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Journal : Journal of Green Science and Technology

Evaluation of Temporary Evacuation Shelter (Tes) For Tsunami In Banggae Timur, Majene Based on Location-Allocation Analysis Erwin, Muh. Alfarezi; Priadmodjo, Anggit; Munaja, Rahmiyatal; Mulawarman, Ade; Mukhlis, Jafar; Wahyudi, Adip
Journal of Green Science and Technology Vol 9 No 2 (2025): Journal of Green Science and Technology Vol. 9 No.2 September 2025
Publisher : Faculty of Engineering, Universitas Swadaya Gunung Jati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33603/jgst.v9i2.10638

Abstract

Majene Regency, specifically the Banggae Timur District, is at considerable risk of tsunamis due to its coastal location and increasing urban density. This research evaluates the effectiveness of current Temporary Evacuation Shelters (TES) using a spatial analysis methodology combined with location-allocation modeling. The methodology included tsunami inundation mapping utilizing historical data, identification of building points, analysis of TES capacity, and modeling of service areas within a maximum evacuation radius of 935 meters.The study concentrated on two specific TES: Prasamya Stadium and the Majene Regency Police Station. Although both locations possess adequate capacity for hosting evacuees, they are situated within high-risk tsunami inundation zones (5–6 meters), making them inappropriate for safe evacuation. Spatial allocation modeling indicates that these TES predominantly serve the western section of Banggae Timur District, resulting in considerable underservicing of eastern coastal areas and increased risk. Of the 2,774 houses located within the tsunami inundation zone, 1,506 are currently unserved by the existing TES. The findings highlight the necessity of identifying and establishing new TES in safer, elevated areas with enhanced accessibility to improve evacuation coverage and safety. This study emphasizes the importance of spatial modeling in enhancing evidence-based disaster mitigation planning. It offers precise, data-driven insights for optimizing emergency infrastructure and minimizing population risk exposure in urban areas susceptible to tsunamis.
Gaps And Needs of Education Facilities in Majene Regency mukhlis, Jafar; Lestari, Sri Apriani Puji; Asriana, Zul; Munaja, Rahmiyatal; Hariani, Mira Lestira
Journal of Green Science and Technology Vol 8 No 2 (2024): Journal of Green Science and Technology Vol.8 No.2 September 2024
Publisher : Faculty of Engineering, Universitas Swadaya Gunung Jati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33603/jgst.v8i2.9581

Abstract

Majene Regency is located in West Sulawesi Province and is designated as a provincial education area causing the population to increase, the increase in population is not accompanied by an increase in the number of educational facilities which causes a lack of access to education. This study aims to determine and analyze the gap in educational facilities in Majene Regency and analyze the needs of ideal educational facilities in Majene Regency. This research is descriptive quantitative research, namely research that describes variables as they are supported by data in the form of numbers generated from actual circumstances. The result of this research is that most districts have educational facilities such as kindergarten, elementary school, junior high school, and high school. Only Banggae district and Tubu Sendana district and Ulumanda district do not have high school facilities. The education distribution gap occurs in Majene Regency, Majene Urban Area is most dominant in lacking educational facilities compared to other districts. This is not correlated with the status of the urban center which in fact provides and has more facilities and services than other districts. Efforts are needed to improve and develop educational facilities by adding educational facilities, especially high school education facilities, which have the highest demand. Keyword: facilities, distribution, needs, education.
Spatial Statistic Modeling for Rice Field Area Prediction Year 2026 to 2030 in Polewali Mandar Regency Mulawarman, Ade; Utami A, Widyanti; Priadmodjo, Anggit; Munaja, Rahmiyatal; Erwin, Muh. Alfarezi; Al-faridzi, Muh. Reza
Journal of Green Science and Technology Vol 10 No 1 (2026): Journal of Green Science and Technology Vol. 10 No.1 March 2026
Publisher : Faculty of Engineering, Universitas Swadaya Gunung Jati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33603/jgst.v10i1.11646

Abstract

The sustainability of rice fields is fundamental to maintaining regional food security, particularly in agricultural production centers such as Polewali Mandar Regency, West Sulawesi, Indonesia. Rapid population growth and spatial development have intensified pressure on productive agricultural land, increasing the risk of long-term decline in rice field availability. This study develops a spatial statistical modeling framework to predict the distribution of rice field conversion for the period 2026–2030 using an integration of Frequency Ratio (FR) and Spatial Multi-Criteria Analysis (SMCA) within a Geographic Information System (GIS) environment. Land cover data from 2010 and 2020 were used to identify historical conversion patterns and to construct predictive variables. Ten driving factors—including topography, slope, geomorphology, soil type, rainfall, accessibility, settlement characteristics, and spatial policy direction—were evaluated alongside protected agricultural zones as limiting constraints. Model validation using the Receiver Operating Characteristic (ROC) curve produced an AUC of 0.83 (success rate) and 0.75 (predictive rate), indicating good and reliable model performance. The projection results demonstrate continued pressure on rice field areas, particularly in zones influenced by infrastructure and settlement expansion. By providing spatially explicit predictions, this study offers a decision-support tool for proactive land-use regulation, agricultural protection policies, and strategic planning interventions aimed at safeguarding food self-sufficiency in the medium term.