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All Journal Agrotrop : Journal on Agriculture Science AGRITROP International Journal of Biosciences and Biotechnology Buletin Udayana Mengabdi E-Jurnal Agroekoteknologi Tropika (Journal of Tropical Agroecotechnology) Journal of Degraded and Mining Lands Management Agro Bali: Agricultural Journal Nandur Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian
I WAYAN NARKA
Program Studi Agroekoteknologi, Fakultas Pertanian, Universitas Udayana
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Education Environmental Science Other

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Aplikasi Sistem Informasi Geografis dan Penginderaan Jauh Untuk Analisis Potensi dan Kerentanan Longsor di Kecamatan Kintamani, Bangli Ardana, Made Putra Eka; Diara, I Wayan; Narka, I Wayan
Agrotrop : Journal on Agriculture Science Vol 14 No 1 (2024)
Publisher : Fakultas Pertanian Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Application of Geographic Information System and Remote Sensing for the Analysis of Landslide Potention and Vulnerability in Kintamani District, Bangli Regency. Kintamani District is an area that is prone to disasters; this is because of its geographical conditions which are located in the highlands and mountains with steep slopes. Research in this area is important to provide information on landslides for the public and government. The objective of this research is to determine the potential and landslide vulnerability. Delineating the potential for landslides used integration of remote sensing data and Geographic Information System (GIS) through the scoring method by overlaying the thematic that causes landslides (zones of susceptibility to soil movement, rainfall, land use, slope and soil type). The determination of landslide vulnerability is carried out by overlaying the landslide potential map with the settlement and road map. The results showed that Kintamani District has four landslide potential classes, namely the non-potential class which is a water area (Batur Lake) covering an area of 1616.13 ha, a low potential of 9350.61 ha, a medium potential of 15021.89 ha and a high potential of 10558.62 ha. The level of vulnerability to landslides in settlements consists of three classes, namely a low vulnerability class covering 1041.49 ha, a medium vulnerability area of 811.36 ha and a high vulnerability area of 174.52 ha. The level of vulnerability to landslides on the 307.16 km road network consists of two types of roads, namely primary collector roads and local roads. There are 23 distribution points of landslides found in research locations spread across Belancan, Kintamani, Bantang, Dausa, Sukawana, South Batur, Central Batur, Abangsongan, Abang Batudinding, and Trunyan Villages.
Effectivity Test of Compost Added By Coca-Cola Solid Waste Sludge With Water Spinach (Ipomoea Reptans POIR.) As an Indicator Arthagama, I Dewa Made; Bimantara, Putu Oki; Gunasih, Ni Made Tri; Narka, I Wayan
International Journal of Biosciences and Biotechnology Vol 11 No 1 (2023): International Journal of Biosciences and Biotechnology
Publisher : Central Laboratory for Genetic Resource and Molecular Biology, Faculty of Agriculture, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/IJBB.2023.v11.i01.p03

Abstract

Effectivity test of compost fertilizer added with Coca-Cola solid waste sludge with an indicator of water spinach (Ipomoea reptans POIR.), aiming to determine the effectiveness of the dose of compost added with Coca-Cola solid waste sludge to increase the yield of water spinach and improve some soil chemical properties. This research is a pot experiment in a greenhouse that was carried out in Kerambitan village, Tabanan region, Bali, Indonesia. Using a completely randomized design (CRD) consisting of 7 doses of compost added by Coca-Cola solid waste sludge. The compost that was used as a treatment was compost that had been added 20% of Coca-Cola solid waste sludge. The doses of compost tested were: K0 (control), K1 (3 tons of compost), K2 (6 tons of compost), K3 (9 tons of compost), K4 (12 tons of compost), K5 (15 tons of compost), Ka (250 kg urea + 50 kg phonska) per hectare, and each treatment was repeated 4 times so that 28 experimental pots were conducted. Parameters observed included: maximum plant height (cm), fresh plant weight at harvest, relative agronomic effectivities (RAE), oven-dry plant weight, soil pH, soil organic carbon (SOC), and soil CEC at harvest. Observational data were statistically analyzed, to determine the effect of the treatment being tried. If the treatment has a significant effect, then continue with the Duncans 5% test. The statistical analysis showed that the treatments had a significant effect on plant height growth, fresh and oven-dry weight of plants, as well as on some soil chemical properties. The heaviest fresh plant weight was obtained in treatment Ka (98.41 g), followed by K5 (98.35 g), K3 (98.33 g), and K4 (98.21 g) per pot. The highest value of relative agronomic effectiveness (RAE) was obtained in K5 (99.63 %), followed by K3 (99.58 %), and K4 (98.76 %). While the highest CEC was obtained in the treatment of K5 (40.25 me 100 g-1), K3 (39.75 me g-1) with successive organic-C levels (31.75%), (3.16 %) and pH (7.04), (7.0). The best dose of compost treatment from the results of this study was found in the K3 treatment (9 tons of compost ha-1).
Evaluasi Kualitas Tanah dan Pengelolaan Lahan Kering di Kecamatan Gerokgak dan Kubutambahan Kabupaten Buleleng, Provinsi Bali, Indonesia Sumarniasih, Made Sri; Kembaren, Donny Alfred; Narka, I Wayan; Karnata, I Nengah
Agro Bali : Agricultural Journal Vol 6, No 3 (2023)
Publisher : Universitas Panji Sakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37637/ab.v6i3.1517

Abstract

Penelitian ini dilakukan di Kecamatan Gerokgak yang terletak di bagian barat Kabupaten Buleleng, dan Kecamatan Kubutambahan yang terletak di bagian timur Kabupaten Buleleng. Tujuan penelitian adalah mengevaluasi perbedaan kualitas tanah, faktor pembatas dan arahan pengelolaan. Metode yang digunakan adalah survei untuk mengetahui karakteristik di lapangan dan pengambilan sampel tanah untuk diuji di laboratorium mengenai sifat fisik tanah (tekstur, kadar air kapasitas lapang, porositas, dan berat volume), sifat kimia tanah (KTK, KB, N-total, K, P-tersedia, C-organik, dan pH), dan sifat biologi tanah (C-biomassa). Berdasarkan hasil penelitian, kualitas tanah di Kecamatan Gerokgak tergolong baik (SLH G2, dan G4) seluas 37.793,00 ha dan kualitas tanah tergolong sedang (SLH G1, G3, G5, G6, G7, G8, G9, G10, dan G11) seluas 39.586,00 ha. Kualitas tanah di Kecamatan Kubutambahan tergolong sedang (SLH KB3, KB4, dan KB7) seluas 47.824,00 ha, dan tergolong buruk (KB1, KB2, KB5, KB6 dan KB8) seluas 50.120,00 ha. Faktor pembatas kualitas tanah di Kecamatan Gerokgak adalah kadar air kapasitas lapang, C-organik, KB, P-tersedia, N-total, C-biomassa, sedangkan di Kecamatan Kubutambahan adalah tekstur, kadar air kapasitas lapang, KTK, KB, N-total, C-biomassa. Pengelolaan lahan yang dilakukan di Kecamatan Gerokgak dan Kubutambahan adalah pemupukan dengan pupuk organik, pupuk urea, dan pembuatan bak penampungan air atau cubang.
A Assessment of Potential Damage and Loss of Subak Land Use Due to Flood Hazard in South Denpasar District, Denpasar City Sianturi, Harrixon Sangputra; Sumarniasih, Made Sri; Wiguna, Putu Perdana Kusuma; Narka, I Wayan; Bhayunagiri, Ida Bagus Putu; Mega, I Made
Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Vol. 22 No. 2 (2025): Volume 22 No 2, December 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jg.v22i2.31312

Abstract

South Denpasar District has an elevation of 0–12 meters above sea level and is categorized as a lowland area, making it prone to flood disasters. Flooding can cause damage and economic losses, particularly in the agricultural sector on subak lands. This study aims to calculate the potential damage and losses in subak land use in South Denpasar. The methods used include the Topographic Wetness Index (TWI) to analyze flood and damage potential, as well as field surveys for validation and loss estimation. The data used include DEM SRTM data, the Indonesian Topographic Map (RBI), the subak boundary map of South Denpasar District, and satellite imagery from Google Satellite. Data from the Department of Agriculture include subak area data. Data from the Agricultural Extension Center (BPP) and subak heads (pekaseh) include data on the cost components of subak production per hectare. Data from the Department of Public Works, Water Resources Division, include subak irrigation data and the cost components for constructing concrete irrigation channels per meter. The results show that subak land in South Denpasar has high damage potential covering 91,732 ha (20,48%), medium damage potential at 133,548 ha (29,81%), and low or no damage at 222,701 ha (49,71%). Areas with the largest subak damage potential are Subak Kerdung and Subak Kepaon. The potential damage to subak irrigation networks is classified as high 974,07 m (8,00%), medium 4.107,12 m (33,71%), and low or none 7.101,99 m (58,29%). The longest irrigation damage potentials are found in Subak Kerdung and Subak Intaran Barat. The total estimated subak loss in South Denpasar District is calculated by summing the losses from high and medium damage potential for each variable. The estimated loss for subak production is IDR 1,564,288,000, while the irrigation loss is IDR 1,496,626,727, resulting in a total potential loss of IDR 3,060,914,727. The highest losses are found in Subak Kerdung and Subak Kepaon. Policy recommendations include strengthening irrigation infrastructure, disaster mitigation training, and preserving the subak system through land conservation.
Mapping eruption affected area using Sentinel-2A imagery and machine learning techniques Trigunasih, Ni Made; Narka, I Wayan; Saifulloh, Moh
Journal of Degraded and Mining Lands Management Vol. 11 No. 1 (2023)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2023.111.5073

Abstract

Volcanic eruptions are natural disasters with significant environmental and societal impacts. Timely detection and monitoring of volcanic eruptions are crucial for effective hazard assessment, mitigation strategies, and emergency response planning. Remote sensing technology has emerged as a valuable tool for detecting and assessing the effects of volcanic eruptions. One of the challenges in remote sensing image processing is handling large data dimensions that are difficult to address using traditional methods. Machine learning approaches offer a suitable solution to tackle these challenges. Machine learning demonstrates increasing computational capabilities, the ability to handle big data and automation. This study aimed to compare different machine learning classification algorithms, including Random Forest (RF), Support Vector Machine (SVM), Gaussian Mixture Model (GMM), and K-Nearest Neighbors (KNN). The data utilized in this study was derived from Sentinel-2A Multi-Spectral Instrument (MSI) imagery, which was tested in areas affected by the eruption of Mount Agung, Bali Province, in 2017. The results indicated that the GMM algorithm performed the best among the machine learning classifiers, achieving an Overall Accuracy (OA) value of 82.04%. It was followed by RF (78.86%) and KNN (77.55%). The areas affected by volcanic eruptions were determined by overlaying disaster-prone regions with areas mapped using the machine learning approach. The total affected area was measured as 29.89 km2, with an additional 3.31 km2 outside the designated zone. The findings of this study serve as a guideline for governmental entities, stakeholders, and communities to implement effective mitigation efforts for disaster risk reduction.
Co-Authors AGUSTINA TANGKETASIK Agustina, I Komang Yudi ALDINO RYAN FAUZI Ardana, Made Putra Eka Bimantara, Putu Oki Boy Fernando Sagala DEVI LEORENSIA BOKINGS Gunasih, Ni Made Tri I DEWA MADE ARTHAGAMA I DEWA MADE ARTHAGAMA I Made Mega I Nengah Karnata, I Nengah I Nyoman Dibia I NYOMAN MERIT I NYOMAN SUNARTA I Wayan Dana Atmaja I Wayan Diara I.N. Dibia I.N. Merit I.N. `Dibia IDA BAGUS PUTU BHAYUNAGIRI IDA BAGUS PUTU WAHYU PERMANA Jamhari Jamhari Kembaren, Donny Alfred Ketut Dharma Susila Krisdianto Putra Sihombing Masana Frininta Sembiring moh saifulloh, moh NI MADE TRIGUNASIH NI MADE WIKARNITI Ni Nengah Soniari Putu Perdana Kusuma Wiguna RENI ANDRIANI NAIBAHO Sianturi, Harrixon Sangputra SUMARNIASIH, MADE SRI T. Kusmawati TATIEK KUSMAWATI TAUFIQ WARDANA WIYANTI WIYANTI