Vol. 5 No. 3 (2024)

Abstract

Energy is a crucial necessity for human societies, and access to electrical energy plays a significant role in economic development. A state-owned enterprise (SOE) is entrusted with the provision of electrical energy across Indonesia. The objective of this study is to identify and assess risk factors within the supply chain of primary distribution materials at SOE. The identification of risk factors was based on a comprehensive review of literature across various industrial sectors, further validated through consultations with senior managers at the company. For the assessment of these risks, the study employed the modified Decision Matrix Risk Assessment methodology, which involves evaluating risks based on their likelihood and impact. This evaluation was conducted through surveys distributed to 66 respondents, including planning managers, distribution managers, and commercial managers across all regional and distribution main units in Indonesia. Two risk categories with five sub-categories and a total of 27 risk factors were identified. Supply-related risks are the most significant compared to the other four sub-categories. Scarcity of raw materials, lack of capacity flexibility, and failure to make delivery requirements are in the top three rankings. This research can enrich the supply chain risk literature and provide valuable insights for utility managers in understanding supply chain risks.

Abstract

This study aims to examine and analyze the effect of return on assets, debt to equity ratio and earnings per share on the share price of telecommunications sector companies listed on the Indonesia Stock Exchange. This research uses secondary data, secondary data in this study is obtained from the annual financial statements of companies listed on the Indonesia Stock Exchange by accessing the www.idx.co.id website. The sample in this study was 6 companies, sampling using purposive sampling techniques. The method used in this study is quantitative descriptive method. The data analysis method in this study used panel data, namely Eviews 12. This research was conducted based on data obtained during the period 2014 to 2023. The results of this study show that partial return on assets has no effect on stock returns, partial debt to equity ratio has no effect on stock returns and partial earnings per share has no effect on stock returns. Simultaneously return on assets, debt to equity ratio and earnings per share have no effect.

Abstract

Based on Presidential Regulation Number 112 of 2022 concerning the Acceleration of Renewable Energy Development for the Supply of Electric Power, Indonesia has a road map in which there is a strategy program for accelerating the end of the operational period of PLTUs. In implementing early retirement, there is a risk of stranded assets that needs to be mitigated. Appropriate decision-making strategies and effective mitigation are needed to reduce the impact of stranded asset risk. Using the Anaytical Hierarchy Process (AHP), this study tries to analyze the implementation of the PLTU early retirement strategy by taking into account the risk of stranded assets and finding appropriate mitigation in reducing the level of impact of the risk of stranded assets that needs to be implemented by stakeholders. The results show that effective mitigation requires comprehensive planning and stakeholder involvement, which can substantially ease the financial transitions from coal to renewable energy sources. The findings suggest that integrating economic and policy considerations into the early retirement planning of coal-fired power plants is crucial for managing the transition effectively and minimizing potential financial losses. This approach ensures a smoother transition to sustainable energy sources, contributing significantly to both national and global decarbonization goals.

Abstract

This study investigates the impact of Indonesia's newly implemented restructuring relaxation policies as moderating variables on the banking sector's performance. Utilizing panel data regression analysis on a sample of 105 banks from 2017 to 2022, the research examines the relationships between non-performing loans (NPL), loan loss provisions (LLP), efficiency ratios, and bank return on assets (ROA). The findings indicate that prior to the policy implementation, the efficiency ratio negatively affected government banks' ROA, while both LLP and the efficiency ratio negatively impacted private and foreign banks' ROA. Post-implementation, the interaction between these policies and each variable (NPL, LLP, and efficiency ratio) was found to be significant for government banks, whereas none of them showed significance for private or foreign banks. This research contributes to understanding financial regulation dynamics and provides insights for policymakers and banking institutions navigating market complexities.

Abstract

This study aimed to anticipate the rupiah loan interest rates at commercial banks in Indonesia by employing the Holt-winters method. This study employs data on rupiah loan interest rates from commercial banks in Indonesia. The data comprises a time series element, with monthly intervals spanning from January 2013 to November 2015, which was obtained from the official website of BPS Indonesia. The study demonstrates that the Holt-winters technique yields the most accurate forecasts, as indicated by a Root Mean Square Error (RMSE) of 0.19720630. The parameters alpha, beta, and gamma, set at 0.6, 0.6, and 0.6 respectively, constitute the optimal configuration for this method. These results indicate that the Holt-winters method is an effective tool for capturing seasonality, trends, and patterns in credit interest rate data, making it a reliable choice for future loan interest rate forecasting. The findings of this study are expected to significantly contribute to strategic decision-making in the banking sector, particularly in risk management and loan interest rate strategy determination.

Abstract

The ESG Rating measurement method from Sustainalytic & S&P is the method that is considered the most suitable for analyzing ESG risks in State-owned electricity companies. This research analyzes the ESG Rating measurement method issued by 4 ESG rating agencies, namely S&P, MSCI, Sustainalytics, and Refinitiv using the method AHP, the results of which will determine which method is most suitable for analyzing ESG risks in state-owned electricity companies. From the results of data collection, it was found that the ESG rating measurement method from Sustainalytic had the highest priority value, namely 38.9%, which was not much different from the method from S&P with a value of 34.0%. Meanwhile, the methods of the other 2 ESG rating agencies have a lower weight, namely MSCI with 14.2% and Refinitiv with 12.9%. Research provides the view that the level of correlation between rating agencies is still low, requiring companies to first analyze the rating agency. The ones they choose will determine the company's strategy in managing their ESG risks.

Abstract

This study aims to examine the influence of financing diversification, which includes six financing contracts of Islamic banks in Indonesia and financial performance on credit risk represented by NPF in Islamic commercial banks using regression panel data in 2018-2022. The results of this study indicate that there is an insignificant positive influence on financing diversification and financial performance partially on credit risk in Islamic banking in Indonesia. However, financing diversification and financial performance together have a significant influence on credit risk, which is currently a concern of the Islamic bank financial services authority in Indonesia. The financial performance measurement indicators in this study only focus on ROA, and this indicator may have limitations in measuring the financial performance of Islamic banking.

Abstract

The electricity demand at Public Electric Vehicle Charging Stations (SPKLUs) exhibits significant volatility, which is driven by several aspects including electricity demand patterns at specific time intervals, load variability, SPKLU capacity, and other related factors. The variability of these swings can present hazards for SPKLU operators in relation to energy administration as well as operational and financial hazards. The objective of this study is to assess the risk associated with energy demand fluctuation at SPKLUs by employing the Conditional Value-at-Risk (CVaR) model technique. CVaR, or Conditional Value at Risk, is a quantitative measure of risk that calculates the predicted loss value in the most unfavorable situation. It is commonly employed to enhance the risk management approach of SPKLUs. The electricity demand at SPKLU exhibits significant volatility, with an average fluctuation of 10.15% and a standard deviation of 49.67%. The CVAR, calculated at -121.19% for a confidence interval of 1%, represents the maximum potential loss that could be experienced during worst-case electrical demand conditions, highlighting the substantial fluctuations in demand. The study initially implemented the CVaR model to analyze power demand at SPKLU, providing novel perspectives on risk reduction for critical infrastructure and proposing unique strategies for managing demand fluctuations in a reliable and efficient manner. The results also offer comprehensive insights into risk exposure and facilitate the formulation of well-informed and strategic risk management plans.

Abstract

The Indonesia government is actively promoting the adoption of electric vehicles, as detailed in the 2021-2030 Electricity Supply Business Plan. The state-owned electricity provider, PLN, is responsible for establishing Public Electric Vehicle Charging Stations (PEVCS). However, several of these stations have encountered malfunctions; notably, 82 of the 567 stations are classified as Unavailable, indicating they are non-functional. Research literature points to a financial loss of $34,000 from operational issues at PEVCSs. This research aims to helps management understand and prioritize disruption that leads to failures or damages at these stations. Method used is the Failure Mode and Effects Analysis (FMEA) method along with logistic regression to examine the disruptions at PEVCSs labeled as Unavailable. The data for this research comes from a six-month historical record of PEVCS disruptions. The variables utilized for logistic regression analysis include foundational variables from the FMEA methodology—Severity, Occurrence, and Disturbance—complemented by two supplementary variables: the speed and age of the PEVCS. Result was found that three out of twelve types of disruptions have a high likelihood of failure, specifically issues with Device Communication, Connectivity, and Emergency Stop functions. A disruption is deemed likely to cause failure if its probability exceeds 50%.

Abstract

Systematic Literature Review (SLR), which focuses on the role of innovation and competitive advantage as mediators of various factors on the performance of Micro, Small, and Medium Enterprises (MSMEs), is still relatively rare. Therefore, this study aimed to determine the factors that affect competitive advantage and the role of innovation mediation and competitive advantage in influencing MSMEs performance. This study utilized Google Scholar as a database. Of 500 studies, 400 were excluded according to the title and abstract, and 100 were screened for eligibility, resulting in 41 studies included for review. This study showed that there were 45 factors that affected competitive advantage and 15 factors that affected sustainable competitive advantage. This study also found that innovation variables, including marketing innovation, innovation, green innovation, and corporate open innovation, mediated various factors influencing competitive and sustainable competitive advantages. Also, competitive advantage was able to mediate the relationship between several factors that affected the performance of MSMEs. These findings provided a reference for future research to analyze innovation as a mediating variable for the relationship of various factors to competitive advantage. This finding also provides information that for MSMEs to survive in globalization, they should have a competitive advantage to be competitive. Thus, the factors in this study can be used to strengthen the competitive advantage of MSMEs and improve their performance.

Abstract

This research aims to develop MSMEs in Aek Songsongan Asahan Sub-district through training in simple bookkeeping, financial management, and internal control. This research uses a qualitative research design with a field study approach. Data were collected through interviews, observation, and evaluation. Data analysis used data triangulation, which combines data from various sources. The results showed that the training improved the efficiency and effectiveness of MSME operations, and promoted financial growth and stability. A more detailed discussion compares with previous studies in the last five years that show the positive impact of training in simple bookkeeping, financial management, and internal control on MSMEs. However, this study also explores aspects of sustainability and technology integration that have not been widely discussed in previous studies. This research makes an important contribution in developing MSMEs through human resource capacity building, particularly in the aspects of simple bookkeeping, financial management, and internal control.

Abstract

This study examines the need for an effective performance management system within organizations. Prior research indicates that such systems significantly enhance business outcomes (Pulakos, Mueller-Hanson & Arad, 2019). O’Kane, McCracken & Brown (2022) introduced a conversation-based performance management model grounded in social exchange theory (SET), suggesting that discussions between supervisors and subordinates foster positive reciprocal relationships. This research aims to analyze the effectiveness of the performance management system implemented by a private trading company in Indonesia. The qualitative study involved semi-structured interviews with the Board of Directors, HRD, Line Managers, and Staff, as well as focus group discussions with Senior Managers. Findings reveal gaps in the system's implementation, notably the absence of feedback processes central to this model. Identified factors contributing to these gaps include goal alignment, feedback frequency, skills development, and formality, alongside environmental factors such as design, development function, buy-in, culture, and linkage with other systems. The study underscores the importance of feedback and explores the system's effectiveness from various perspectives, offering insights that contribute to the literature on performance management systems, particularly conversation-based approaches in private companies in Indonesia.

Abstract

In today's data-driven era, big data automation is crucial, often referred to as "the new oil." Industries, particularly the fast-moving consumer goods (FMCG) sector like the tobacco industry, must undergo digital transformation to stay competitive. The integration of big data automation with reporting processes is significantly correlated, as it can automate repetitive reporting tasks, enhancing efficiency. This automation enables decision-makers to make faster and more accurate decisions.

This research focuses on assessing the capacity and factors involved in the collaboration between the operations department and the digital team to automate repetitive reporting processes by integrating big data from various sources such as SAP and Microsoft Forms. The study employs a combination of qualitative and quantitative methods, along with the Analytic Hierarchy Process (AHP), to identify optimal business solutions. Insights from this research prioritize big data automation and reporting projects to meet business needs. Results indicate among four alternative project groups, the Central Data Wastage project is the top priority with a score of 51.7%, followed by SMD Wastage at 25.2%, PMD Wastage at 14.7%, and FMD Wastage at 8.4%. Five stakeholders participated in this research, including a product manager, business user, business analyst, and two developers. These participants contributed to assessing criteria, sub-criteria, and alternative project groups. This research not only helps prioritize projects but also facilitates seamless digitalization within the operations team, fostering synergy with the digital team.

Abstract

The purpose of this research is to identify the primary operational risks associated with photovoltaic power plants and develop effective risk management strategies to optimize the operation of existing plants and mitigate risks for future plants that will be constructed as part of the new renewable energy (EBT) transition agenda until 2030. The integration of Failure Mode and Effect Method Analysis (FMEA) with logistic regression provides the formation of a risk treatment ranking that management should prioritize. Risk assessment relies on the expertise and experience of professionals in performing their responsibilities associated with photovoltaic power plants. The research findings have identified 10 potential risks associated with improving photovoltaic power plants operations to prevent failure or damage to the system. These risks are categorized into five stages of the operation process: planning and procurement, installation, operation, and maintenance. Risk rankings and mitigation are generated to prioritize actions aimed at limiting the occurrence of failure/damage and low-capacity factors in photovoltaic power plants as recommendations for the management.

Abstract

While acknowledging the importance of training, the challenge lies in understanding and optimizing its effectiveness, especially in the context of the government institution’s ever-changing landscape and the associated budgetary considerations. It examines whether pre-training factors—organizational support, training environment, trainer quality, and training need analysis— influence training effectiveness directly or are mediated by motivation to learn, motivation to transfer, and self-efficacy in non-ministerial government institutions in Indonesia. Data were collected from 202 respondents across 19 institutions using purposive sampling and analyzed with Covariance Based-Structural Equation Modeling (CB-SEM) using Lisrel 8.80. The findings reveal that trainer quality significantly affects motivation to learn, motivation to transfer, and self-efficacy but does not directly impact training effectiveness. Instead, its influence is mediated by motivation to transfer and self-efficacy. This underscores the crucial role of trainers in enhancing training effectiveness by boosting participants' motivation and self-efficacy. The study highlights the need for organizations to invest in high-quality trainers through ongoing professional development, robust evaluation systems, and incentives to improve training outcomes and achieve organizational goals more efficiently.

Abstract

The purpose of this research is to determine the effect of Role Ambiguity, Workload moderated by Resilience on employee Burnout at PT. United Waru Biscuits manufacturing. Cikande Branch. The research method used is associative with a quantitative approach. Data collection techniques, data questionnaires and literature study. The partial research results of the first test using a one sample t-test showed; The first test of the Ambiguity variable on Burnout obtained a t-count value of 11.983 > t-table 1.988, with a significance of 0.000 < 0.05, this shows that there is a positive and significant influence, the second test of the Workload variable on Burnout obtained a t-count value of 6.813 > t -table 1.988 with a significance of 0.000 < 0.05, this shows that there is a positive and significant influence, the third test of Role Ambiguity on Employee Burnout which is moderated by Resilience obtained a t-count value of 1.045 < t-table 1.988, with a significance of 0.299 > 0, 05 This shows that there is no positive and significant influence. The fourth test of Workload on Employee Burnout moderated by Resilience obtained a t-count value of 1.695 < t-table 1.988, with a significance of 0.094 > 0.05, this shows that there is no positive and significant influence.

Abstract

This study aims to compare the disclosure of Value at Risk (VaR) in market risk prediction among banks in Indonesia. By employing comparative and analytical methods, this research examines the effectiveness of VaR disclosure as a market risk prediction tool. Through the evaluation of VaR models disclosed by Indonesian banks and their comparison to a parametric model using asymmetric GARCH volatility for Variance Covariance Value at Risk, this study identifies the extent to which VaR disclosure can be relied upon to predict market risk. This research contributes to the understanding of risk management practices in the Indonesian banking sector and offers recommendations for improving market risk prediction accuracy through more effective VaR disclosures.

Abstract

Current study explored the connection between e-service quality, social networks, purchase intention, and customer trust, specifically focusing on how artificial intelligence impacts e-service quality within insurance companies. This research employed Theory of Planned Behavior as the basis foundation and conducted through a quantitative approach. Denpasar was used as the research location and targeting 150 local communities as respondents. Empirical data was collected through questionnaires and the analysis was performed using Structural Equation Modeling (SEM) with AMOS version 23 software. The findings indicate significant and positive relationships among all variables, leading to the acceptance of all hypothesis. The findings of this research show that the quality of AI-based services and social networks has a significant impact on the level of consumer trust in insurance products. A high level of trust in the quality of insurance products will in turn increase consumers' willingness to use these insurance products, thereby stimulating consumer loyalty towards insurance companies. The results of data analysis highlight that trust is a crucial key in consumer interest in purchasing a product. Interesting findings from this research also emphasize that gender, especially female consumers, show higher interest in insurance products. This is due to the belief that women have a high awareness of health and financial risks, thus motivating them to use insurance products.

Abstract

This research aims to test the effect of work-life balance and burnout on employee job satisfaction in the Pekanbaru city banking industry, both simultaneously and personally. This research is quantitative research. The sample in this study is a total of 100 employees of the banking industry in the city of Pekanbaru. The sampling technique used is saturated sampling by the way all populations are sampled. Data collection is by the primary method obtained from the results of the questionnaire distribution. The analysis technique used is multiple linear using the smartPLS version 3 application. Based on the results of research, it is shown that work-life balance (X1) has a positive and significant effect on Job Satisfaction (Y) and burnout (X2) has a positive and significant effect on job satisfaction (Y) in employees of the banking industry in the city of Pekanbaru. The three variables together work-life balance and burnout have a positive and significant effect on job satisfaction in employees in the banking industry in the city of Pekanbaru.

Abstract

This study examines the effectiveness of various liquidity proxies in distinguishing between Investment Grade (IG) and High Yield (HY) bonds within the Indonesian corporate bond market. Utilizing logistic regression models across a dataset of 30,738 observations for IG bonds and 176 observations for HY bonds, we evaluated the impact of six liquidity proxies: Range Measure (RG), Hui Heubel ratio (HH), Market Share (MS), Interquartile Range (IR), Imputed Roundtrip Cost (IRC), and Trading Volume (TV). The findings reveal that the Imputed Roundtrip Cost (IRC) is the most reliable indicator of liquidity, demonstrating a significant negative relationship with the likelihood of a bond being classified as IG. This suggests that higher IRC values, which represent higher transaction costs, are associated with lower liquidity. In contrast, the other proxies, including the Hui Heubel ratio, did not show consistent or significant impacts in line with the hypotheses. The study concludes that IRC is the best measure for assessing liquidity in the Indonesian corporate bond market.