ANALISIS PERBANDINGAN ALGORITMA CLASSIFICATION UNTUK AUTHENTICATION UANG KERTAS (STUDI KASUS: BANKNOTE AUTHENTICATION)

Khairul Sani, Wing Wahyu Winarno, Silmi Fauziati

Abstract


Uang merupakan alat transaksi yang digunakan untuk proses pertukaran barang dan jasa. Peredaran uang palsu dari tahun ke tahun terus mengalami peningkatan. Hal tersebut dikarenakan mudahnya mendapatkan informasi cara membuat uang palsu di internet, ditunjang dengan perkembangan teknologi yang sangat cepat, serta kemajuan digital image processing sehingga susah untuk mengenali mata uang asli atau palsu.  Untuk membedakan mata uang asli dan palsu maka penelitian ini akan menganalisis authentication uang kertas, dengan menggunakan beberapa algoritma classification. Tahapannya dimulai dari pengambilan data, kemudian proses recognition banknote yang terdiri dari proses image acquisition, gray scale conversion, sampai ke tahap classification. Selanjutnya tahap pengujian classification yaitu menggunakan WEKA appliaction tool dengan menerapkan metode cross validation pada data banknote authentication. Dari hasil pengujian yang dilakukan, bahwa algorithm tree C4.5 memiliki nilai classified instance yang paling tinggi yaitu sebesar 98.54 % dibanding dengan algorithm naive bayes dan neural network

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DOI: http://dx.doi.org/10.26555/jifo.v10i1.a3344

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