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All Journal Annual Research Seminar PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer
Junia Kurniati
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Computer Science & IT

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IDENTIFIKASI TANDA TANGAN MENGGUNAKAN TRANSFORMASI GABOR WAVELET DAN JARAK MINKOWSKI Junia Kurniati
Annual Research Seminar (ARS) Vol 2, No 1 (2016)
Publisher : Annual Research Seminar (ARS)

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Abstract

Tanda tangan memiliki beberapa kesulitan untuk di lakukan identifikasi yang disebabkan karena banyaknya variasi tanda tangan yang diperlukan terhadap tanda tangan orang yang sama, hal ini memiliki kecenderungan perubahan berdasarkan posisi, ukuran, dan kemiringan. Tanda tangan yang akan di identifikasi akan diambil terlebih dahulu ciri-cirinya dengan melakukan proses ekstraksi ciri. Salah satu metode ekstraksi ciri adalah Transformasi Gabor Wavelet (TGW). TGW mampu mendeskripsikan variasi citra tanda tangan menjadi beberapa nilai ekstraksi ciri berdasarkan orientasi dan scale. Untuk itu, dikembangkan perangkat lunak untuk mengekstraksi ciri citra tanda tangan dengan metode TGW serta melakukan identifikasi tanda tangan  menggunakan jarak Minkowski. Hasil percobaan memperlihatkan bahwa metode TGW mendapatkan hasil yang baik pada proses ekstraksi ciri, dengan persentase hasil pengujian identifikasi tanda tangan untuk data uji terhadap data latih adalah sebesar 81% yaitu menggunakan jarak Minkowski parameter 2, 74% untuk jarak Minkowski parameter 4, dan 74% untuk jarak Minkowski parameter 6. 
Pengembangan Representasi Pengetahuan Ontologi Domain Bidang Ilmu Informatika Rodiah, Desty; Kanda Januar Miraswan; Junia Kurniati; Dellin Irawan; Vanya Terra Ardiani
Jurnal PROCESSOR Vol 19 No 2 (2024): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2024.19.2.1905

Abstract

Research in computer science, which often involves complex issues, frequently encompasses multiple sub-disciplines. The more research that applies multiple sub-disciplines, it becomes challanging to categorize the appropriate branches of knowledge related to the research. Therefore, a knowledge representation is needed to accurately depict these fields of study. This research develops an ontology that serves as a knowledge representation for computer science, comprising four sub-disciplines: graphics and visualization, natural language processing, distributed systems, and data science and pattern recognition.The ontology development is based on the grouping references from the Association for Computing Machinery (ACM). Using the Protégé software version 5.5.0, the development resulted in a matrix with 3,584 axioms, 837 logical axioms, 794 classes, and 1 equivalent class. Once the ontology was successfully developed, it underwent testing through query examinations, with four specific queries for each sub-discipline. The query testing utilized a filter based on keywords input by the user. The keywords used were graphics, words, security, and patterns. The ontology successfully provided answers based on the exploration of relationships between subclasses within the ontology.
Co-Authors Dellin Irawan Desty Rodiah Kanda Januar Miraswan Vanya Terra Ardiani