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Journal : International Journal of Information System and Innovative Technology

Design of Mobile-Based Samosir Tour Hero Tourism Application Silitonga, Agnes Irene
International Journal of Information System and Innovative Technology Vol. 4 No. 1 (2025): June
Publisher : Geviva Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63322/stcja626

Abstract

Samosir Tour Hero is an innovative platform designed to help tourists who want to explore Samosir Island easily, integrated, and informatively. The application offers detailed information on vehicle rentals, accommodations, and tourist destinations, and serves as a direct link between tourists and experienced local tour guides. With advanced features such as searching for nearby tourist locations, customized tour packages, and user reviews and recommendations, Samosir Tour Hero provides a comprehensive solution to enhance the tourist experience. The application has significant potential to boost the local economy, support tour guide activities, and strengthen the tourism sector in Samosir. With a user-friendly approach, simple yet effective interface design, and integration of transportation, accommodation, and tour guide services, Samosir Tour Hero aims to create a more personalized, comfortable, and memorable travel experience.
A Data Mining Approach to Clustering Cases of Violence Against Children in Indonesia Agnes Irene Silitonga; Silitonga, Agnes Irene
International Journal of Information System and Innovative Technology Vol. 4 No. 2 (2025): December
Publisher : Geviva Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63322/tc9nng05

Abstract

Violence against children in Indonesia remains a crucial issue that requires a data-driven approach for more targeted interventions. This study aims to cluster provinces in Indonesia based on the number of cases of violence and the types of violence committed, namely physical, psychological, and sexual violence. The method used in this study is the K-Means Clustering algorithm, an unsupervised learning technique in data mining that is able to find hidden patterns in large data sets. Data was obtained from the Ministry of Women's Empowerment and Child Protection's Gender and Child Information System (SIGA), which covers 38 provinces. The clustering results produced three main groups: a cluster with high levels of violence consisting of the provinces of North Sumatra, DKI Jakarta, West Java, Central Java, and East Java; a cluster with moderate levels of violence consisting of 16 provinces; and a cluster with low levels of violence covering 17 provinces. These findings are expected to form the basis for the development of evidence-based child protection policies geographically and thematically.
A Data Mining Approach to Clustering Cases of Violence Against Children in Indonesia Agnes Irene Silitonga; Silitonga, Agnes Irene
International Journal of Information System and Innovative Technology Vol. 4 No. 2 (2025): December
Publisher : Geviva Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63322/tc9nng05

Abstract

Violence against children in Indonesia remains a crucial issue that requires a data-driven approach for more targeted interventions. This study aims to cluster provinces in Indonesia based on the number of cases of violence and the types of violence committed, namely physical, psychological, and sexual violence. The method used in this study is the K-Means Clustering algorithm, an unsupervised learning technique in data mining that is able to find hidden patterns in large data sets. Data was obtained from the Ministry of Women's Empowerment and Child Protection's Gender and Child Information System (SIGA), which covers 38 provinces. The clustering results produced three main groups: a cluster with high levels of violence consisting of the provinces of North Sumatra, DKI Jakarta, West Java, Central Java, and East Java; a cluster with moderate levels of violence consisting of 16 provinces; and a cluster with low levels of violence covering 17 provinces. These findings are expected to form the basis for the development of evidence-based child protection policies geographically and thematically.