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All Journal Journal of Tropical Soils JTSL (Jurnal Tanah dan Sumberdaya Lahan) Journal of Degraded and Mining Lands Management Habitat Jurnal Pengelolaan Laboratorium Pendidikan Jurnal Ilmiah Wahana Pendidikan Jurnal HPT (Hama Penyakit Tumbuhan) Jurnal Media dan Komunikasi
Aditya Nugraha Putra, Aditya Nugraha
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Religion Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Education Environmental Science Health Professions Social Sciences Other

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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.
Penerapan Desain dalam Feeds dan Reels Instagram Terhadap Antusiasme Penonton dalam Berdonasi Putra, Aditya Nugraha; Romadhona, Mahimma
Jurnal Ilmiah Wahana Pendidikan Vol 10 No 12 (2024): Jurnal Ilmiah Wahana Pendidikan 
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.12176129

Abstract

On World of Design, Design is used to make a person knowing the acknowledge about design, sometimes it used to be a message or a conveys to the world, like this journal which was written to be a guide for people to spread kindness and to teach people which design is compatible to a message, so many people don’t be outguided with the wrong guide of design basic
EVALUASI KESESUAIAN LAHAN KELAPA SAWIT PADA LAHAN GAMBUT DI PESISIR SELATAN, SUMATERA BARAT Arifin, Syamsul; Nugraha, Irfan Nur Priya; Al Jauhary, Muhammad Rifqi; Putra, Aditya Nugraha; Riza, Sativandi; Setiawan, Adi; Andhika, Yosi; Adril, Adril; Rayes, Mochtar Luthfi
JTSL (Jurnal Tanah dan Sumberdaya Lahan) Vol. 13 No. 1 (2026)
Publisher : Departemen Tanah, Fakultas Pertanian, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtsl.2026.013.1.4

Abstract

Indonesia's current population growth rate has reached 1.13% per year, leading to increased demand for land and consequent land use conversion, including peatlands. The conversion of peatlands into oil palm plantations raises several negative issues, such as increased carbon emissions. Therefore, it is crucial to consider the characteristics of peatlands when determining their suitability for crop cultivation. This study aims to assess peat quality, nutrient retention, and soil classification in the research area and evaluate the suitability of peatlands for oil palm cultivation in Pancung Soal. The research was conducted in an oil palm plantation in Nagari Tluk Amplu Inderapura, West Sumatra, using a survey method and parameters such as peat depth, ash content, and pH. The boundaries of land suitability classes were determined based on oil palm production results. The findings indicate variations in peat quality, nutrient retention, and suitability for oil palm cultivation. The analysis initially reveals land suitability classes ranging from S3 to N. However, with modifications to certain parameters, the suitability classes can be improved to S2 and S3. These results approximate suitability based on actual field productivity. Boundary delineation for specific parameters is necessary to enhance land suitability for oil palm in the region.
PEMETAAN BATAS PETAK LAHAN SAWAH PERSIL MENGGUNAKAN ALGORITMA DEEP LEARNING DI KECAMATAN KEPANJEN, KABUPATEN MALANG, JAWA TIMUR Savitri, Elvin; Putra, Aditya Nugraha; Candra, Danang Surya
JTSL (Jurnal Tanah dan Sumberdaya Lahan) Vol. 13 No. 1 (2026)
Publisher : Departemen Tanah, Fakultas Pertanian, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtsl.2026.013.1.19

Abstract

This research was conducted to mapping the boundaries of paddy fields in Kepanjen District, Malang Regency, using the U-Net deep learning model based on Convolutional Neural Network (CNN) for image classification per pixel. The input used was WorldView-2 imagery, and the model was trained with 25, 75, and 150 epochs variety to evaluate its performance in accurately classifying paddy field use down to the parcel scale. The 75 epochs variation model was used for image classification because it has balance between model performance and training period. Validation test were conducted using paired T-test to identify statisfically significant differences between the classified image paddy area and the actual field conditions. The results showed that U-Net model with various epoch variations did not differ significantly in terms of performance, the time taken for the model to learn the dataset per epoch, or accuracy, which reached 90%. The model was able to accurately classify paddy and non-paddy land use in WorldView-2 imagery down to the plot scale. Based on WorldView-2 image segmentation to identify paddy field boundaries, the paddy field area is 1217 Ha. The results were validated by comparing the area of rice fields in the image with the actual area of rice fields in the field. Validation test result with actual paddy area showed a calculated T (0,5486) lower than the T table (1,9603) and a p value (0,5833) greather than 0,05. This indicates no significant mean difference between the two data sets (ground check and imagery). The lack of significant difference provides strong evidence that the U-Net model is effective for mapping paddy plot boundaries on a large scale.
PEMETAAN DISTRIBUSI SPESIES POHON BERBASIS DEEP LEARNING DAN PENGINDERAAN JAUH DI KEBUN RAYA PURWODADI Pratiwi, Nisrina Salwa; Putra, Aditya Nugraha; Latifah, Evy
JTSL (Jurnal Tanah dan Sumberdaya Lahan) Vol. 13 No. 1 (2026)
Publisher : Departemen Tanah, Fakultas Pertanian, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtsl.2026.013.1.3

Abstract

Indonesia is rich in germplasm, with approximately 38,000 plant species spread across the archipelago. However, significant deforestation has led to a decline in species distribution, with deforestation rates reaching 1 to 1.8 million hectares from 1985 to 1998. The Purwodadi Botanical Garden serves as a mini prototype of Indonesia's plant diversity but lacks an integrated database on tree species distribution. This study aims to utilize Deep Learning and remote sensing technology for tree species mapping in the Purwodadi Botanical Garden. Using the RCNN Deep Learning model in ArcGIS Pro, the data includes SPOT 6 and 7 imagery, field observations of tree species, and object labeling based on taxonomic levels. The RCNN model successfully detected 235 tree objects with an accuracy of 72%, Precision of 84.45%, Recall of 70.29%, F1-score of 0.76, and an Average Precision of 61%. The species diversity index (H’) was recorded at 3.919161, while the evenness index (E) was 0.973619, indicating high biodiversity. A total of 56 species with 341 individuals were identified, including rare species such as Tectona grandis L. f., Adansonia digitata L., and Syzygium cumini. These findings demonstrate that Deep Learning technology can effectively support biodiversity monitoring.
Co-Authors Abda Abda Achmad Noerkhaerin Putra Adelyanti, Martiana Adi Setiawan Adril, Adril Al Jauhary, Muhammad Rifqi Alia Fibrianingtyas Andhika, Yosi Ayuningtyas, Priska Danang Surya Candra, Danang Surya Didik Suprayogo Erekso Hadiwijoyo Evy Latifah Fachry Abda El Rahman Fata, Yulia Amirul Fauziah, Dwi Christina Hadi, Maruf Hidayatullah, Rifqi Rahmat Istika Nita Iva Dewi Lestariningsih, Iva Dewi Kartika Budi Utami Kristiawati, Wanda Kurniawan Sigit Wicaksono, Kurniawan Sigit Lestari, Nina Dwi Luqmanul Hakim Melati Julia Rahma Mochtar Luthfi Rayes Nugraha, Irfan Nur Priya Nugroho, Agung Prasetya, Novandi Rizky Pratiwi, Nisrina Salwa Puspitasari, Siti Riza, Sativandi Rizki Maulana Ishaq Romadhona, Mahimma Samudra, Ferdianto Budi Saputra, Danny Dwi Sari, Rika Ratna Savitri, Elvin Sektiono, Antok Wahyu Sitorus, Albert Fernando Sudarto Sudarto Sugeng Prijono Sugiarto, Michelle Talisia Suryoprojo, Adithya Riefanto Syamsul Arifin