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All Journal Majalah Ilmiah Teknologi Elektro Jurnal Sains dan Teknologi CESS (Journal of Computer Engineering, System and Science) Sistemasi: Jurnal Sistem Informasi Jurnal Ilmiah Teknologi Informasi Asia Jurnal Pilar Nusa Mandiri Jurnal Teknologi Informasi dan Komputer SINTECH (Science and Information Technology) Journal Matrik : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer jurnal teknik informatika dan sistem informasi International Journal of Engineering and Emerging Technology INSERT: Information System and Emerging Technology Journal Prosiding SNAST Jurnal Krisnadana Jurnal Krisnadana Jurnal aplikasi IPTEK
I Gusti Ayu Agung Diatri Indradewi
Universitas Pendidikan Ganesha
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences

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Journal : Prosiding SNAST

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METODE LVQ BERBASIS PARAMETER HSV UNTUK PENENTUAN UANG RUPIAH PALSU I Gusti Ayu Agung Diatri Indradewi; Made Suci Ariantini
PROSIDING SNAST Prosiding SNAST 2018
Publisher : IST AKPRIND Yogyakarta

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Abstract

The government has socialized the 3D method (Visible, Feeling, and Diterawang) to prevent people from accidentally transacting using counterfeit money. In addition to this method, counterfeit money scanners that use ultraviolet light are also commonly used. However, the use of methods or scanners must be accompanied by a human eye to determine whether the money is genuine or false. Along with the development of technology, the technique of making counterfeit money will also develop so that supporting techniques are needed that can be used to help identify counterfeit money automatically. In this study, the data used is only original and fake banknotes with a nominal value of Rp. 100,000.00. Image acquisition is done with the help of a digital camera and a light source from ultraviolet lights. Pre-processing in the form of pruning on the image of banknotes produces an image measuring 210 × 64 pixels. The feature extraction stage is done by changing the RGB image value to the HSV color space. The HSV value of the image is then used as an input vector on the LVQ network to determine the authenticity of the banknote image. The method test used for 100 real money images and 80 fake images yields the best performance when the learning level α (0) = 0,1 in epoch = 4 with an MSE value of 0,088889. Classification with the best accuracy occurs when the rate of learning α (0) = 0,1 in epoch = 1 with the level of truth classification is 87,2%.
Co-Authors Adnyana, I Ketut Widhi I Gde Prayoga Wibawa I Gede Mahendra Darmawiguna I Kadek Andika Putra I Kadek Wahyu Dananjaya I ketut Gede Darma Putra I Ketut Resika Arthana I Md. Dendi Maysanjaya I Putu Agung Bayupati Kadek Wawan Cahyadi Komang Pramayasa Laurensia Anjelina Tutosili Arakian Made Diah Arista Devi Made Suci Ariantini Ni Luh Pangestu Widya Sari Ni Luh Wiwik Sri Rahayu Ginantra Ni Putu Sri Mulyani Ni Wayan Wardani Putu Yudia Pratiwi Saraswati, Ni Wayan Sumartini Wardani, Ni Wayan Wayan Gede Suka Parwita