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Journal : Malcom: Indonesian Journal of Machine Learning and Computer Science

Geographic Information System Mapping of Location Distribution Homestay Area Waingapu City Sumba Web-Based East Sumba Jeti, Estherlita Grace Bulu; Talakua, Alfrian Carmen; Uly, Hawu Yogia Pradana
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 3 (2024): MALCOM July 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i3.1354

Abstract

Based on the results of the identification of the needs of tourists looking for lodging in the city of Waingapu, there is a lack of spatial information (latitude and longitude), non-spatial (owner's name, price, facilities, address, contact) with the nearest route. Although available on google maps, it is still lacking because it is still incorporated with hotels, boarding houses and other housing. Therefore, a Web-based Geographic Information System for Mapping the Distribution of Homestay Locations in the Waingapu City Area of East Sumba is made to provide recommendations to tourists who need lodging in accessing Homestayinformation by determining the user's location point and the nearest Homestay will appear. Maps will direct to the location of the selected lodging house accompanied by the desired information. This system was built using the PHP programming language with the MySQL Database. The method used in this research is the Waterfall model for system development and Euclidean Distance for the calculation of the closest distance.
Geographic Information System for Mapping Poverty Levels In East Sumba District Huluuma, Melania Mburu; Talakua, Alfrian Carmen; Uly, Hawu Yogia Pradana
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 1 (2024): MALCOM January 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i1.1050

Abstract

Poverty issues in East Sumba Regency, East Nusa Tenggara Province, which is faced with a high poverty rate. The obstacle of mapping areas with poor people that are difficult to identify is the main focus. Through qualitative and quantitative approaches, this research applied the Extreme Programming (XP) method to develop a web-based Geographic Information System (GIS), aimed at mapping poverty areas. XP was applied to ensure flexibility, adaptability, and active stakeholder participation in the application development. The main objectives were to produce an effective GIS application, provide accurate information for the government and stakeholders, and improve the effectiveness of poverty reduction programs. This research is expected to contribute to the design of programs that are more targeted, effective, and can improve community welfare in East Sumba Regency.