Analysis of the Application of the K-Means Algorithm to the Clustering Method Approach for Grouping Consumer Purchasing Trends at One of the Textile Companies
DOI:
https://doi.org/10.58344/jws.v3i6.601Keywords:
Clustering, K-Means Algorithm, Data Mining, Consumer Purchasing Trends, Textile Industry, Business StrategyAbstract
In Indonesia, the regulation of sexual abuse crimes is a critical aspect of ensuring justice and protection for victims. However, challenges remain in the effectiveness and comprehensiveness of these regulations. This study aims to analyze and evaluate the current legal framework addressing sexual abuse in Indonesia, identifying gaps and proposing improvements to enhance legal protections for victims. The research employs a qualitative approach, utilizing legal analysis and case studies to assess the application of existing laws. Data collection involves reviewing legal documents, court cases, and expert interviews to gather comprehensive insights into the regulatory landscape. The findings indicate significant shortcomings in the legal framework, including inconsistencies in legal definitions, procedural delays, and inadequate victim support mechanisms. The study discusses the implications of these findings, emphasizing the need for a more cohesive and victim-centered approach in legal reforms. This research underscores the necessity for legislative improvements to address the identified gaps in the regulation of sexual abuse crimes. Recommendations include clearer legal definitions, expedited legal processes, and enhanced victim support services. These measures are essential for ensuring justice and effective protection for victims of sexual abuse in Indonesia.
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