Implementasi Sistem Data Mining Untuk Menentukan Stock Accuracy Pada Warehouse PT Coca-Cola Amatil Indonesia Cibitung–Plant
DOI:
https://doi.org/10.30865/mib.v4i1.1795Keywords:
Kata Kunci, Data Mining, Stock Opname, Warehouse.Abstract
Abstract−Data Mining is a process of extracting data or filtering data that utilizes large data sets through a series of processes to obtain information that stands out from the data. PT. Coca-Cola Amatil Indonesia Cibitung-Plant has one of the largest warehouse in Indonesia exactly warehouse mega distribution center (DC). With ±32000 m2 warehouse area or equivalent to ±30000 Pallets. To maintain the accuracy of the stock in the warehouse of course required a good system in order to support the operational activities in the warehouse, one way to maintain the accuracy of stock in the warehouse is to do the overall product calculation in the warehouse (Stock Opname), in order to know the accuracy data in the system with the physical stock in the warehouse. With the data transactions stored in the database, sometimes the transaction data is only on leave to accumulate without any further action, then make the information system that manages the data to dig information by data mining techniques.
References
Agus Ristono, (2013), Manajemen Keuangan Teori dan Aplikasi, Edisi 4. BPFE- Yogyakarta.
Elmasari, Ramez and Shamknat B. Navathe, (2012), Fundamentals of Database Systems, Third Edition, Addison Wesley Publishing Company, New York.
Han, Jiawei, (2014), Data Mining : Concepts and Techniques, Department of Computer Science University of Illinois at Urbana-Champaign.
Jindal, Rajni, and Taneja, Shweta , (2012), Comparative Study of Data Warehouse Design Approaches: A Survey.
Jogiyanto Bukunya Yakub, (2012), Pengantar Sistem Informasi, Graha Ilmu, Yogyakarta.
Kadir, Abdul, (2013), Pengenalan Sistem Informasi, Andi, Yogyakarta.
Manari, J. I, (2013), Perancangan Basis Data Perusahaan Distribusi dengan Menggunakan Oracle, e-journal.
Moh. Nazir Ph D, (2014), Metode Penelitian, Ghalia Indonesia, Bogor.
Rainardi, Vincent, (2013), Building a Data Warehouse with Examples in SQL Server, Springer, New York.
R. Ramakrishnan and J. Gehrke, (2007), Database Management System, McGraw Hill Higher Education, USA.
Santoso, Budi, (2007), Data Mining Teknik Pemanfaatan Data Untuk Keperluan Bisnis, Graha Ilmu, Yogyakarta.
S, Rosa A. dan M.Shalahudin, (2013), Rekayasa Perangkat Terstrtuktur Dan Berorientasi Objek, Informatika, Bandung.
Witten, I. H and Frank, E, (2011), Data Mining: Practical Machine Learning Tool and Techniques Second Edition,Morgan Kauffman:San Francisco.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment 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 acknowledgment 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 (Refer to The Effect of Open Access).