Implementation of Data Mining for Finished Goods Warehouse Relayout Using the Apriori Method: A Case Study of Oyster Mushroom Cultivation in Mulyosari Penelitian ilmiah
Main Article Content
Abstract
Every manufacturing industry should have supporting facilities and infrastructure for its business continuity. Infrastructure is very important and is part of the final placement of the production process is storage warehouses, storage can be temporary or long-term depending on the needs of the company. Problems that often occur in warehouses are generally the placement of finished goods that are still not well organized so that a lot of time and effort needed by the pic rack in the activity of preparing the goods to be sent because the location of the goods requested to be sent simultaneously the location is still far away. Based on the above problems the author intends to conduct research to provide alternative thinking to the company by conducting data testing with a priori algorithm to obtain new information on the layout of goods more effectively. From the calculation results that have been done can be concluded that the most frequent transactions simultaneously with a minimum support of 40% and a minimum confidence of 80% are 4 items namely COVER ADF SUB C, COVER PAPER GUIDE ASF, PAPER GUIDE DUPLEX LOWER (MASUO) and PAPER GUIDE UPPER ADF. From the test results above, a new combination model has been formed so that the pic rack can change the old layout with the new one.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with Positif : Jurnal Sistem dan Teknologi Informasi agree to the following terms:
- 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.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
S. S. Efrataditama, A. Vidha; Wigati, “Perancangan Tata Letak Gudang Dengan Metode Dedicated Storage Di Toko Listrik Anugrah Jaya,” Semin. Nas. IENACO – 2016, no. 03, pp. 276–351, 2016.
L. I. Prahartiwi and W. Dari, “Algoritma Apriori untuk Pencarian Frequent itemset dalam Association Rule Mining,” PIKSEL Penelit. Ilmu Komput. Sist. Embed. Log., vol. 7, no. 2, pp. 143–152, 2019, doi: 10.33558/piksel.v7i2.1817.
Ulvah, “Implementasi Algoritma Apriori Aturan Keterkaitan Data Untuk Analisa Keranjang Belanja Sistem Persediaan Obat Pada Apotek Perdos Farma Makassar,” J. Instek (Informatika Sains dan Teknol., vol. 3, no. 2, pp. 231–240, 2018.
S. Nur, “METODOLOGI PENELITIAN Disertai Dengan Contoh Penerapannya Dalam Penelitian.” p. 210, 2018.
M. Fauzy, K. R. Saleh W, and I. Asror, “Penerapan Metode Association Rule Menggunakan Algoritma Apriori pada Simulasi Prediksi Hujan Wilayah Kota Bandung,” J. Ilm. Teknol. Inf. Terap., vol. II, no. 2, pp. 221–227, 2016.
A. W. O. Gama, I. K. G. D. Putra, and I. P. A. Bayupati, “Menemukan Frequent Itemset Dalam,” Tekonologi Elektro, vol. 15, no. 2, pp. 27–32, 2016.