Rancang Bangun Data Warehouse Dan Dashboard Pada Produktivitas Komoditas Kedelai Di Jawa Timur Menggunakan Metode Kimball

Patria, Andika Insan (2026) Rancang Bangun Data Warehouse Dan Dashboard Pada Produktivitas Komoditas Kedelai Di Jawa Timur Menggunakan Metode Kimball. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Sumber utama protein nabati yang paling digemari oleh masyarakat, kedelai, mengalami peningkatan jumlah konsumsi yang tinggi namun tidak diikuti dengan peningkatan produksi kedelai lokal. Data terkait budidaya kedelai seperti luas lahan, luas panen, hasil produksi, kebutuhan kedelai, harga pasar, dan harga pupuk telah tersedia di Dinas Pertanian dan Ketahanan Pangan Jawa Timur namun masih dilakukan pencatatan menggunakan format yang beragam dan belum terintegrasi. Kondisi ini menyulitkan analisis produktivitas dan pemantauan harga komoditas kedelai secara cepat dan konsisten. Penelitian ini bertujuan untuk menerapkan data warehouse dan dashboard Business Intelligence yang sesuai dengan Metode Kimball sebagai Business Intelligence (BI) untuk mendukung pengambilan keputusan terkait komoditas kedelai di Jawa Timur. Metodologi yang digunakan adalah identifikasi permasalahan dan kebutuhan informasi, perancangan model menggunakan Nine Step Kimball Method, pengembangan proses Extract–Transform–Load (ETL) menggunakan Apache Airflow, serta pembangunan dashboard web interaktif. Arsitektur data warehouse dan pipeline ETL telah berhasil mengintegrasikan data terkait komoditas tingkat kabupaten/kota di Jawa Timur. Data telah berhasil divisualisasikan melalui dashboard yang menampilkan informasi visual seperti perbandingan luas lahan, volume produksi, dan kondisi harga kedelai di Jawa Timur. Berdasarkan hasil User Acceptance Testing (UAT), sistem yang dikembangkan terbukti telah memenuhi kebutuhan informasi para pemangku kepentingan di Dinas Pertanian dan Ketahanan Pangan Jawa Timur. Dashboard ini secara efektif dapat membantu mendukung keputusan strategis dalam perencanaan budidaya komoditas kedelai.
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The most consumed source of vegetable protein, soybeans, has a significant increase in consumption, but this has not been accompanied by an increase in local soybean production. Data related to soybean cultivation, such as land area, harvested area, production yield, soybean demand, market price, and fertilizer price, are available at Dinas Pertanian dan Ketahanan Pangan Jawa Timur, but are still recorded using various formats and are not yet integrated. This condition makes it difficult to analyze productivity and monitor soybean prices quickly and consistently. This study aims to implement a data warehouse and Business Intelligence dashboard in accordance with the Kimball Method as a Business Intelligence (BI) to support decision-making related to soybean commodities in East Java. The methodology used is identification of problems and information needs, model design using the Nine Step Kimball Method, development of the Extract–Transform–Load (ETL) using Apache Airflow, and the construction of an interactive web dashboard. The data warehouse architecture and ETL pipeline have successfully integrated data related to commodities at the district/city level in East Java. The data has been successfully visualized through a dashboard that displays visual information such as a comparison of land area, production volume, and soybean price conditions in East Java. Based on User Acceptance Testing (UAT), the developed system has proven to meet the information needed by the stakeholders at the Dinas Pertanian dan Ketahanan Pangan Jawa Timur. This dashboard can be used as a support in decision making in planning soybean cultivation.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Business Intelligence, Data Warehouse, Kimball Method, Soybean, Kedelai, Metode Kimball
Subjects:	T Technology > T Technology (General) > T57.5 Data Processing
Divisions:	Faculty of Information Technology > Information System > 57201-(S1) Undergraduate Thesis
Depositing User:	Andika Insan Patria
Date Deposited:	01 Aug 2026 06:53
Last Modified:	01 Aug 2026 06:53
URI:	http://repository.its.ac.id/id/eprint/141094

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