Optimasi Model Data Warehouse Menggunakan Skema Bintang untuk Mendukung Analisis Multidimensi Kredit Usaha Rakyat Syariah
DOI:
https://doi.org/10.52436/1.jpti.1405Keywords:
Analisis Multidimensi, Big Data, Data Warehouse, ETL, Kredit Usaha Rakyat Syariah, Star SchemaAbstract
Sistem Informasi Kredit Program (SIKP) pada akhir 2024 menanggung beban 592.294 data debitur dan 1.220.833 data akad Kredit Usaha Rakyat (KUR) Syariah. Beban ini menurunkan performa query (kueri), menghambat kebutuhan rekapitulasi mendesak, dan menimbulkan inkonsistensi karena ekstraksi manual tanpa timestamp (penanda waktu). Penelitian ini bertujuan mengoptimasi model data warehouse berbasis star schema (skema bintang) agar kinerja kueri meningkat, kualitas data terjaga, dan tersedianya analisis multidimensi untuk pemantauan kinerja pembiayaan serta penilaian risiko. Perancangan dilakukan dengan satu tabel fakta utama beserta dimensi waktu, wilayah, jenis pembiayaan, dan kategori debitur. Data historis diproses melalui ETL (Extract, Transform, Load) sebelum dianalisis dengan OLAP (Pemrosesan Analitik Daring) guna mendukung agregasi lintas hierarki. Ruang lingkup pengujian mencakup kueri rekapitulasi agregat menurut waktu, wilayah, jenis pembiayaan, dan kategori debitur dengan menggunakan data historis SIKP tahun 2023 dan 2024. Pengujian menunjukkan percepatan eksekusi kueri hingga 85% dibandingkan skema operasional awal, disertai peningkatan konsistensi pelaporan dan sifat yang fleksibel untuk pemutaran perspektif analitis. Secara praktis, rancangan ini menyediakan pelaporan strategis yang cepat tanpa mengorbankan kestabilan operasional penerimaan transaksi SIKP. Secara teoretis, hasilnya menguatkan posisi star schema sebagai arsitektur yang relevan untuk big data dan analitik keuangan syariah.
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