Article Per Year (5 Year)
p-Index From 2021 - 2026
1.704
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Sosial dan Ilmu Politik Jurnal EECCIS Jurnal Computech & Bisnis (e-Journal) Jurnal Ilmu Sosial dan Ilmu Politik Buffer Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Warta Penelitian Perhubungan Jurnal Manajemen Informatika Jurnal Penelitian Transportasi Laut JATI (Jurnal Mahasiswa Teknik Informatika) Frontier Energy System and Power Engineering Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) JURNAL ILMIAH PENELITIAN MAHASISWA Warta Penelitian Perhubungan
Bambang Siswoyo
Unknown Affiliation
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Social Sciences Transportation

Published : 39 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

 1 
MultiClass Decision Forest Machine Learning Artificial Intelligence Bambang Siswoyo
Journal of Applied Informatics and Computing Vol 4 No 1 (2020): Juli 2020
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1139.609 KB) | DOI: 10.30871/jaic.v4i1.1155

Abstract

Artificial intelligence is the best solution in dealing with various fields. The Multi Class Decesion Forest Machine Learning algorithm which is part of artificial intelligence is an interesting field to be applied in the banking field. This research was developed to build a model that can predict and evaluate bankruptcy in the banking industry. The predictor variable is the financial ratio obtained from the publication of the site http://www.idx.co.id. Modeling machine learning with six variables, where five variables as input and one variable as a target. Overall, the Multi Class Decistion Forest Machine Learning is able to train data input-output relationships and modeling behavior well, 92% accuracy value, 92% precision value and 90% under area curve value.
Co-Authors Abdy Kurniawan Achmad Zaenal Ade Hendara Adi Mulyadi Ahmad Faqih Andrianto . Azhar Azhar Banjarnahor, Ekawati Bashir Mosaddegh Benny Kadarisman Desi Mislianti Ekawati Banjarnahor Gifthera Dwilestari Gradianto, Gasa Heny Maryana Hery Widijanto I Nyoman Wahyu Satiawan John Imanuel Goro jurnal, firman Kurnia Atiullah Kurniawan, Abdy M. Fadhilatur Ramadhan Nikhlatul Maolah Pratama, Denni Roro Erna Sri Ratnawati Sagita, Ayu sse, encep Susana, Heliyanti Tri Nurwati Wijono Wijono Yunita Budi Cahyani