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All Journal Asian Journal of Management Analytics Jurnal Sains, Teknologi dan Komputer
Khesya Sabilah Rizwinie
Universitas Negeri Medan
Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Analysis of Bad Credit or Non-Performing Loan (NPL) at PT Bank Negara Indonesia (Persero) Tbk Khesya Sabilah Rizwinie; Andreas Martin Raja Sirait; Fihi Khoirani Sihotang; Patricya Damanik
Asian Journal of Management Analytics Vol. 2 No. 2 (2023): April 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ajma.v2i2.3895

Abstract

Bad credit is an important thing in the banking world because it affects the financial health of banks. This study aims to analyze the level of bad credit at PT Bank Negara Indonesia (Persero) Tbk in terms of the Non-Performing Loan (NPL) ratio. The method used in this research is qualitative. The data obtained is secondary data with quantitative data obtained from the annual report of PT Bank Negara Indonesia (Persero) Tbk for the last 15 years, starting from 2007–2022. The results of this study indicate that the highest NPL ratio level was 8.2% in 2007, and the lowest was 1.9% in 2018. The average NPL from 2007 to 2022 was 4.9%, which was included in the healthy criteria and did not endanger the bank.
Implementasi NLP Dalam Pembuatan Chatbot Customer Service Publisher Jurnal Studi Kasus LARISMA Mutiara Akbar Nasution; Anisa Fitri; Khesya Sabilah Rizwinie; Vetryc Styphen Silaban; Fihi Khoirani
Jurnal Sains, Teknologi & Komputer Vol. 1 No. 1 (2024): Jurnal Sains, Teknologi & Komputer (SAINTEK)
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/saintek.v1i1.451

Abstract

This research aims to develop a Customer Service Chatbot for Larisma Journal Publisher that can effectively answer questions and reduce response time to questions that are often similar. This research will design a Chatbot system that can facilitate users in interacting and finding information related to journal publishing, by applying Natural Language Processing. This chatbot system uses training data collected from various questions commonly asked by authors to produce accurate information, with data analysis methods involving preprocessing, training and model building. Testing the accuracy of this chatbot was carried out by the designer through a terminal in Google Colab by viewing and assessing the suitability between the questions and the answers generated. The test results state that this chatbot is able to provide effective responses by evaluating answers based on keywords in the chatbot, so as to provide the right answers.
Co-Authors Andreas Martin Raja Sirait Anisa Fitri Fihi Khoirani Fihi Khoirani Sihotang Mutiara Akbar Nasution Patricya Damanik Vetryc Styphen Silaban