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All Journal Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal International Journal of Advances in Data and Information Systems
Arif Furqon Nugraha Adz Zikri
Master of Management Science, Faculty of Economics and Business, Padjadjaran University
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Pay Later Risk Management: A Review of FMECA and Potential Customer Prediction Frameworks Through the Application of Machine Learning Arif Furqon Nugraha Adz Zikri; Wiwin Suwarningsih
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1293

Abstract

The development of technology continues to develop and gradually change the way people buy such as on online shopping sites. The increase in internet use, especially in the use of E Commerce, has given birth to great potential in the market, especially in Indonesia. These changes prompted the birth of various payment methods. One of them is Pay Later. 27% of the 3560 samples decided to use Pay Later with all the conveniences offered. However, the development of Pay Later is not synchronized with good risk management. The use of Pay Later, which is not targeted at the right consumers, causes PT. XYZ suffered losses due to 22.37% of users defaulting on Pay Later installments. The purpose of this study is to reduce Pay Later default users by answering what factors cause consumers to default. To support this study, the authors used FMECA, Cause Effect Diagrams and conducted tests using Machine Learning to improve company efficiency. Through critical matrix analysis, the author gets 3 priority failure modes, Users default, users disappear, and users experience payment delays. In solving the problems in this study, the authors provide recommendations in the form of a new framework in the form of analyzing the best Pay Later offers by analyzing consumer behavior patterns in an E Commerce by utilizing Machine Learning. However, future research will need to be conducted correlation analysis and static testing in testing attribute correlation before testing algorithms when building machine learning models. The authors also suggested comparing using other methods to improve risk management in this study.
RETRACTED: Sustainable Human Resource Management: A Transformation Perspective of HRM Functions Through Optimized Artificial Intelligence Arif Furqon Nugraha Adz Zikri; Sunu Widianto; Rita Komaladewi
Jurnal Aplikasi Bisnis dan Manajemen Vol. 10 No. 2 (2024): JABM, Vol. 10 No. 2, May 2024
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.10.2.557

Abstract

We hereby announce the retraction of the article titled “Sustainable Human Resource Management: A Transformation Perspective of HRM Functions Through Optimized Artificial Intelligence”, Vol. 10 No. 2, Mei 2024. This retraction is due to the discovery that the article had been previously published in BISMA (Bisnis dan Manajemen, which constitutes a violation of our policy on duplicate publication. The document pertaining to the article, including its content and any supplementary materials, has been retracted from the Jurnal Aplikasi Bisnis Dan Manajemen (JABM). Consequently, it is imperative to undertake reasonable measures to expunge all references to this article.
Co-Authors Rita Komaladewi Sunu Widianto Wiwin Suwarningsih