Article Per Year (5 Year)
p-Index From 2021 - 2026
1.554
P-Index
This Author published in this journals
All Journal DINAMIKA DOTCOM TEKNOLOGI INFORMASI SENTIA 2015 Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) UTAMAX : Journal of Ultimate Research and Trends in Education Jurnal Pengabdian Polinema Kepada Masyarakat Indonesian Journal of English Teaching Jurnal Teknik Ilmu dan Aplikasi Jurnal Informatika Polinema (JIP) International Journal of Integrated Science and Technology Jurnal Nasional Teknologi Informasi dan Aplikasinya
Banni Satria Andoko
Politeknik Negeri Malang
Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Social Sciences Other

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : international journal of integrated science and technology

 1 
Comparative Analysis of Convolutional Neural Network (CNN) Architectures in Classification of Cattle and Pig Rambaks Haryono, Haryono; Rahmad, Cahya; Andoko, Banni Satria
International Journal of Integrated Science and Technology Vol. 2 No. 5 (2024): May 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i5.1793

Abstract

Rambak crackers are one of the food ingredients that have the characteristics of expansion and crispy texture. The general public often faces difficulties in distinguishing between pork and beef rambak crackers that have been processed, so it is important to rely on technology, especially artificial intelligence (AI), to help distinguish between them. This study was conducted to compare the capabilities of several CNN architectures in classifying images of pork and beef rambak crackers. The results of the study showed that the Xception architecture had the highest accuracy rate in classifying pork and beef rambak crackers, with an average accuracy rate of 98.24%.
Co-Authors Abdurrasyid Muhasibi Andre Asmara, Rossa Anisa Taufika Firdausi Annisa Taufika Firdausi Annisa Taufika Firdausi Aris Alfian Atiqah Nurul Asri Batubulan, Kadek Suarjuna Chairandy, Ranno Putra Chandra Sina Putra Deddy Kusbianto P.A Dharma Yudistira Eka Putra Dian Hanifudin Subhi Eka Larasati Amalia Evy Sophia Hapsari, Indri Tri Haryono Haryono Hersandi Anjar Susanto Hilmy, Naufal Farras Hirashima, Tsukasa Indri Tri Hapsari Kusbianto P.A, Deddy M. Danang Mirza Zainurachman Nasrul Firdaus Naufal Farras Hilmy Nurudin Santoso Putra Prima Arhandi, Putra Prima Putra, Chandra Sina Rahmad, Cahya Ranno Putra Chairandy Ridwan Rismanto Rifqie Muhammad Riris Silvia Zahri Rosa Andrie Asmara Santoso, Nurudin Shoumi, Milyun Ni’ma Subhi, Dian Hanafudin Susanto, Hersandi Anjar Usman Nurhasan Vivin Ayu Lestari Wafiuddin, Naufal Falah Wang, Xia Zahri, Riris Silvia Zainurachman, M. Danang Mirza