Pengembangan Algoritma Apriori Untuk Pengambil Keputusan

Penulis

  • Lismardiana Lismardiana Program S2 Teknik Informatika, Fakultas Ilmu Komputer dan Teknologi Informasi Universitas Sumatera Utara
  • Herman Mawengkang Program S2 Teknik Informatika, Fakultas Ilmu Komputer dan Teknologi Informasi Universitas Sumatera Utara
  • Erna Budhiarti Nababan

Kata Kunci:

Develovment Apriori, FP-Growth, Asosiasi Rule Mining, Frequent Item/itemset

Abstrak

Algoritma Apriori salah satu algoritma data mining dalam pembentukan asosiasi rule mining. Algoritma apriori adalah proses ekstraksi informasi dari suatu database, dilanjutkan dengan melakukan frequent item/itemset dan candidate generation dalam pembentukan asosiasi rule mining guna mendapatkan hasil nilai minimum support dan hasil nilai minimum confidence. Pada database yang cukup besar, algoritma apriori banyak menghasilkan pattern frequent item/itemset (pola sering muncul suatu item/itemset) yang banyak, karena harus melakukan candidate generation serta merekam database secara berulang-ulang. Dengan ini penulis berkeinginan mengembangkan algoritma apriori dengan melakukan penelitian  tentang bagaimana meminimalkan frequent item/itemset pada apriori, tanpa melakukan candidate generation sehingga mempercepat tahapan penyelesaian pencarian asosiasi rule mining. Untuk solusi meminimalkan  frequent item/itemset pada algoritma apriori, maka penulis  menggunakan metode FP-Growth,dari hasil penelitian yang dilakukan dengan menggunakan dataset 1000 records pada TransactionID-Sales , pada apriori mulai dari k2, dihasil sebanyak 101 frequent  item/itemset, sementara pada FP-Growth k2 sebanyak 40 frequent  item/itemset. Dari  jumlah hasil  frequent item/itemset dapat disimpulkan bahwa dengan metode FP-Growth mampu meminimalkan jumlah frequent item/itemset pada algoritma apriori dan lebih efesien dari segi waktu, juga  tahap penyelesaian lebih cepat, lebih terperinci dalam memaparkan hasil frequent item/itemset karena hasil frequent yang bernilai 1 masih diperhitungkan

Referensi

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(https://support.spatialkey.com/spatialkey-sample-csv-data/ data sales di download pada tanggal 18 Juni 2015 pukul 22.45 WIB)

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Unduhan

Diterbitkan

2016-12-13

Terbitan

Vol 4 No 2 (2015): Jurnal Teknologi Informasi dan Komunikasi (TIK)

Bagian

Artikel

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