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Application of Cluster Analysis and Correlation between Mathematics and Natural Sciences Subject Based on Student Test Scores Using K-Means Clustering Pangesti, Sekar; Roslan, Nurul Farisah Binti; Andreansyah
Indonesian Journal of Applied Mathematics and Statistics Vol. 2 No. 1 (2025): Indonesian Journal of Applied Mathematics and Statistics (IdJAMS)
Publisher : Lembaga Penelitian dan Pengembangan Matematika dan Statistika Terapan Indonesia, PT Anugrah Teknologi Kecerdasan Buatan PT Anugrah Teknologi Kecerdasan Buatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71385/idjams.v2i1.8

Abstract

Educational unit examinations are a means of supporting decisions to determine students' abilities in mastering all the material that has been taught. education unit examinations also have an impact on students' ability to continue to the next level of education, besides that they can also improve the quality of school education. Based on the background of the problem, this researcher aims to group learning outcomes for mathematics and natural sciences subjects based on educational unit exam scores using the k-means clustering algorithm, in addition to finding out the relationship between mathematics and natural sciences subject learning outcomes using Spearman rank correlation analysis. The population in this study was all 39 students in class IX of SMP Plus Berkualitas Lengkong Mandiri for the 2023/2024 academic year. The sample in this study used saturated sampling. The research results show that through clustering using the k-means clustering algorithm, it was found that cluster 1 with the high category had 21 students, cluster 2 with the medium category had 12 students and cluster 3 with the low category had 6 students. Based on the Spearman rank correlation analysis of the entire sample, a low correlation was obtained between mathematics results and natural sciences results based on educational unit exam scores of 0.608 and a coefficient of determination of 36.9%. Meanwhile, the Spearman rank correlation test on all cluster 1 samples showed a moderate relationship between mathematics learning outcomes and natural sciences subject learning outcomes of 49.5%.
Multiple Exponential Regression Modeling of Dengue Haemorrhagic Fever Factors in West Java Province, Indonesia Ridhatusalma, Ghina; Diandra, Salsabila Putri; Rahma, Hasna Nabilah; Pangastuti, Sinta Septi; Roslan, Nurul Farisah Binti
Indonesian Journal of Applied Mathematics and Statistics Vol. 1 No. 1 (2024): Indonesian Journal of Applied Mathematics and Statistics (IdJAMS)
Publisher : Lembaga Penelitian dan Pengembangan Matematika dan Statistika Terapan Indonesia, PT Anugrah Teknologi Kecerdasan Buatan PT Anugrah Teknologi Kecerdasan Buatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71385/idjams.v1i1.12

Abstract

Dengue Haemorrhagic Fever is a major public health problem in Indonesia, with 103,509 cases of Dengue Haemorrhagic Fever recorded in Indonesia until the end year of 2020 with 725 deaths with the case fatality rate of 0.70%, and an incidence rate of 38.15 per 100,000 population. The aim of this research is to determine the multiple exponential regression model for the number of Dengue Haemorrhagic Fever cases and its factors in the West Java Province, Indonesia, at the time period of 2020. This research uses secondary data sourced from Open Data Jabar and Badan Pusat Statistik in the form of the number of the Dengue Haemorrhagic Fever cases in each regency or city throughout the West Java, with the independent variables; the number of poverty rate, the number of healthcare workforces, population density, and number of households with adequate sanitation. The final model from the multiple exponential regression shows that population density has a significant effect on the number of Dengue Haemorrhagic Fever cases in the West Java Province.