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All Journal Media Statistika World Psychology
Mastika, Mastika
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Decision Sciences, Operations Research & Management Education Social Sciences Other

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The Relationship Between Parental Involvement and Students’ Academic Achievement in Rural Areas Jumiyah, Rahmi; Yulita, Ona; Mastika, Mastika; Ningsih, Nuristi; Khairani, Juhesmi; Siregar, Ripa Hannum
World Psychology Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/wp.v4i1.802

Abstract

Parental involvement has long been recognized as a crucial factor in enhancing students’ academic achievement. However, its impact in rural areas, where access to educational resources and parental education levels may differ significantly from urban settings, remains underexplored. This study examines the relationship between parental involvement and students’ academic performance in rural areas, aiming to identify specific parental behaviors that influence academic success in these communities. A mixed-methods approach was employed, combining quantitative surveys with qualitative interviews. The survey, conducted with 200 parents and 200 students from rural schools, measured levels of parental involvement across various domains, including homework support, communication with teachers, and participation in school activities. Academic achievement was assessed using students’ GPA scores. The results indicated a strong positive correlation between parental involvement and students’ academic performance, with homework support and teacher communication emerging as the most significant factors. Qualitative data revealed that parents’ limited educational backgrounds and work schedules posed challenges to involvement, yet many expressed a commitment to supporting their children’s education. The study concludes that increasing parental engagement in rural areas can significantly improve students’ academic outcomes. Interventions aimed at providing support and resources for parents in these areas are essential for fostering better educational environments.
COMPARISON OF MISSING VALUE IMPUTATION USING MEAN, BAYESIAN KNN, AND NON-BAYESIAN KNN ON TEP GENE EXPRESSION DATA Mastika, Mastika; Siswantining, Titin; Bustamam, Alhadi
MEDIA STATISTIKA Vol 18, No 1 (2025): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.18.1.61-72

Abstract

Analysis of gene expression data, particularly in cancer data, often faces challenges due to the presence of missing values. One approach to overcome this is data imputation. This study evaluates the performance of three imputation methods, namely mean imputation, K-Nearest Neighbors (KNN), and KNN with Bayesian optimization using Gaussian Process modeling, on Tumor Educated Platelets (TEP) gene expression data. Missing values were introduced using Missing Completely at Random (MCAR) gradually at levels of 5%, 10%, 15%, and up to 60%, and performance was evaluated using three metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), and Normalized Root Mean Squared Error (NRMSE). The results show that the three methods produce relatively similar performance, with differences in MAE, MSE, and NRMSE values only at a small decimal scale. Although Bayesian Optimization is expected to improve the accuracy of KNN, the resulting improvement on this dataset is not significant. These findings indicate that simple imputation such as the average and KNN-based methods still provide competitive results on TEP data with data characteristics that have 14,020,496 zeros out of a total of 16,512,496 existing values, which is approximately 84.91% of the total data.
Co-Authors Bustamam, Alhadi Jumiyah, Rahmi Khairani, Juhesmi Ningsih, Nuristi Siregar, Ripa Hannum Siswantining, Titin Yulita, Ona