentuk database
Impact of Reforestation After Forest Fire on Infiltration and Other Soil Physical Properties Lestariningsih, Iva Dewi; Mewar, Filza Roholesi; Anggara, Akmaludin Dimas; Lathif, Sarifudin; Sukbara, Ghozian Putra; Riza, Sativandi; Wicaksono, Kurniawan Sigit; Wang, Yumin
JOURNAL OF TROPICAL SOILS Vol. 29 No. 1: January 2024
Publisher : UNIVERSITY OF LAMPUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5400/jts.2024.v29i1.49-58

Abstract

Forest fires have become a vital issue causing various hydro-meteorological disasters. Many parties have carried out efforts. This study aimed to analyze the impact of land covers due to reforestation on infiltration rate and other soil physical properties related to hydrological conditions. The research was conducted in the Cempaka Forest area. There are four observed land covers, i.e., Timber Forest Products (TFP), Non-Timber Forest Products (NTFP), Pine, and Shrub. The results showed that land cover significantly affected the infiltration rate (p <0.05). The infiltration rate of Pine was not significantly different from NTFP but significantly different from TFP and Shrubs. The infiltration rate of Pine, NTFP, TFP, and Shrub land cover was 76.2 cm hr-1, 48.1 cm hr-1, 32.7 cm.hr-1, and 40.0 cm hr-1, respectively. The infiltration correlated with soil bulk density at two depths (0-15 cm and 16-30 cm) with r values of 0.614 and 0.595, respectively. Infiltration rate also significantly correlated with water content at pF 0 and pF 2.5 in the second soil depth. Additionally, soil bulk density is correlated with soil particle density with r  = 0.621. Soil particle density also correlated with clay content with r equal to 0.726.
PREDICTION OF SOIL PARTICLES USING A SPATIALLY ADAPTIVE GEOGRAPHICALLY WEIGHTED K-NEAREST NEIGHBORS ORDINARY LOGISTIC REGRESSION APPROACH Pramoedyo, Henny; Ngabu, Wigbertus; Iriany, Atiek; Riza, Sativandi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2815-2830

Abstract

Soil particle prediction is crucial in various fields, including agriculture, environmental management, and geotechnical applications. The spatial variation of soil texture significantly affects land fertility, erosion risk, and construction feasibility. However, conventional statistical methods and machine learning techniques often fail to capture the complex spatial heterogeneity in soil distribution. This study proposes the Geographically Weighted K Nearest Neighbors Ordinary Logistic Regression (GWKNNOLR) method to improve the accuracy of soil particle classification by integrating geographically weighted regression with an adaptive spatial weighting mechanism using the K Nearest Neighbors (KNN) algorithm. The objective of this research is to develop and evaluate a spatially adaptive classification model that more accurately predicts soil particle categories, namely sand, silt, and clay, by incorporating local spatial dependencies using GWKNNOLR in the Kalikonto watershed (DAS Kalikonto) in Batu. This study utilizes field measurement data combined with digital terrain modeling to analyze the relationship between local morphological variables and soil texture classification (sand, silt, and clay). The study area includes 50 observation points and 8 test variables. The model's performance is compared to the Ordinary Logistic Regression (OLR) method. The results indicate that GWKNNOLR achieves a classification accuracy of 88 percent, outperforming OLR, which only reaches 80 percent. Integrating KNN as a spatial weighting mechanism enhances adaptability to variations in sample distribution, leading to more accurate predictions. These findings emphasize the importance of considering spatial dependencies in soil texture modeling. The proposed method can support sustainable land resource management, erosion risk mitigation, and precision agriculture by providing more reliable soil classification. Future research may explore further optimization of spatial weighting mechanisms and the application of this method in different geographical regions.
Co-Authors Achmad Noerkhaerin Putra Aditya Nugraha Putra, Aditya Nugraha Andhika, Yosi Anggara, Akmaludin Dimas Atiek Iriany Henny Pramoedyo Istika Nita Iva Dewi Lestariningsih, Iva Dewi Kartika Budi Utami Kristiawati, Wanda Kurniawan Sigit Wicaksono, Kurniawan Sigit Lathif, Sarifudin Maulidiyah, Nurul Melati Julia Rahma Mewar, Filza Roholesi Samudra, Ferdianto Budi Sektiono, Antok Wahyu Sukbara, Ghozian Putra Syamsul Arifin Wang, Yumin Wigbertus Ngabu