Klasifikasi Data Tidak Lengkap Dengan Pendekatan Fuzzy Grid Partition

Murni Marbun; Erwin Panggabean; Ricky Martin Ginting; Robertus Rinaldi Pakpahan

doi:10.31294/ji.v8i2.10703

Klasifikasi Data Tidak Lengkap Dengan Pendekatan Fuzzy Grid Partition

Murni Marbun, Erwin Panggabean, Ricky Martin Ginting, Robertus Rinaldi Pakpahan

Abstract

Klasifikasi data tidak lengkap dapat di proses langsung dengan cara tertentu untuk mendapatkan aturannya atau diperoleh dari pengetahuan para pakar. Ketergantungan terhadap pakar akan sulit memodelkan implikasi logis manusianya, tidak tersedianya framework proses pemodelan, dan biaya pakar yang mahal. Kesulitan tersebut dapat diatasi dengan mendapatkan aturan dari data yang bersifat uncertain dengan menerapkan metode dari sistem fuzzy yang dibangun berdasarkan konsep fuzzy if-then rules. Pendekatan metode pada penelitian ini adalah metode fuzzy grid partition untuk mengklasifikasikan data tidak lengkap. Data yang digunakan adalah data cuaca yang terdiri data kelembaban udara sebagai konklusi, data temperatur, curah hujan, lamanya penyinaran matahari dan kecepatan angin sebagai anteseden. Tahapan penelitian dimulai dengan menginput data set tidak lengkap, merubah data tidak lengkap menjadi data lengkap, menormalisasi data, membangkitkan aturan dan melakukan proses klasifikasi data. Hasil penelitian menghasilkan 22 aturan untuk mengklasifikasi data dengan tingkat akurasi 66,67%, tingkat error 33,33% dan jumlah data unclass adalah 0

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DOI: https://doi.org/10.31294/ji.v8i2.10703