Analisa Kategori Barang dengan Penjualan Terbanyak dalam Jangka Waktu 3 Bulan Menggunakan Data Warehouse

Authors

  • I Putu Agus Eka Pratama Prodi Teknologi Informasi, Fakultas Teknik, Universitas Udayana
  • Rey Bernard Universitas Udayana, Jimbaran, Indonesia

DOI:

https://doi.org/10.31961/eltikom.v6i1.457

Keywords:

Data Warehouse, ETL, Multi Dimensional Data, Pentaho Data Integration, Tableau

Abstract

UD. Makmur Sejahtera as one of the largest distributors of daily necessities in Manokwari Papua has sales transaction data for each category of goods and types of goods. These data are still physically stored in the form of notes and have not been digitized so that they can be utilized optimally to help UD. Makmur Sejahtera increases sales. This research has the basic idea of using digital sales transaction data to find out which categories of goods have the most sales in a period of three months (July 2020 to September 2020) through the Extraction, Transformation, Loading (ETL) process based on Pentaho Data Integration, to then be stored in multi-dimensional data forms, categorized, and visualized using Tableau. The test results show that rice commodity is the category of goods with the most sales in a period of three months and the implementation of the Data Warehouse is very helpful for UD. Makmur Sejahtera in achieving its business goals.

Downloads

Download data is not yet available.

References

I.P.A.E. Pratama, Handbook Data Warehouse. Informatika. 2018, hal. 20-30.
Widianty, "Data Warehouse Design With Kimball Method: Case Study of Farhenheit Manufacturing Systems," Jurnal ComTech, Vol. 6 No. 4, pp. 604-612, 2015.
S. Pratama, R. Priambodo, "Data Warehouse Menggunakan Algoritma Naive Bayes Untuk Menunjang Analisis Divisi Marketing di Perusahaan Multifinance," Jurnal Cendikia, Vol. XVII, pp. 272-280, 2019.
M. Akbar, Y. Rahmanto, "Desain Data Warehouse Penjualan Menggunakan Nine Step Methodology Untuk Business Intelligency," Jurnal Informatika dan Rekayasa Perangkat Lunak (JATIKA), Vol. 1, No. 2, pp.137-146, 2020.
I.P.A.E. Pratama, I.G.A. Pradipta, "Desain dan Implementasi Data Warehouse Untuk Prediksi Penjualan Produk Pada Toko Mekarsari,” Jurnal Teknologi Informatika dan Terapan, Vol. 05, No 01, 2018.
D. Subuh, W. Yasman, "Implementasi Data Warehouse dan Penerapannya Pada Toko Magnifique Clothes Dengan Menggunakan Tools Pentaho," Seminar Nasional Inovasi dan Aplikasi Teknologi di Industri, 2019.
I. Sadam, A.U. Hamdani, "Perancangan Model Data Warehouse Untuk Mengetahui Kinerja Layanan Jasa Pengiriman Barang Studi Kasus: XYZ," IDEALIS Indonesia Journal of Information System, Vol. 2, No. 4, 2019.
A.F. Hardiyanti, D.D. Ramadha, A.M. Khosasih, Sudirmansyah, "Perancangan Sistem Penerimaan Mahasiswa Baru Pada Universitas Pamulang Menggunakan Data Warehouse Online Analytical Processing (OLAP)," Jurnal Ilmiah Fakultas Ilmu Komputer, Vol. 8, No. 2, 2019.
I.M.S. Putra, D.K.T.A. Putra, "Rancang Bangun Engine ETL Data Warehouse dengan Menggunakan Bahasa Python," Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), Vol.3, No. 2, pp.113–123, 2019.
R. Riksazany, M. Ayub, "Eksplorasi Data Warehouse Penjualan dengan Tableau," Jurnal STRATEGI, Vol.1, No. 2, 2019.
R.Susanto, T. Harihayati, "Pemodelan Data Warehouse Distribusi Produk di PT. X," Jurnal Insentif, Vol. 3, No. 2, 2019.
R.T. Yunandar, Amir, K. Rizal, "Perancangan Data Warehouse Untuk Informasi Strategi Studi Kasus Penerimaan Siswa Baru STIE Binaniaga Bogor," Jurnal Teknik Komputer AMIK BSI, Vol.VI, No.1, 2020.
M.A.A. Maulana, Maskur, W. Soeharso, "Analisis dan perancangan data warehouse evaluasi mahasiswa studi kasus pada jurusan Teknik Informatika UMM," Jurnal Repositor, Vol.1, No.1, 2019.
R. Ferianto, A. Nugroho, T. Andriyanto, "Data Warehouse Pengelolahan Data Penjualan Studi Kasus UD HF Bersaudara," Proseding Seminar Nasional Inovasi Teknologi UN PGRI Kediri, 2021.
A.F. Azizah, R.A. Hendrawan, R.A. Vinarti, "Pembuatan Data Warehouse Penjualan Produk dan Penerapan Dalam Studi Kasus Divisi Greenscope Energy PT. Tustika Nagata Surabaya," Jurnal Teknik POMITS, Vol. 1, No. 1, 2012, pp. 1-5.
Pentaho. Pentaho Data Integration User Guide: Open Source Business Intelligence. Pentaho. 2018.
Hitachi Inspire the Next. "Pentaho Data Integration." help.pentaho.com [online] Available: https://help.pentaho.com/Documentation/7.1/0D0/Pentaho_Data_Integration [Accessed: 18 Agustus 2020].
Tableau. "Enterprise Data Warehouse Visualization: The Visual Approach to Business Intelligence." tableau.com [online] Available: https://www.tableau.com/whitepapers/enterprise-data-warehouse-business-intelligence [Accessed: 20 Agustus 2020].
R. Wijaya, B. Pudjoatmodjo, "Penerapan Extraction-Transformation-Loading (ETL) Dalam Data Warehouse (Studi Kasus: Departemen Pertanian)," Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI), Vol.5, No.2, 2016.
V. Loren, Y.F. Soleman, B. Berlinton, "Analisis dan Perancangan Online Analytical Processing Sebagai Business Intelligence Pada Sekolah Musik Cantata," Jurnal Informatika dan Bisnis, Vol.6, No.1, 2017.
B.K. Easterita, I. Arwani, D.E. Ratnawati, "Pengembangan Data Warehouse dan Online Analytical Processing (OLAP) Untuk Analisis Data Artikel Pada Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)," Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI), Vol.1, No.1, 2020

Downloads

Published

15-05-2022

How to Cite

[1]
Eka Pratama, I.P.A. and Bernard, R. 2022. Analisa Kategori Barang dengan Penjualan Terbanyak dalam Jangka Waktu 3 Bulan Menggunakan Data Warehouse. Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer. 6, 1 (May 2022), 65–78. DOI:https://doi.org/10.31961/eltikom.v6i1.457.

Issue

Vol. 6 No. 1 (2022)

Section

Articles

License

Copyright (c) 2022 Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer

Creative Commons License

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.