Data Mining Prediction of Oil Palm Fruit

  • ANISYA ANISYA INSTITUT TEKNOLOGI PADANG
Keywords: Data Mining, Association Rule, Palm Fruit

Abstract

The development of information technology today is very meaningful for all circles. Currently, information technology has become a necessity in everyday life. The use of information technology is proven to facilitate human performance. Where the number of suppliers that supply palm oil fruit every year will affect the activities of companies engaged in palm oil production. So that currently the company needs a decision-making strategy in the procurement of oil palm fruit. Data mining is a technology that is very useful to help companies find very important information from data centers. Data mining predicts trends and characteristics of business behavior which are very useful to support important decision making. One of the techniques the writer uses is the Association Rule technique. Association Rule is a data mining technique to find association rules between item combinations. Using the Association Rule technique will help companies predict which suppliers will supply palm fruit in the following year. Meanwhile, to predict the load does not use the association rule method but uses existing data analysis.

References

[1] Sutrisno, Dkk (2013), Penerapan Data Mining Pada Penjualan Menggunakan Metode Clustering Study Kasus PT.Indomarco Palembang.

[2] Nurjoko, Darmawan Abdi, (2015), Penerapan Data Mining Menggunakan Association

[3] Bahrur Roji (2013), Penerapan Metode Association Rule Mining (ARM) Untuk Memprediksi Rencana Penambahan Stok Pupuk Berdasarkan Kebiasaan Pelanggan (Studi Kasus: CV. Tani Makmur Jaya).

[4] Gunadi Goldie, Dkk (2012), Penerapan Metode Data Mining Market Basket Analysis Terhadap Data Penjualan Produk Buku Dengan Menggunakan Algoritma Apriori Dan Frequent Pattern Growth (Fp-Growth) : Studi Kasus Percetakkan PT.Gramedia.

[5] Nurdin dan astika dewi, (2015), Penerapan Data Mining Untuk Menganalisis Penjualan Barang Dengan Menggunakan Metode Apriori Pada Supermarket Sejahtera Lhokseumawe.

[6] Tumpubolon Kannedi, Dkk (2013), Implementasi Data Mining Algoritma Apriori Pada Sistem Persediaan Alat – Alat Kesehatan.

[7] Asa Verano Dwi, (2016), Assosiasi Rules Dan Moving Average Untuk Memprediksi Persediaan Bahan Buku Produksi.

[8] Widodo Prabowo Pudjo, Dkk. 2013. Penerapan data mining dengan matlab. Bandung : Penerbit Pasar Buku Palasari.

[9] Fathansyah. 2012. Basis Data. Bandung: Penerbit Informatika Bandung.
Published
2021-04-30