Article Per Year (5 Year)
p-Index From 2020 - 2025
0.778
P-Index
This Author published in this journals
All Journal Jurnal Belantara Journal of Information Systems and Informatics MAKILA: Jurnal Penelitian Kehutanan International Journal of Multidisciplinary Approach Research and Science
Basoka, Muhammad Darmawan
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Immunology & microbiology Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Identification of Landslide Susceptibility Level in Buffer Village Lore Lindu National Park Using Scoring Method Suni, Muhammad Adam; Mappatoba, Cesar Andi; Basoka, Muhammad Darmawan
International Journal of Multidisciplinary Approach Research and Science Том 1 № 02 (2023): International Journal of Multidisciplinary Approach Research and Science
Publisher : PT. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/ijmars.v1i02.96

Abstract

A landslide is a form of natural phenomenon that often occurs in mountainous and hilly regions with steep up to very steep slopes. Landslides are one of the most dangerous natural hazards and occur frequently in many hilly or mountainous areas, often occurring without warning and causing loss of life and property, marked with movement material of slope-forming materials in the form of rocks, soil, or materials down the slope. This study aimed to identify the distribution of landslide-prone areas in 86 buffer villages in Lore Lindu National Park, Central Sulawesi Province using geographic information system (GIS) based spatial analysis with scoring and overlay. The research parameters consisted of land cover/use, rainfall, elevation, slope, soil type, lithology, and distance from the fault. Identification of vulnerability factors for susceptibility level was determined according to 7 parameters used in the analysis. The results showed that the level of landslide susceptibility in the study area was divided into 3 classes, namely low (85.679,74 ha), moderate (363.184,89 ha), and high (26.888,46 ha). Villages that have a high level of vulnerability are Lempelero, Runde, Sedoa, Tuare, and Tongoa.
Spatial Analysis of Changes in Normalization Differences Vegetation Index in Protected Forest Areas of South Lore District, Poso Regency Suni, Muhammad Adam; Basoka, Muhammad Darmawan; Rafiq, Muhammad; Umar, Mohamad Fahrul Himalaya; Muis, Hasriani; Baharuddin, Rhamdhani Fitrah; Agusman, Agusman
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.577

Abstract

Detection of changes in vegetation density generally uses the vegetation index parameter. The value of the vegetation index can provide information on the proportion of vegetation cover, live plant index, plant biomass, cooling capacity, and estimation of carbon dioxide absorption. This study aims to analyze changes in the level of vegetation density using Sentinel 2-A imagery in the protected forest area of South Lore District. This study used the method of calculating the Normalized Difference Vegetation Index (NDVI) to identify changes in density over 5 years. The results of the NDVI analysis are the largest in the range of -0.92960 to 0.871725. The vegetation density class in the Protected Forest Area of South Lore District in 2017 is in the dense class with an area of 15,322.24 Ha or around 47.66%, while the smallest in the non-vegetation class, which is 103.11 Ha or 0.32%, while the largest vegetation density class is in the Protected Forest Area of South Lore District in 2022, namely in the medium/quite dense class with an area of 19,948.18 Ha or 62.01% while the smallest in the non-vegetation class of 219.17 Ha or 0.68%. The largest increase in area was in the moderate/quite dense class of 4,892.33 Ha or 15.20% while the largest decrease in area was in the dense class with an area of 6,651.16 Ha or 20.67% of the total area of the Protected Forest Area of South Lore District.
MODELING OF LANDSLIDE SUSCEPTIBILITY IN THE CORE ZONE OF THE LORE LINDU BIOSPHERE RESERVE USING GIS Suni, Muhammad Adam; Basoka, Muhammad Darmawan; Maarif, Fadjri; Mappatoba, Cesar Andi
Jurnal Belantara Vol 8 No 1 (2025)
Publisher : Forestry Study Program University Of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbl.v8i1.1029

Abstract

Landslide is a very dangerous natural disaster and often occurs in many hilly or mountainous areas, it often occurs without warning and causes loss of life and property, marked by the displacement of slope-forming material in the form of rocks, soil, or material down the slope. This study aims to model landslide-prone areas in the core zone of the Lore Lindu biosphere reserve in Central Sulawesi Province using the overlay method with a score between 6 parameters. The research parameters included land cover/use, rainfall, elevation, slope, soil type, and lithology. The weighting analysis produces three variables that determine the level of landslide vulnerability: slope, land use, and rainfall. The results showed that the level of vulnerability to landslides in the study area was divided into 4 classes, namely 17.482,15 ha (8,10%) non-prone areas, 98.372,96 ha (45,60%) low vulnerability areas, 98.032,51 ha (45,45%). moderate hazard area, and 1.832,04 ha (0,85%) high hazard area. In high vulnerability zones small or large-scale landslides often occur due to high rainfall and steep to very steep slopes, the rock forms in the form of sediment. Vegetation conditions are generally lacking. The areas included in this class are the villages of Bulili, Lawua, Sedoa, Katu, and Karunia.
Land Cover Classification Using Sentinel 2A Image in Lore Lindu National Park Area, Central Sulawesi Suni, Muhammad Adam; Maarif, Fadjri; Basoka, Muhammad Darmawan; Rafiq, Muhammad; Baharuddin, Rhamdhani Fitrah
MAKILA Vol 19 No 1 (2025): MAKILA: Jurnal Penelitian Kehutanan
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/makila.v19i1.17651

Abstract

Land cover within Lore Lindu National Park is undergoing a continuous transformation driven by both natural processes and anthropogenic pressures. Accurate mapping and classification of land cover types are critical for informed conservation planning and sustainable ecosystem management. This study aims to assess the effectiveness of Sentinel-2A satellite imagery combined with the supervised Maximum Likelihood Classification (MLC) method in delineating land cover types within the Lore Lindu National Park, Central Sulawesi. The research was conducted from August to December 2023 and involved four primary stages: image pre-processing through layer stacking, land cover classification, field verification (ground truthing), and accuracy assessment. The classification results yielded an Overall Accuracy (OA) of 83.75%, indicating a high level of reliability. A total of fifteen distinct land cover classes were identified, with secondary dryland forest occupying the most significant proportion of the area (approximately 80.60%), followed by primary dryland forest, plantation areas, and smaller fractions of rice fields, mining zones, and water bodies. These findings underscore the utility of Sentinel-2A imagery, in conjunction with the Maximum Likelihood algorithm, as a dependable tool for land cover mapping in tropical protected environments. The results provide a valuable spatial basis for developing targeted conservation strategies and enhance the understanding of landscape dynamics within the park.
Co-Authors Agusman, Agusman Baharuddin, Rhamdhani Fitrah Hasriani Muis Maarif, Fadjri Mappatoba, Cesar Andi Muhammad Adam Suni Muhammad Rafiq Suni, Muhammad Adam Umar, Mohamad Fahrul Himalaya