Article Per Year (5 Year)
p-Index From 2020 - 2025
2.364
P-Index
This Author published in this journals
All Journal TEKNIK INFORMATIKA Jurnal Keuangan dan Perbankan FIRM: Journal of Management Studies Proceeding of the International Conference on Family Business and Entrepreneurship (ICFBF) Prosiding Sesiomadika Journal of Actuarial, Finance, and Risk Managment
Edwin Setiawan Nugraha
President University
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences Other

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 16 Documents
Search

 1   2 
Cover Page Edwin Setiawan Nugraha
Proceeding of the International Conference on Family Business and Entrepreneurship 2022: Proceeding of the 5th International Conference on Family Business and Entrepreneurship
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (382.343 KB) | DOI: 10.33021/icfbe.v2i1.3521

Abstract

This is the cover page of the Proceeding of the 5th International Conference on Family Business and Entrepreneurship.
Impacts of macroeconomics factors toward IDX composite and IDX finance during Covid-19 pandemic Mei Siang Jemima Aurelia; Ranny Febrianti; Edwin Setiawan Nugraha
Proceeding of the International Conference on Family Business and Entrepreneurship 2022: Proceeding of the 5th International Conference on Family Business and Entrepreneurship
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (636.574 KB) | DOI: 10.33021/icfbe.v2i1.3556

Abstract

Macroeconomics is the branch of economy that deals with activity, structure, behaviour and decision making of economy as a whole. IDX Composite and IDX Finance are stock market indices used by Indonesia Stock Exchange, unfortunately, relationship between macroeconomics and IDX composite and IDX finance during COVID-19 period in Indonesia is still poorly understood. This research aimed to investigate the impacts of macroeconomics factor included Inflation Rate, Bank Indonesia rate (BI Rate), the exchange rate on IDR, and monthly new cases of COVID-19 in Indonesia on IDX Composite and IDXFINANCE, respectively. The analysis was using multiple linear regression method. The result indicated that BI Rate negatively significantly impacted both IDX Composite and IDXFINANCE. While, Indonesian inflation and USD to IDR exchange rate, gave significant impact on IDX Composite, consecutively positively and negatively. Partial test indicated that COVID-19 monthly cases in Indonesia did not impact both IDX Composite and IDXFINCANCE. In addition, Indonesian inflation and USD to IDR exchange rate also did not impact IDXFINANCE.  Overall test illustrated that all of the mentioned macroeconomics variables impacted both IDX Composite and IDXFINANCE. This research is expected to help investors and traders in making futures investment decision.
Tea production forecasting in Indonesia’s large plantation by using ARIMA models Juliano Victor Christian Medellu; Edwin Setiawan Nugraha
Proceeding of the International Conference on Family Business and Entrepreneurship 2022: Proceeding of 6th International Conference on Family Business and Entrepreneurship
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1086.955 KB) | DOI: 10.33021/icfbe.v3i1.3750

Abstract

Indonesia is known for its outstanding agricultural sector and natural wealth. Tea is one of the plantation sectors that are mostly consumed all over the world and has been one of Indonesia’s mainstay commodities that has already been listed as one of the 10 export commodities with a big amount of production. Tea production data have a fluctuating pattern and characteristic. Therefore, it is really important to know the projection of tea production for planning and management purposes. The ARIMA (Autoregressive Integrated Moving Average) model is one of the methods that can be used to predict future productions. The ARIMA (4,1,0) is found to be the most suitable model to be used with a MAPE of 29.9%. The forecasting process shows the production will have an uptrend pattern for ten months from March 2018. The Tea production forecast data will be useful for future planning and production control.
Comparison of Microeconomics and Stock Returns Relationships in Financial Sector in 2019 and 2020 Mei Siang Jemima Aurelia; Edwin Setiawan Nugraha
Jurnal Keuangan dan Perbankan Vol 26, No 3 (2022): JULY 2022
Publisher : University of Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jkdp.v26i3.7877

Abstract

Stock return is crucial to analyze before making investment since gaining return is the main objective. The analyzing can implement fundamental analysis which involves microeconomics variables of company. According to IDX, financial sector generates the highest return, unfortunately it is still volatile. Moreover, since COVID-19 pandemic, economic situation becomes unstable. This research aims to analyze and compare partial and simultaneous relationship of microeconomics variables (Book Value Per Share, Price to Book Value, Price Earning Ratio, Debt to Equity Ratio, Net Profit Margin and Debt Ratio) with stock return in financial sector main board companies in 2019 (before COVID-19 pandemic) and 2020 (during COVID-19 pandemic). Multiple linear regression is implemented and resulting that in 2019, only Price to Book Value, Price Earning Ratio and Net Profit Margin have significant relationship with stock return. In 2020, only Price Earning Ratio and Debt to Equity Ratio have significant relationship with stock return. For both years, simultaneous relationship between all microeconomics variables and stock return are found. The result can be used for investor and main board financial sector companies.
A Backpropagation Artificial Neural Network Approach for Loan Status Prediction Gabrielle Jovanie Sitepu; Edwin Setiawan Nugraha
JURNAL TEKNIK INFORMATIKA Vol 15, No 2 (2022): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v15i2.27006

Abstract

Providing credit has become a main source of profit for financial and non-financial institutions. However, this transaction might lead into credit risk. This risk occurred if debtors unable to complete their obligations that will led loss for creditors.  It is necessity for company to create assessment in distinguishing eligible or non-eligible prospective customer. Artificial Neural Network (ANN) is introduced in solving this typical classification case. Furthermore, one of learning algorithm in ANN namely Backpropagation is able to minimizing error of output in order to receive accurate result. This research aims to form models that capable in classifying the loan status of applicants by utilizing historical data. The method developed in this research is Backpropagation with activation function is a sigmoid function. In addition, this research formed two data model for analyzed; with first data model is every variable given in dataset and for the second data model is the variables that influenced the loan acceptance. Backpropagation shows high performance with more or less data variables. The results of this research show that the both data model has highest accuracy of prediction is 94.37% while the lowest accuracy prediction is 80.28%.
Forecasting the Number of Jabodetabek Train Passengers Using ARIMA Moerpradighta Prayreyka; Edwin Setiawan Nugraha; Mokhammad Ridwan Yudhanegara
Prosiding Sesiomadika Vol 4 No 1 (2023): Seminar Nasional Matematika dan Pendidikan Matematika
Publisher : Prosiding Sesiomadika

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to analyze a suitable forecasting model using ARIMA to help PT. KAI Indonesia in predicting the number of train passengers in Jabodetabek. This study uses the method of identifying forecasting patterns. Model selection is very important in forecasting because forecasting models are beneficial for forecasting using past data in the past. The sample used is the number of Jabodetabek train passengers from January 2014 to December 2016. The results show that the suitable forecasting method to predict the number of Jabodetabek train passengers is the ARIMA method (3,1,6). The results from this analysis can be used for considering to calculate operational costs and business development in the future.
Analysis of Financial Risks on Indonesian Commercial Banks Return on Asset in 2012 – 2021 Edwin Setiawan Nugraha; Rosyid Nur Salam
FIRM Journal of Management Studies Vol 8, No 1 (2023): FIRM JOURNAL OF MANAGEMENT STUDIES
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/firm.v8i1.4149

Abstract

Financial risks analysis is immensely important for financial institutions since obtaining desirable return at acceptable level of risks is their main objective. Based on Indonesian Banking Statistics, non-performing loans and risk weighted assets have increased annually in Indonesian commercial banks from 2012 to 2021. Additionally, fluctuations in external variables can result in uncertainties which cannot be controlled internally. This work presented analyze the relationship between financial risks such as credit, liquidity, interest rate, inflation, and foreign exchange toward commercial banks return on asset by using multiple linear regression.  The results that independent variables simultaneously have a significant relationship towards return on asset. In addition, some independent variables such inflation rate and liquidity risks have partially positive significant relationship to return on asset while operational risk has negative relationship.  The result of this research will be insight for practitioner in banking as consideration when they are designing the strategy for enhancing their return on asset
Log Linear Model on Contingency Table to Analyze Relationship between Age, Income, and Health Insurance Ownership Evelyn Priscilla; Jeslyn Prinssesa; Mei Siang Jemima Aurelia; Edwin Setiawan Nugraha
Journal of Actuarial, Finance, and Risk Management Vol 1, No 1 (2022)
Publisher : Journal of Actuarial, Finance, and Risk Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/jafrm.v1i1.3674

Abstract

Health insurance is a type of insurance that is important for everyone to have since it has benefits as protection against health risks that may occur in the future. Unfortunately, most people nowadays do not really want health insurance, especially people who are relatively young and have low incomes. Young people feel that they are still strong and do not get sick easily, while people with low incomes cannot afford to buy insurance because of the high premium prices. Therefore, the relationship between age, income, and insurance ownership (other than BPJS) needs to be known to help insurance companies develop new strategies. In this study, we implemented a Log-Linear model on a contingency table using survey data that we took in Jabodetabek, Bali, and Kalimantan areas. The results showed that the Log-Linear model (OI.OA.IA) was efficient enough to determine the relationship between age, income, and insurance ownership with a 95% confidence level. Homogeneous interactions happened so that there is no relationship between age, income, and insurance ownership, but there were relationships between age and income, age and insurance ownership, and income and insurance ownership. This research is expected to assist insurance companies in determining their target market and developing their marketing.
Forecasting PT Bank Central Asia Tbk Stock Price Using ARIMA Model Agna Olivia; Edwin Setiawan Nugraha
Journal of Actuarial, Finance, and Risk Management Vol 2, No 1 (2023)
Publisher : Journal of Actuarial, Finance, and Risk Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/jafrm.v2i1.4563

Abstract

Stocks are one of the most popular financial market instruments. Issuing shares is one of the company's options when deciding to fund the company. On the other hand, stocks are an investment instrument that many investors choose because stocks are able to provide an attractive level of profit. Autoregressive Integrated Moving Average (ARIMA) model is a method used to predict the stock price of PT Bank Central Asia Tbk. This analysis shows that ARIMA (3,2,0) is the best model for forecasting the stock price of PT. Bank Central Asia Tbk because it has the smallest MAPE among the other model which is 14.03%. This forecasting is very useful for the investor as a guideline in the future for making effective and efficient decisions about stocks on PT Bank Central Asia Tbk.
ARIMA Model in Predicting Jakarta Composite Index Shafa Luthfia Sari Haerani; Edwin Setiawan Nugraha
Journal of Actuarial, Finance, and Risk Management Vol 1, No 1 (2022)
Publisher : Journal of Actuarial, Finance, and Risk Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/jafrm.v1i1.3675

Abstract

This study discusses stock price modeling using ARIMA model. We apply to model to the Jakarta Composite Index (JCI) as it represents all stock performances listed in Indonesia Stock Exchange. In this study, we propose several ARIMA models based on the daily from June 10th, 2019 until December 6th, 2019. The parameters among the models are estimated by using RStudio. We chose the best model by considering its AIC and RMSE. The best model that is ARIMA (21, 1, 2) with 99% confidence interval. This model is then used to predict the next 15 days (December 09, 2019 to January 02, 2020).
Co-Authors Adi Saptari Agna Olivia Christabell Christabell Elisabeth Gloria Manurung Evelyn Priscilla Gabriella Maria Singgih Gabrielle Jovanie Sitepu Jeslyn Prinssesa Juliano Victor Christian Medellu Karunia Eka Lestari Lovena Louisa Mei Siang Jemima Aurelia Mei Siang Jemima Aurelia Moerpradighta Prayreyka Mokhammad Ridwan Yudhanegara Novia Galuh Ramadhanty Ranny Febrianti Rifky Fauzi Rosyid Nur Salam Shafa Luthfia Sari Haerani