Journal of Economics, Finance and Accounting Studies

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EISSN : 2709-0809
Total articles ≅ 18
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, Muhamad Yunanto, Ega Hegarini
Journal of Economics, Finance and Accounting Studies, Volume 3, pp 91-100; https://doi.org/10.32996/jefas.2021.3.2.10

Abstract:
This study analyzes the influence of financial technology on the financial performance of banks listed on the Indonesia Stock Exchange (IDX) during the 2014-2020 period. Financial technology was measured by the number of Automated Teller Machine (ATM) transactions and internet and mobile banking, while bank profitability was measured by Return On Assets (ROA). Furthermore, this study used the panel data regression analysis, with the Automated Teller Machine (ATM) transactions as well as internet and mobile banking as the independent variables, and ROA as the dependent variable. Purposive sampling was used to select six banks as samples. The results showed the fixed effect as the most suitable model, where ROA is affected by the internet and mobile banking, while the TM technology has no effect.
Muhammad Nadzif Ramlan
Journal of Economics, Finance and Accounting Studies, Volume 3, pp 60-73; https://doi.org/10.32996/jefas.2021.3.2.7

Abstract:
The purpose of this study is to model the forecast of Malaysia's export of goods using Autoregressive Integrated Moving Average Model (ARIMA) modelling with Box-Jenkins method. The time-series concerned is from the first quarter of 2015 to the first quarter of 2021 based on the Department of Statistics Malaysia (DOSM) data. The empirical analysis focuses on the five criteria for consideration towards the best model: high significant coefficient, high adjusted R-squared value, low sigma squared value, low Akaike Information Criterion (AIC) and low Schwarz Information Criterion (SIC). The study showed that ARIMA (2,1,2) would be the best model to forecast Malaysian export of goods from the second quarter of 2021 to the fourth quarter of 2022. The quarterly forecast opined the performance rate of Malaysian goods export to be at a stable positive rate of 4.9% throughout 2022, indicating the economic recovery progress that Malaysia would acquire from its vaccination programme and Movement Control Order (MCO) done in the previous year. The annual forecast showed a more precise value after comparing the actual and forecast growth value of exports in 2021. This finding is further supported with qualitative analysis about the validity of the forecast values via reports released by sources such as World Bank and Focus Economics.
, Endang Kurniati, Mardiah Hasanah Nasution, Rahmad Dani
Journal of Economics, Finance and Accounting Studies, Volume 3, pp 101-105; https://doi.org/10.32996/jefas.2021.3.2.11

Abstract:
Companies require a short time in creating their financial statements reporting their financial conditions to the public, stakeholders, and investors. In 2019-2020, 80 companies did not publish their financial statements. This phenomenon affected the effectiveness and the financial statement performance and the overall company performance. As a result, the financial statement performance was not good, and the number of investors' trusts in responding to the financial statements of 80 issuers in the stock market decreased. The declining investors' trust was caused by the low effectiveness and quality of the financial statements of 80 companies listed on the IDX. Therefore, the IDX demanded the 80 issuers repair their financial statements based on the actual conditions. This research employed a descriptive quantitative method through multiple linear regression analysis using SPSS 20. The population of this study involved 100 users of financial statements in several Indonesian companies. Meanwhile, the samples of 100 users were taken using the census method distributing a questionnaire directly to the samples via email. Based on the partial and simultaneous hypothesis tests, the data analysis results showed that the punctuality, the quality of financial statements, and the effectiveness of the financial statement information had a positive and significant effect on the companies' financial statement performance.
M. Noor Salim, Dhermawan Ismudjoko
Journal of Economics, Finance and Accounting Studies, Volume 3, pp 01-12; https://doi.org/10.32996/jefas.2021.3.2.1

Abstract:
The purpose of this research is to determine companies financial distress base on Altman, Springate, Zmijewski, Ohlson and Grover Models and to assess the accuracy of those five prediction models in coal mining sector firms listed in Indonesia Stock Exchange (IDX) for the period 2015 – 2019. This research has 22 samples of 23 coal mining firms listed in IDX base on the purposive sampling technique. This study is a descriptive design using quantitative and panel data. The research data is analyzed using the Kruskal Wallis test because there are more than two prediction models to compare and the data are not normally distributed. The result indicates that the Modified Altman and Ohlson Models are the most accurate predictive models because these models have the highest accuracy rate of 90.91%, followed by Zmijewski Model, which has an accuracy rate of 86.36%, then Grover Model has 81.82% accuracy rate, and the lowest prediction rate is Springate Model with the value of 63.64%.
, Sardiyo Sardiyo, Reza Septian, Devi Anggreni Sy, Deni Nurdiansyah
Journal of Economics, Finance and Accounting Studies, Volume 3, pp 140-151; https://doi.org/10.32996/jefas.2021.3.2.14

Abstract:
This study investigates the effect of fintech on financial inclusion, and financial literacy, it was able to influence financial literacy on financial inclusion in Lubuklinggau. The research was conducted by distributing questionnaires to eight districts in the city of Lubuklinggau with a total sample of 401 people who use fintech as the main requirement. Data analysis was carried out with WarpPLS to identify direct and indirect effects on the tested variables. Based on the results, the perception of the ease and effectiveness of using fintech does not affect financial inclusion in Lubuklinggau. People are still not familiar with fintech and consider fintech as a new financial system and not easy to use. The level of risk and interest in using fintech has a significant influence on the financial inclusion variable in the Lubuklinggau. The indirect analysis explains it proves that financial literacy is able to moderate perceptions of the ease of using fintech and reduce the risk of fintech itself on financial inclusion. However, financial literacy is not able to moderate the effectiveness of using fintech and interest in financial inclusion to use of fintech after understanding financial literacy, people become more selective in using fintech.
, Abayomi Ayinla Adebayo
Journal of Economics, Finance and Accounting Studies, Volume 3, pp 35-42; https://doi.org/10.32996/jefas.2021.3.2.4

Abstract:
This study examines the gender-disaggregated effect of health status on the growth trajectory of sub-Saharan Africa region. The renewed interest in the health status – economic growth nexus stems from the increasing recognition of the importance of health and gender roles in achieving economic growth and sustainable development, particularly in the developing regions of sub-Saharan Africa characterized by poor health, gender inequality and low growth. Health status is proxy by gender-disaggregated data on life expectancy at birth. The study employs the generalized method of moment (GMM) modelling technique, and the result shows that there is gendered differences in the effect of health status on the economic growth process of sub-Saharan Africa. In particular, we find that female life expectancy is positively associated with economic growth. Thus, the study recommends that efforts aimed at promoting health wellbeing in the region should be enhanced. In particular, policies geared towards bridging the gender gap in health should be enacted and implemented.
, Sara Almeida de Figueiredo
Journal of Economics, Finance and Accounting Studies, Volume 3, pp 43-50; https://doi.org/10.32996/jefas.2021.3.2.5

Abstract:
Predicting bank failures has been an essential subject in literature due to the significance of the banks for the economic prosperity of a country. Acting as an intermediary player of the economy, banks channel funds between creditors and debtors. In that matter, banks are considered the backbone of the economies; hence, it is important to create early warning systems that identify insolvent banks from solvent ones. Thus, Insolvent banks can apply for assistance and avoid bankruptcy in financially turbulent times. In this paper, we will focus on two different machine learning disciplines: Boosting and Cost-Sensitive methods to predict bank failures. Boosting methods are widely used in the literature due to their better prediction capability. However, Cost-Sensitive Forest is relatively new to the literature and originally invented to solve imbalance problems in software defect detection. Our results show that comparing to the boosting methods, Cost-Sensitive Forest particularly classifies failed banks more accurately. Thus, we suggest using the Cost-Sensitive Forest when predicting bank failures with imbalanced datasets.
, Siti Mujiatun, Rosita
Journal of Economics, Finance and Accounting Studies, Volume 3, pp 106-119; https://doi.org/10.32996/jefas.2021.3.2.12

Abstract:
Dividend policies aim to determine the number of dividends to shareholders and the amount to be reinvested (retained earnings). In this study, dividend policies were measured using the Dividend Payout Ratio (DPR). This study aimed to test and analyze the influence of investment, liquidity, and profitability on dividend payout ratio policies of the 2015-2019 Indonesia Stock Exchange Listed LQ-45 companies. The purpose is to find out and examine the pattern of Investment, Liquidity, and Profitability in the Dividend Payout Ratio Policy of Companies listed on LQ-45 Indonesia Stock Exchange 2015-2019. The subjects of this study were the Indonesia Stock Exchange Listed LQ-45 companies while the objects were the 2015-2019 financial statements. The population of this study was 45 companies with 30 companies as the samples after purposive sampling. Data were analyzed using multiple linear regression, classical assumption test, and hypothesis testing. The results of research in partially, investment and profitability had a significant and positive influence on the dividend payout ratio policies while liquidity had no influence on the dividend payout ratio policies. Simultaneously, investment, liquidity, and profitability had an 11.8% influence on the dividend payout ratio policies while the remaining 88.2% were explained by other variables such as leverage ratio, growth, and others.
, Sara Almeida de Figueiredo
Journal of Economics, Finance and Accounting Studies, Volume 3, pp 51-59; https://doi.org/10.32996/jefas.2021.3.2.6

Abstract:
Forecasting bank failures has been an essential study in the literature due to their significant impact on the economic prosperity of a country. Acting as an intermediary player, banks channel funds from those with surplus capital to those who require capital to carry out their economic activities. Therefore, it is essential to generate early warning systems that could warn banks and stakeholders in case of financial turbulence. In this paper, three machine learning models named as GLMBoost, XGBoost, and SMO were used to forecast bank failures. We used commercial bank failure data of Turkey between 1997 and 2001, where we have 17 failed and 20 healthy banks. Our results show that the Sequential Minimal Optimization and GLMBoost provide the same performance when classifying failed banks, while GLMBoost performs better in AUC and SMO when considering total classification success. Lastly, XGBoost, one of the most recent and robust classification models, surprisingly underperformed in all three metrics we used in research.
, Rani Ferina Pulung, Agustin Rusiana Sari
Journal of Economics, Finance and Accounting Studies, Volume 3, pp 74-80; https://doi.org/10.32996/jefas.2021.3.2.8

Abstract:
This study aims to investigate: the effect of Net Profit Margin (NPM) on stock prices and whether EPS is a moderating variable on the effect of NPM on stock prices. The case study was determined on the food and beverage sub-sector companies listed on the Indonesia Stock Exchange from 2015 to 2019. The population of this study was 26 companies, with the sampling technique used was the purposive sampling method. The use of this sampling technique resulted in 11 companies that met the criteria. The data analysis techniques used include simple regression (t test), multiple regression (F test), and interaction-type moderation tests using Moderated Regression Analysis. Data processing was carried out with the help of the IBM SPSS Ver 22 program. The findings of this study were that NPM had an effect on stock prices and EPS became a moderating variable (strengthened) on the effect of NPM on stock prices.
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