Implementasi Data Mining Untuk Menentukan Persediaan Stok Pakan Kucing Menggunakan K-Means Clustering (Studi Kasus : Suterakoi)
Keywords:
Data Mining, K means Clustering, Persedian StokAbstract
Suterakoi is a company located in the Silk World. The company sells quality cat food specifically to meet the nutritional and health needs of cats. Currently the process of managing cat feed stocks in the Suterakoi warehouse continues to use conventional methods, this often leads to an inconsistency between the amount of stock available and the actual amount. Because of the lack of accurate reports on the goods sold and the availability of stocks of cat feed in the warehouse, this has resulted in a written cat feed stock report that does not correspond to the amount of cat food stock in the storehouse. This could affect customer demand for cat feed stock produced by Suterakoi. The author did a research to build a system that could help the company predict stocks of cat feed in the warehouse. For this situation, the creators run the information mining application using the K-Means Grouping strategy. This strategy is used to gather information into groups based on commonalities. by classifying stocks based on certain attributes such as product type, price, or demand needs. The author designed a web-based Data Mining application using PHP and MySQL programming languages as data storage. Hopefully this study can improve accuracy in predicting cat feed stocks.
References
Afiasari, Nur, Nana Suarna, and Nining Rahaningsi. 2023. “Implementasi Data Mining Transaksi Penjualan Menggunakan Algoritma Clustering Dengan Metode K-Means.” Jurnal SAINTEKOM 13 (1): 100–110. https://doi.org/10.33020/saintekom.v13i1.402.
Andryana, Septi, Eri Mardiani, Universitas Nasional, and Data Mining. 2021. “Implementasi Data Mining Untuk Menentukan Persediaan Stok Obat Di Enok Menggunakan Metode K-Means Clustering 1,2,3” 8 (3): 1294–1306.
Annisa Siti Habibah, Arip Solehudin, & Aji Primajaya. 2022. “Analisis Persediaan Stok Barang Warung Menggunakan Data Mining Dengan Algoritma Fp-Growth (Studi Kasus: Warung Bu Nani).” Jurnal Ilmiah Wahana Pendidikan 8 (17): 46–58. https://jurnal.peneliti.net/index.php/JIWP%0AAnalisis.
Zafira, Fara, Bambang Irawan, and Agus Bahtiar. 2024. “PENERAPAN DATA MINING UNTUK ESTIMASI STOK BARANG DENGAN METODE K-MEANS CLUSTERING” 8 (1): 156–61.
Febriyanti, L., & Zakaria, H. (2023). Implementasi Data Mining Untuk Memprediksi Produktivitas Pada Tanaman Kacang Tanah Menggunakan Metode Naive Bayes:(Studi Kasus: Perkebunan Kacang Tanah Di Kota Bogor). LOGIC: Jurnal Ilmu Komputer dan Pendidikan, 1(2), 105-118.
Muhammad, R., & Zakaria, H. (2023). Penerapan Algoritma K-Means dalam Penentuan Siswa Bermasalah Berdasarkan Running Record (Studi Kasus: SMK Averus Jakarta). JRIIN: Jurnal Riset Informatika Dan Inovasi, 1(7).
Indriani, Diana, Bambang Irawan, Agus Bahtiar, and K-means Clustering. 2024. “PENERAPAN ALGORITMA K-MEANS CLUSTERING UNTUK MENENTUKAN PERSEDIAAN STOK BARANG” 8 (1): 182–87.
Prastiwi, Hani, Jeny Pricilia, and Errissya Rasywir. 2022. “Implementasi Data Mining Untuk Menentuksn Persediaan Stok Barang Di Mini Market Menggunakan Metode K-Means Clustering.” Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) 2 (1): 141–48. https://doi.org/10.33998/jakakom.2022.2.1.34.
