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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Informatics and Communication Technology (IJ-ICT) Bulletin of Electrical Engineering and Informatics Journal of Applied Science, Engineering, Technology, and Education Jurnal Teknik Informatika (JUTIF) JINAV: Journal of Information and Visualization Quantitative Economics and Management Studies ARRUS Journal of Mathematics and Applied Science ARRUS Journal of Engineering and Technology Applied Engineering and Technology Journal of Fuzzy Systems and Control (JFSC) Journal of Future Artificial Intelligence and Technologies
Ojugo, Arnold Adimabua
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Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Physics Other

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Journal : ARRUS Journal of Engineering and Technology

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Quest For Convergence Solution Using Hybrid Genetic Algorithm Trained Neural Network Model For Metamorphic Malware Detection Ojugo, Arnold Adimabua; Obruche, Chris Obaro; Eboka, Andrew Okonji
ARRUS Journal of Engineering and Technology Vol. 2 No. 1 (2022)
Publisher : Lembaga Penelitian dan Pengembangan Teknologi dan Rekayasa, Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/jetech613

Abstract

An unstable economy is rife with fraud. Perpetrated on customers, it ranges from employees’ internal abuse to large fraud via high-value contracts cum control breaches that impose serious consequences to biz. Loyal employees may not perpetrate fraud if not for societal pressures and economic recession with its rationalization that they have bills to pay and children to feed. Thus, the need for financial institutions to embark on effective measures via schemes that will aids both fraud prevention and detection. Study proposes genetic algorithm trained neural net model to accurately classify credit card transactions. Compared, model used a rule-based system to provide it with start-up solution and it has a fraud catching rate of 91% with a consequent, false alarm rate of 9%. Its convergence time is found to depend on how close the initial solution space is to the fitness function, and for recombination and mutation rates applied.
Co-Authors Abdullahi, Mustapha Barau Achmad Nuruddin Safriandono Adigwe, Wilfred Afotanwo, Anderson Agboi, Joy Aghaunor, Tabitha Chukwudi Aghware, Fidelis Obukohwo Ajib Susanto Akazue, Maureen Ifeanyi Akhmad Dahlan Ako, Rita Erhovwo Ashioba, Nwanze Chukwudi Binitie, Amaka Patience Budi Widjajanto De Rosal Ignatius Moses Setiadi Dian Kristiawan Nugroho Eboka, Andrew Okonji Edim, Edim Bassey Efetobore Edje, Abel Ejeh, Patrick Ogholorunwalomi Ejeh, Patrick Ogholuwarami Emordi, Frances Uche Emordi, Frances Uchechukwu Ezzeh, Peace Oguguo Farah Zakiyah Rahmanti Gan, Hong-Seng Geteloma, Victor Ochuko Ibor, Ayei Egu Idama, Rebecca Okeoghene Ifeanyi Akazue, Maureen Iwan Setiawan Wibisono Jumbo, Evans Fubara Max-Egba, Asuobite ThankGod Muhamada, Keny Muslikh, Ahmad Rofiqul Niemogha, Star Umiyemeromesu Nwankwo, Obinna Nwozor, Blessing Uche Obruche, Chris Obaro Odiakaoase, Christopher Chukwufunaya Odiakaose , Christopher Chukwufunaya Odiakaose, Christopher Chukufunaya Odiakaose, Christopher Chukwufunaya Odiakaose, Chukwufunaya Chris Odoh, Anne Ojei, Emmanuel Obiajulu Okpako, Ejaita Abugor Okpor, Margaret Dumebi Okpor, Margareth Dumebi Onochie, Christopher Chukwudi Onoma, Paul Avweresuo Onoma, Paul Avweresuoghene Onoma, Paul Avwerosuoghene Onyemenem, Innocent Sunny Orobor, Anderson Ise Otakore, Oghenevwede Debby Oweimieotu, Amanda Enaodona Stefanus Santosa Sudibyo, Usman Syahroni Wahyu Iriananda, Syahroni Wahyu Taylor, Onate Egerton Ugbotu, Eferhire Valentine Yoro, Rume Elizabeth Zuama, Leygian Reyhan