Student Data Visualization of Metro City Using Google Looker Studio
DOI:
https://doi.org/10.35870/ijsecs.v5i2.4396Keywords:
Student Enrollment Analysis, Gender Distribution Patterns, Educational Data Visualization, Google Looker Studio, Evidence-Based Educational PolicyAbstract
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.
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References
Hartama, D. (2018). Analisa visualisasi data akademik menggunakan Tableau big data. Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika), 3, 46-55.
Tupari, T., Abdullah, S., & Chairani, C. (2023). Visualisasi data analisa sentimen RUU omnibus law kesehatan menggunakan KNN dengan software RapidMiner. Jurnal Informatika: Jurnal Pengembangan IT, 8(3), 261-268. https://doi.org/10.30591/jpit.v8i3.5641
Cendana, W. P., & Silmina, E. P. (2022, March). Visualization of COVID-19 data in Yogyakarta City using Data Studio. In Conference Senatik STT Adisutjipto Yogyakarta (Vol. 7, pp. 189-200). https://doi.org/10.28989/senatik.v7i1.444
Saputri, T. A., Muharni, S., Perdana, A., & Sulistiyanto, S. (2021). Pemanfaatan Google Data Studio untuk visualisasi data bagi kepala gudang UD Salim Abadi. Ilmu Komputer Untuk Masyarakat, 2(2), 67-72. https://doi.org/10.33096/ilkomas.v2i2.1067
Nisa, N., Firdaus, D., & Aprilia, R. (2023). Implementasi business intelligence untuk menganalisis jumlah guru SD SMP SMA SMK di Jawa Barat. Simpatik: Jurnal Sistem Informasi dan Informatika, 3(1), 11-16. https://doi.org/10.31294/simpatik.v3i1.1725
Saputra, M. A. R., Febriawan, D., & Hasan, F. N. (2023). Penerapan business intelligence untuk menganalisis data kasus Covid-19 di Provinsi Jawa Barat menggunakan platform Google Data Studio. Jurnal Ilmiah Komputasi, 22(2), 187-196. https://doi.org/10.32409/jikstik.22.2.3362
Puteri, S. R. (2022). Analisis visualisasi data Kecamatan Kertapati menggunakan Tableau Public. JUPITER: Jurnal Penelitian Ilmu dan Teknologi Komputer, 14(2-b), 366-373. https://doi.org/10.5281/jupiter.2022.10
Bahtiar, I. R., Nur, M. A., & Marzuq, A. (2022). Peningkatan kompetensi pembuatan dan visualisasi data bagi tenaga kependidikan. BERNAS: Jurnal Pengabdian Kepada Masyarakat, 3(1), 22-32. https://doi.org/10.31949/jb.v3i1.1692
Gunawan, A., Iskandar, A., & Purba, O. S. M. (2023). Rancang bangun business intelligence untuk memantau purna TKI pada BNP2TKI. Jurnal Ilmiah Komputasi, 22(1), 41-48. https://doi.org/10.32409/jikstik.22.1.3325
Tumini, & Minatania, A. (2023). Visualisasi data Covid19 tahun 2021 di Jawa Barat menggunakan Google Data Studio. Jurnal Informasi dan Komputer, 11(01), 44-51.
Sulistiyanto, S., Saprudin, U., Sari, E. G., & Ikhsanto, M. N. (2023). Ujian kompetensi keahlian sebagai penilaian kesiapan siswa memasuki dunia kerja di SMKN 3 Metro. SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan, 7(2), 979-983.
Dendodi, D., Simarona, N., Elpin, A., Bahari, Y., & Warneri, W. (2024). Analisis penerapan augmented reality dalam meningkatkan efektifitas pembelajaran sains di era digital. Alacrity Journal of Education, 293-304. https://doi.org/10.52121/alacrity.v4i3.456
Romero, C., & Ventura, S. (2020). Educational data mining and learning analytics: An updated survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(3). https://doi.org/10.1002/widm.1355
Taylor, L., Gupta, V., & Jung, K. (2024). Leveraging visualization and machine learning techniques in education: A case study of k-12 state assessment data. Multimodal Technologies and Interaction, 8(4), 28. https://doi.org/10.3390/mti8040028
Yuan, Y., Xu, H., Krishnamurthy, M., & Vijayakumar, P. (2024). Visualization analysis of educational data statistics based on big data mining. Journal of Computational Methods in Sciences and Engineering, 24(3), 1785-1793. https://doi.org/10.3233/jcm-230003
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