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All Journal IJIIS: International Journal of Informatics and Information Systems International Journal for Applied Information Management
Ulfah, Siti Zayyana
Unknown Affiliation
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Social Sciences

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Clustering Students Based on Academic Performance and Social Factors: An Unsupervised Learning Approach to Identify Student Patterns Rahma, Felinda; Ulfah, Siti Zayyana
International Journal for Applied Information Management Vol. 5 No. 3 (2025): Regular Issue: September 2025
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijaim.v5i3.109

Abstract

This study explores the application of K-Means clustering, an unsupervised learning method, to group students based on academic performance and social factors. The primary objective is to uncover hidden patterns among students by analyzing academic scores in mathematics, reading, and writing, as well as demographic attributes including gender, ethnicity, parental education level, and lunch type. Data preprocessing steps, such as normalization and one-hot encoding, were conducted to prepare the dataset for clustering. The optimal number of clusters was determined using the Elbow Method and Silhouette Score, with K=3 selected for its balance between cluster quality and interpretability. The clustering results revealed three distinct groups of students: low performers, average performers, and high performers. These clusters were visualized using PCA and t-SNE, which showed clear separation and internal consistency. Interpretation of the clusters suggests that social factors may influence academic outcomes, with students from disadvantaged backgrounds more likely to fall into the lower-performing group. The study highlights the importance of data-driven approaches in understanding student diversity and designing targeted interventions. Furthermore, this research underlines the potential of clustering techniques to inform educational strategies by identifying students' needs more precisely. However, limitations include reliance on academic and basic demographic variables, and sensitivity of the K-Means algorithm to outliers and the predefined number of clusters. Future research should incorporate additional factors such as emotional well-being and learning preferences to develop more comprehensive educational models. Overall, the study demonstrates that clustering can serve as a valuable tool for enhancing the effectiveness and equity of educational programs
Examining Risk and Trust in Student Mobile Banking Adoption: An Extended Technology Acceptance Model Perspective Rahma, Felinda Aprilia; Ulfah, Siti Zayyana
International Journal of Informatics and Information Systems Vol 8, No 2: March 2025
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v8i2.261

Abstract

This study examines the influence of trust, compatibility, satisfaction, perceived risk, and risk acceptance on students’ intention to use mobile banking applications. As mobile banking becomes increasingly popular for its convenience and efficiency, especially among tech-savvy youth, understanding the behavioral factors influencing adoption is crucial. Utilizing an extended Technology Acceptance Model (TAM), this study employs a quantitative approach with multiple linear regression analysis. The dataset, comprising responses from 219 Indonesian university students, was drawn from the "cogent_adoption_m_banking_pls" survey. The results reveal that satisfaction, compatibility, and trust significantly influence students’ intention to use mobile banking, while perceived risk and risk acceptance do not show a significant effect. The model explains approximately 57% of the variance in adoption intention (R² = 0.570), indicating substantial explanatory power. These findings offer valuable insights for mobile banking developers and financial institutions to enhance user satisfaction, align services with user lifestyles, and strengthen trust—key factors for increasing adoption among student users.
Co-Authors Rahma, Felinda Rahma, Felinda Aprilia