The Implementation of Data Warehouse and Star Schema for Optimizing Property Business Decision Making

Authors

  • Willsen Wijaya Universitas Multimedia Nusantara, Indonesia
  • Jansen Wiratama Universitas Multimedia Nusantara, Indonesia
  • Santo Fernandi Wijaya Universitas Multimedia Nusantara, Indonesia

DOI:

https://doi.org/10.33379/gtech.v8i2.4091

Keywords:

Data Warehouse, ETL, Pentaho Data Integration, Property Industry, Star Schema

Abstract

The property industry is a sector that faces intense competition, so innovation is needed to plan business strategies. PT Wijaya Karya Realty faces several problems, such as determining strategic locations for its property products, such as houses or shophouses, and comparing the price of company houses with the market price of homes in specific locations. To answer these needs, it is necessary to implement a data warehouse and Extract, Transform, Load (ETL). In this research, Pentaho Data Integration (PDI) is used as a tool for managing and cleaning data that can be used as analysis material to assist in data-based decision-making. Apart from that, Mondrian can be used through the workbench scheme to improve data analysis effectively. Designing a star schema that includes a dimensional table and fact table can help optimize the analysis process better. The implementation of a data warehouse allows companies to make in-depth decisions based on critical variables. The research results show that the implementation of Star Schema can provide information for companies in decision-making and business strategy planning in the property sector.

References

Awiti, J., Vaisman, A., & Zimányi, E. (2019). From Conceptual to Logical ETL Design Using BPMN and Relational Algebra. In C. Ordonez, I.-Y. Song, G. Anderst-Kotsis, A. M. Tjoa, & I. Khalil (Eds.), Big Data Analytics and Knowledge Discovery (pp. 299–309). Springer International Publishing.

Awiti, J., Vaisman, A., & Zimányi, E. (2020). Design and implementation of ETL processes using BPMN and relational algebra. Data Knowl. Eng., 129, 101837. https://doi.org/10.1016/j.datak.2020.101837

Effendy, M. R., Kusumasari, T. F., & Hasibuan, M. A. (2019). Star Schema Implementation For Monitoring in Data Quality Management Tool (A Case Study at A Government Agency). 2019 Fourth International Conference on Informatics and Computing (ICIC), 1–6. https://doi.org/10.1109/ICIC47613.2019.8985695

Hahn, S. M. L. (2019). Analysis of Existing Concepts of Optimization of ETL-Processes. In R. Silhavy (Ed.), Software Engineering Methods in Intelligent Algorithms (pp. 62–76). Springer International Publishing.

Handika, I. P. S., Tama, G. B. A., & Krisnayanti, N. P. M. (2020). Penerapan Teknologi Datawarehouse Nosql Dan Business Intelligence Untuk Analisa Transaksi Penjualan. Jurnal RESISTOR (Rekayasa Sistem Komputer), 3(2), 120–127. https://doi.org/10.31598/jurnalresistor.v3i2.626

Haryono, E. M., Fahmi, Tri W, A. S., Gunawan, I., Nizar Hidayanto, A., & Rahardja, U. (2020). Comparison of the E-LT vs ETL Method in Data Warehouse Implementation: A Qualitative Study. 2020 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), 115–120. https://doi.org/10.1109/ICIMCIS51567.2020.9354284

Jayashree, G., & Priya, C. (2019). Design of visibility for order lifecycle using datawarehouse. International Journal of Engineering and Advanced Technology, 8(6), 4700–4707. https://doi.org/10.35940/ijeat.F9171.088619

Kannapadang, D., & Ta’dung, Y. L. (2022). Faktor-Faktor Yang Mempengaruhi Perubahan Laba Pada PT. Wijaya Karya Bangunan Gedung Tbk. Yang Terdaftar Di Bursa Efek Indonesia. Fair Value: Jurnal Ilmiah Akuntansi Dan Keuangan, 5(5), 2376–2382. https://doi.org/10.32670/fairvalue.v5i5.2763

Mathur, S., Bali, V., Gupta, S. L., & Pahwa, P. (2019). Data warehouse testing and security: A conspectus. International Journal of Innovative Technology and Exploring Engineering, 8(9 Special Issue), 843–850. https://doi.org/10.35940/ijitee.I1136.0789S19

Paliwal, M., & Saraswat, P. (2022). Approaches of Data Warehousing and Their Applications: a Review. International Journal of Innovative Research in Computer Science & Technology, 1, 117–121. https://doi.org/10.55524/ijircst.2022.10.1.21

Pratama, I. P. A. E., & Widhiasih, N. P. N. D. (2020). Perancangan Data Warehouse Untuk Prediksi Penjualan Pada Orba Express Menggunakan Pentaho. JUSS (Jurnal Sains Dan Sistem Informasi), 3(2), 43–48. https://doi.org/10.22437/juss.v3i2.8147

Setiadi, T. F., & Rahutomo, R. (2022). A Data Warehouse Schema for Monitoring Regional COVID-19 Case Registration. 2022 International Conference on Information Management and Technology (ICIMTech), 144–148. https://doi.org/10.1109/ICIMTech55957.2022.9915222

Setiawan, J., Gousander, V., & Prasetiawan, I. (2023). Unmasking the Sentiments of Labuan Bajo: An Instagram-based Analysis for Tourism Insights through VADER Sentiment Analysis. G-Tech: Jurnal Teknologi Terapan, 7(3), 967–976. https://doi.org/10.33379/gtech.v7i3.2615

Zahra, F., Wardhani, D., & Wiratama, J. (n.d.). Improving the Quality of Service : ETL Implementation on Data Warehouse at Pharmacy Industry. 18(1), 1–14.

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Published

2024-04-18

How to Cite

The Implementation of Data Warehouse and Star Schema for Optimizing Property Business Decision Making. (2024). G-Tech: Jurnal Teknologi Terapan, 8(2), 1242-1250. https://doi.org/10.33379/gtech.v8i2.4091

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