Article Per Year (5 Year)
p-Index From 2019 - 2024
5.075
P-Index
This Author published in this journals
All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information System, Applied, Management, Accounting and Research Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Indonesian Journal of Business Intelligence (IJUBI) Jurnal Teknologi Dan Sistem Informasi Bisnis JISA (Jurnal Informatika dan Sains) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Ilmiah Intech : Information Technology Journal of UMUS Jurnal Teknologi Informatika dan Komputer Bulletin of Information Technology (BIT) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) SIGMA: Information Technology Journal Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Lentera Pengabdian VIDHEAS: Jurnal Nasional Abdimas Multidisiplin SAINTEK
Wahyu Hadikristanto
Universitas Pelita Bangsa
Religion Agriculture, Biological Sciences & Forestry Humanities 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 Engineering Industrial & Manufacturing Engineering Social Sciences

Published : 40 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

 1 
Analisis Perbandingan Algoritma Optimasi pada Random Forest untuk Klasifikasi Data Bank Marketing Yoga Religia; Agung Nugroho; Wahyu Hadikristanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (271.874 KB) | DOI: 10.29207/resti.v5i1.2813

Abstract

The world of banking requires a marketer to be able to reduce the risk of borrowing by keeping his customers from occurring non-performing loans. One way to reduce this risk is by using data mining techniques. Data mining provides a powerful technique for finding meaningful and useful information from large amounts of data by way of classification. The classification algorithm that can be used to handle imbalance problems can use the Random Forest (RF) algorithm. However, several references state that an optimization algorithm is needed to improve the classification results of the RF algorithm. Optimization of the RF algorithm can be done using Bagging and Genetic Algorithm (GA). This study aims to classify Bank Marketing data in the form of loan application receipts, which data is taken from the www.data.world site. Classification is carried out using the RF algorithm to obtain a predictive model for loan application acceptance with optimal accuracy. This study will also compare the use of optimization in the RF algorithm with Bagging and Genetic Algorithms. Based on the tests that have been done, the results show that the most optimal performance of the classification of Bank Marketing data is by using the RF algorithm with an accuracy of 88.30%, AUC (+) of 0.500 and AUC (-) of 0.000. The optimization of Bagging and Genetic Algorithm has not been able to improve the performance of the RF algorithm for classification of Bank Marketing data.
Co-Authors Abdul Hasyim Achmad Firmansyah Putra Adibah Yahya Agung Nugroho Ahmad Zy Ali Nurdiansyah Andri Firmansyah Arvita Emarilis Intani Aswan S Sunge Dichi Setiawan Edi Junianto Edi Widodo Edora Edora Fajar Arief Rachman Gatot Tri Pranoto Holwati Imam Nasai2 Intan Sari Rahayu Irfan Afriantoro Irfan Afriantoro Ismasari Ismasari Maulida Ramadhan Mico Giovanni Dermawan Muhamad Fatchan Muhammad Makmun Effendi Muhammad Suprayogi2 Nanang Tedi Kurniadi Naufal Muyassar Nita Paramita Njai Njai Nur Azizah Nurhadi Surojudin Nurul Ariffaeni Islami Purdianto Purdianto Rasmiati Nur Aeni Retno Purwani Setyaningrum Rosyati Adelia Sandi Salvan N N Sapardi . Suhardian Suhardian Suherman Suherman Suherman Sya syah Apriliyani Taofik Safrudin Tiara Deswara Pungkas Vidya Anis Fitri Yoga Religia