ANALISIS JARINGAN SYARAF TIRUAN UNTUK KLASIFIKASI KASUS KEKERASAN TERHADAP PEREMPUAN DEWASA MENGGUNAKAN ALGORITMA LEARNING VECTOR QUANTIZATION (LVQ) - Selfina Agustin; Wanayumini (Smart Education, 2026)
Violence against adult women is a social problem that still frequently occurs in Indonesia and shows an increase every year. Available data on violence cases are still in the form of raw data, making it difficult to use to determine the level of vulnerability in each region. Therefore, a method is needed that can process this data into more meaningful information through a classification process. This study aims to classify the level of violence against adult women in Indonesia using the Learning Vector Quantization (LVQ) algorithm. This data uses seven attributes, namely physical violence, psychological violence, sexual violence, exploitation, human trafficking, neglect, and others. The classification process is carried out into three classes, namely high, medium, and low. The test results show that the first data for the Aceh Province region is classified into class 1 (high) with a distance value of 111.7157645406. The second data for the North Sumatra Province region is also classified into class 1 (high) with a value of 114.41286640237. Meanwhile, the 3rd data for the West Sumatra Province region is classified into class 3 (low) with a value of 104.51753457. The results of the study indicate that the Learning Vector Quantization (LVQ) algorithm is able to group data on cases of violence against adult women based on their level of vulnerability so that it can be used as supporting information in decision-making and policy formulation for handling cases of violence against women.