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All Journal Buletin PSP CIVED (Journal of Civil Engineering and Vocational Education) Jurnal Bisnis, Manajemen, dan Informatika Hasanuddin Journal of Applied Business and Entrepreneurship Jurnal Hukum Respublica Jurnal Golden Age JOURNAL OF SCIENCE AND SOCIAL RESEARCH Majalah Kedokteran Andalas EARLY CHILDHOOD : JURNAL PENDIDIKAN Raudhatul Athfal: Jurnal Pendidikan Islam Anak Usia Dini Jurnal Ekonomi dan Kebijakan Publik Indonesia OSEANA Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Qathrun Jurnal Keilmuan dan Pendidikan Islam Jurnal Teknik Mesin Sinergi Manajemen Kreatif Jurnal Al Hikmah: Indonesian Journal of Early Childhood Islamic Education Teknofile, Jurnal Sistem Informasi REKADATA (Rekayasa Data dan Kecerdasan Artifisial)
Fahmi Fahmi
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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DATA ENGINEERING AND VISUALIZATION OF STUDENT ACADEMIC PERFORMANCE USING BUSINESS INTELLIGENCE TOOLS Fahmi Fahmi
REKADATA Vol. 1 No. 1 (2025): Rekayasa Data dan Kecerdasan Artifisial (REKADATA)
Publisher : CV Mazaya Cahaya Utama

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Abstract

The rapid growth of data in higher education institutions has created challenges in managing, analyzing, and interpreting student academic performance information. Academic data such as course grades, attendance, and assessment results are often scattered across multiple sources, making it difficult for decision-makers to gain comprehensive insights. This study presents the development of a data engineering and visualization framework designed to process and present student academic performance using business intelligence (BI) tools. The methodology involves several stages: data acquisition from academic information systems, data cleaning and transformation through a structured pipeline, and integration into a centralized database. Visualization was carried out using BI tools to generate interactive dashboards that provide multi-dimensional analysis of student achievement. The results demonstrate that the developed framework successfully consolidated student performance data into a single repository, enabling efficient analysis and visualization. Key performance indicators such as GPA trends, course completion rates, and subject-specific weaknesses were visualized in real time. These visualizations support lecturers, academic administrators, and students in identifying performance patterns, predicting potential risks, and formulating appropriate interventions. The novelty of this research lies in the combination of data engineering processes with user-friendly BI dashboards tailored for the education sector in Indonesia. In conclusion, the proposed system enhances transparency, accessibility, and decision-making in academic performance monitoring. It highlights the importance of integrating data engineering and visualization techniques in higher education, providing a foundation for more advanced analytics such as predictive modeling and personalized learning recommendations.
VISUALISASI DATA PENJUALAN HARIAN PRODUK FASHION E-COMMERCE MENGGUNAKAN POWER BI rahmat saputra rahmat; fahmi fahmi
TEKNOFILE : Jurnal Sistem Informasi Vol. 4 No. 2 (2026): Februari 2026
Publisher : PT. ZIVANA CENDEKIAWAN BANGSA

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Abstract

Pesatnya perkembangan e-commerce di sektor fashion telah menghasilkan data transaksi yang besar dan kompleks, sehingga diperlukan pengelolaan dan analisis data yang efektif guna mendukung pengambilan keputusan bisnis. Penelitian ini bertujuan untuk membangun sistem visualisasi data penjualan harian produk fashion e-commerce berbasis Power BI. Metode yang digunakan adalah pendekatan kuantitatif dengan tahapan ETL (Extract, Transform, Load) untuk membersihkan dan menyiapkan data sebelum divisualisasikan dalam bentuk dashboard interaktif. Hasil penelitian menunjukkan bahwa Power BI mampu menyajikan visualisasi data yang komprehensif dan real-time, meliputi tren penjualan, kategori produk terlaris, distribusi pembelian berdasarkan gender, serta pendapatan berdasarkan lokasi cabang. Insight yang diperoleh di antaranya adalah dominasi penjualan oleh kategori Electronics, tren penurunan kepuasan pelanggan selama triwulan pertama 2023, serta kontribusi signifikan konsumen wanita dalam transaksi. Temuan ini membuktikan bahwa penggunaan Power BI dapat meningkatkan efisiensi operasional, mempercepat proses analisis, serta memperkuat strategi bisnis berbasis data dalam industri fashion e-commerce.
Co-Authors Abd. Karim M Abubakar Hamzah Adi Purwandana Amelia Nur Safitri Harahap Amroeni Drajat Anwiri Chairunnisa Arthur Halik Razak Asril Zahari Atin Fatimah Dadhan Harusda Dewi Harmoni Dewi Sartika Diah Ayu Lestari Endang Winarti Faza Karimatul Akhlak Fis Purwangka Hasan Bakti Nasution Imtitsalul Kamilah Az-zahroh Johar, Olivia Anggie Jusni Jusni Luluk Asmawat Luluk Asmawati Mohd. Nur Syechalad Muhammad Ali Prima Zola rahmat saputra rahmat Riefki Dwi Putra Syaharuddin Rasyid Tilmidah Fauziah Yetti Yetti