Application of Association Rule Mining to Analyze Factors Affecting Student Evaluation Results in Ikat Weaving Subjects

Abstract

Ikat weaving is a hereditary cultural practice that possesses significant market value. However, many young people currently perceive ikat weaving as a profession suited for those who lack formal education, leading to a reluctance to engage in fabric weaving. SMA Negeri 1 Kambera has taken proactive steps by incorporating ikat weaving into the school curriculum. This initiative faces various challenges, including differences in family backgrounds, levels of interest, and proficiency in the Sumba language, all of which can potentially impact students' understanding and learning outcomes. At present, the relationship between these factors and student evaluation results is seldom analyzed. Therefore, this study aims to identify patterns in the factors influencing student evaluation outcomes in ikat weaving subjects by employing Association Rule Mining to analyze the relationships among variables such as family background, gender, ethnicity, student interests, and Sumba language skills. The analysis, conducted with a support threshold of 0.3 and a confidence level of 0.6, revealed that factors such as learning interest, gender, and family background have a strong association with evaluation performance. Female students tend to exhibit higher interest and achieve better evaluation results, while students from non-weaving families generally fall into the category of satisfactory grades. Nevertheless, non-weavers still have the potential to attain good grades if they belong to the Sumba tribe and possess proficiency in the Sumbanese language.