Published: 2025-08-01
Student Data Visualization of Metro City Using Google Looker Studio
DOI: 10.35870/ijsecs.v5i2.4396
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Abstract
Metro City educational landscape encompasses over 50,000 students across multiple institutional levels, yet systematic enrollment pattern analysis remains underdeveloped. Gender disparities and uneven institutional distribution challenge educational planners seeking evidence-based policy solutions. Our research examined student enrollment data from Metro City Education Department for the 2025/2026 academic year, focusing on gender balance and institutional representation across KB, TK, SD, SMP, SMA, SMK, and SLB schools. Using descriptive quantitative methodology, we processed secondary data through spreadsheet applications before implementing Google Looker Studio visualization. The platform transformed numerical datasets into interactive dashboards featuring bar charts, pie diagrams, and filterable tables accessible to non-technical stakeholders. Analysis revealed unexpected findings challenging conventional gender imbalance assumptions. Rather than anticipated male dominance, data showed near-equal gender distribution (55% male, 45% female) across 64 institutions serving 14,298 students. However, enrollment concentration became apparent when SMP Muhammadiyah Ahmad Dahlan Metro accounted for 50% of total student population, potentially skewing statistical interpretation. Educational staff demographics differed significantly, with female educators outnumbering males 2:1, suggesting professional preference rather than access barriers. Google Looker Studio demonstrated practical effectiveness for real-time data processing, enabling rapid information retrieval and policy formulation support. Research limitations include single-year scope without longitudinal analysis or socio-economic variables. Future investigations should incorporate historical perspectives and predictive modeling. The visualization platform successfully addressed research objectives, providing Metro City education leadership with actionable insights for policy development and resource allocation strategies.
Keywords
Student Enrollment Analysis ; Gender Distribution Patterns ; Educational Data Visualization ; Google Looker Studio ; Evidence-Based Educational Policy
Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 5 No. 2 (2025)
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Section: Articles
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Published: %750 %e, %2025
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License: CC BY 4.0
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Copyright: © 2025 Authors
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DOI: 10.35870/ijsecs.v5i2.4396
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Galih Putra Pamungkas
Informatics Engineering Study Program, Faculty of Technology, Business and Science, Universitas Dharma Wacana Metro, Metro City, Lampung Province, Indonesia
Usep Saprudin
Informatics Engineering Study Program, Faculty of Technology, Business and Science, Universitas Dharma Wacana Metro, Metro City, Lampung Province, Indonesia
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