Helmi Hasan Basri
Sekolah Tinggi Ilmu Kehutanan Pante Kulu, Aceh, Indonesia

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Optimizing Soil Fertility To Achieve Food Security In Krueng Raya, Aceh Besar District Eka Sri Wulandari; Helmi Hasan Basri
International Journal of Multidisciplinary Sciences and Arts Vol. 5 No. 2 (2026): International Journal of Multidisciplinary Sciences and Arts, Article April 202
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v5i2.8268

Abstract

Agroforestry optimizes soil fertility by adding organic matter from tree litter, enhancing nutrient cycling, improving soil structure and water-holding capacity—all of which contribute to increased and stable crop yields, thereby supporting food security. Soil fertility optimization is the process of improving soil quality to make it more productive and support plant growth, including   which can be achieved through soil and water management techniques in agroforestry systems, beginning with periodic soil analysis to help determine plant nutrient needs and assist in establishing appropriate fertilization strategies. Soil fertility in agroforestry lands is crucial for supporting food security. Agroforestry, which involves the integration of trees with agricultural crops, can significantly enhance soil fertility through various mechanisms. The objective of this study is to analyze the soil in agroforestry lands regarding its physical and chemical properties, as well as to develop agroforestry-based land optimization strategies. The results indicate that the soil texture in Mon Village is loamy. Its chemical properties include slightly acidic soil (pH), low organic carbon (C-Organic), low total nitrogen (N-total), very low available phosphorus (P-available), and high soluble potassium (K-dd). The key factors determining the success of land optimization include: (a) Ecological aspects, such as the types of trees planted and soil fertility (i.e., soil physical and chemical properties), (b) economic aspects, including farmers’ knowledge of economic value, and (3) socio-cultural aspects, including community perception and participation, understanding of agroforestry systems, and the local wisdom of communities surrounding the forest.
GIS-Based Flood Risk Mapping in Kluet Tengah Subdistrict, South Aceh Helmi Hasan Basri; Bakruddin B
International Journal of Multidisciplinary Sciences and Arts Vol. 5 No. 2 (2026): International Journal of Multidisciplinary Sciences and Arts, Article April 202
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v5i2.8294

Abstract

Flooding is one of the most frequent hydrometeorological disasters in South Aceh Regency, particularly in Kluet Tengah Subdistrict, where overflow from the Menggamat River causes recurrent inundation of settlements, agricultural areas, and other land uses. This study aims to map flood risk spatially in Kluet Tengah Subdistrict using a Geographic Information System (GIS)-based overlay approach. The analysis was conducted using land cover and slope parameters derived from satellite imagery, Digital Elevation Model (DEM) data, and supporting records of flood events from relevant disaster management agencies. Spatial data were processed through clipping, classification, and overlay analysis to produce flood risk categories. The results show that high-risk areas are concentrated in lowland zones with flat to gentle slopes (0–30%), particularly in settlements, rice fields, and open land. Moderate-risk areas are associated with moderately steep slopes (30–50%) dominated by mixed gardens and shrubland, while low-risk areas are mainly located in steep to very steep uplands (>50%) covered by protected forest and the Gunung Leuser National Park area. These findings indicate that the interaction between land cover and slope plays an important role in shaping flood risk distribution in the study area. The resulting flood risk map can support spatial planning, disaster mitigation, and sustainable land management in flood-prone regions of South Aceh.
Socioeconomic and Farming Characteristics of Farmers in Kluet Tengah District, South Aceh, Indonesia Helmi Hasan Basri; Bakruddin B; Redra Mursija; Ebi Darmawan
International Journal of Multidisciplinary Sciences and Arts Vol. 5 No. 4 (2026): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v5i4.9791

Abstract

Socioeconomic and farming characteristics provide baseline information for agricultural planning in smallholder farming areas. This study described the socioeconomic and farming characteristics of 339 farmers in Kluet Tengah District, South Aceh Regency, Indonesia. A quantitative descriptive survey was conducted in 2026 using purposive sampling and structured interviews, and the responses were summarized as frequencies and percentages. The respondents were aged 20–64 years. Male respondents accounted for 237 (69.91%). Elementary and senior high school education were equally common (96 respondents; 28.32% each), and 168 (49.56%) reported three to four dependents. Most respondents (277; 81.71%) were in the lowest household-income category, below 1.5 million Indonesian rupiah. Plantation crops were the most common principal commodity (143; 42.18%), 189 respondents (55.75%) managed less than 0.5 hectares, and the most frequently reported distance from farmland to a river or major watercourse was 100–500 meters (116; 34.22%). These distributions point to limited household resources and small-scale farming structures among the surveyed farmers. Because respondents were purposively selected, the findings describe the surveyed farmers only and are not district-wide estimates. They provide a descriptive reference for local agricultural planning and for further studies that link farm characteristics to verified hazard and spatial data.