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All Journal Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Alsella Meiriza
Universitas Sriwijaya, Palembang
Computer Science & IT Decision Sciences, Operations Research & Management

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Penerapan Metode SOSTAC dalam Perancangan Sistem Informasi Space Rent UMKM Stasiun Rugaiyah Balqis; Pacu Putra; Nabila Rizky Oktadini; Alsella Meiriza; Putri Eka Sevtiyuni
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3247

Abstract

The provision of Space rent or space rental for LRT station MSMEs in Palembang City is a form of sensitivity and concern for economic growth in Indonesia. Currently, the dissemination of information regarding the provision of space rent for MSMEs is only limited to several social media such as Facebook and Instagram. This research aims to be able to provide new opportunities in the form of designing a marketing information system for Space rent UMKM at the Palembang City LRT station using a website. System design must be by applying methods that can formulate, control, and evaluate the system so that it can be right on target according to user needs. This research is a descriptive qualitative research using the results of the analysis of direct interviews with five informants consisting of business development parties of the South Sumatra Light Railway Management Center, station UMKM business actors, and the general public which are used as reference materials for the formulation of analyses into the method used, namely the SOSTAC method which is implemented through a prototype website and tested through blackbox testing. The results of this research are in the form of the Palembang City LRT Station Space rent MSME website which can be used as a marketing media and MSME sales information system according to user needs. Based on testing through blackbox testing, it was found that the Palembang City LRT Station UMKM Space rent website had run well.
Comparison of Clustering Algorithms for Analyzing the Impact of Conflict on Poverty and Inflation M Raykah Alam Ramadan; Dhio Pratama Wiransyah; Satria Ramadhani; Rayya Ramadhan Simangunsong; Ken Dhita Tania; Alsella Meiriza; Ahmad Rifai
Building of Informatics, Technology and Science (BITS) Vol 7 No 4 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i4.9512

Abstract

Armed conflict can have significant impacts on the social and economic conditions of a region, particularly on poverty levels and inflation. This study aims to analyze the impact of conflict on key economic indicators using a Knowledge Management System (KMS) approach and to compare the performance of clustering algorithms in identifying underlying data patterns. The research applies clustering analysis by comparing K-Means, DBSCAN, and Hierarchical Clustering algorithms to group data based on similarities in economic characteristics. The dataset used in this study consists of several indicators, including poverty levels before and during conflict, extreme poverty rates, inflation rates, GDP changes, and currency devaluation. Data preprocessing techniques such as normalization are applied to ensure comparability among variables. The evaluation of clustering performance is conducted using Silhouette Score and Davies–Bouldin Index to determine the most effective algorithm. The results show that clustering methods are able to identify distinct grouping patterns of regions based on the level of conflict impact on economic conditions. Among the evaluated algorithms, DBSCAN demonstrates superior performance in handling complex and uneven data distributions. The analysis also indicates a consistent tendency for poverty and inflation to increase during periods of conflict, highlighting the economic vulnerability of affected regions. Furthermore, the integration of clustering results into a Knowledge Management System enables the transformation of analytical outputs into structured knowledge that can support data-driven decision making. These findings are expected to contribute to the development of more effective economic policies and analytical frameworks in conflict-affected areas.
Co-Authors Ahmad Rifai Dhio Pratama Wiransyah Ken Dhita Tania M Raykah Alam Ramadan Oktadini, Nabila Rizky Pacu Putra Putri Eka Sevtiyuni Rayya Ramadhan Simangunsong Rugaiyah Balqis Satria Ramadhani