Rescollacomm (E-Journals)
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Modeling Fire Insurance Claim Frequency Using Negative Binomial Regression
Full text linkFire insurance plays an important role in providing financial protection against losses caused by fire risks. To support risk management and accurate premium determination, a model capable of predicting claim frequency based on relevant factors such as the Total Sum Insured (TSI) is required. The data used in this study consist of statistical fire insurance data covering the number of policies and claim frequencies in three provinces: West Java, Central Java, and East Java. The analysis was conducted using Poisson regression and Negative Binomial regression to model and predict claim frequency based on TSI. Initial estimation using the Poisson model indicated the presence of overdispersion, suggesting that this model is less suitable for the data. Therefore, the Negative Binomial regression model was applied, as it can better handle excessive variance. This model produced a lower AIC value compared to the Poisson model and showed that TSI has a significant effect on claim frequency. Thus, the Negative Binomial regression model is considered more accurate for predicting fire insurance claim frequency based on TSI
Determining the Optimum Replacement Time of Dosing Pump Components Using the Age Replacement Model (Case Study at PDAM Tirtawening Bandung)
Full text linkThe increase in population over time has a direct impact on the rising demand for clean water supply services, making the availability and management of water resources an increasingly critical aspect. To maintain water quality and supply continuity, reliable production machines are required. One of the machines used is a dosing pump, whose critical component is the valve ring. To ensure continuous operation without machine failure during the production process, appropriate maintenance is required by determining the optimum replacement time interval for the valve ring component using the Age Replacement model. The results of the data analysis show that the failure of the valve ring component follows a Nonhomogeneous Poisson Process (NHPP) with a Power Law Process (PLP) failure model. The optimum replacement time for the valve ring component based on the Age Replacement model is every 103.87 days of operation with a total replacement cost risk of Rp. 925,063.20, and this model is able to reduce the replacement cost of the valve ring component by 46.72%
Building Globally-Ready SMEs Through Strengthening Compliance and Risk Management with Indonesia-Uzbekistan Collaboration in Caringin Subdistrict, Bogor Regency
Full text linkMicro, Small, and Medium Enterprises (MSMEs) play a strategic role in the global economy, but face complex challenges related to regulatory compliance and risk management. A community service program themed "International Community Service: Building Bridges, Sharing Culture, Strengthening SMEs for Global Opportunities" was implemented in Caringin District, Bogor Regency, with the aim of increasing the capacity of MSMEs through Indonesia-Uzbekistan collaboration. Literature shows that the implementation of Enterprise Risk Management (ERM) and the ISO 31000:2018 standard can improve operational efficiency and competitiveness of MSMEs. The implementation method included data collection through surveys and Focus Group Discussions (FGDs), training, implementation assistance, data analysis using spider web analysis, and reporting of results. Participants were 10 MSMEs with the majority aged over 36 years, predominantly women (70%), and engaged in the food sector (60%). The results of the pre-test and post-test analysis showed a significant increase in all understanding parameters, especially regarding compliance and risk challenges which increased from 3.1 to 4.25. This program has successfully strengthened the managerial literacy of MSMEs and opened up opportunities for access to global markets through cross-border knowledge transfer and strengthening international networks
Survival Analysis Of Long Time To Recovery Of Covid-19 Patients Using The Antiviruses Remdesivir And Favipiravir Using The Kaplan-Meier Method
Full text linkThe coronavirus first appeared in Wuhan, China, in early December 2019. This virus is also known as Coronavirus disease 2019 (COVID-19). Based on the increasing number of COVID-19 cases and the high number of deaths, further research is deemed necessary. In this case, an effective treatment is needed to accelerate patient recovery. Two commonly used drugs are Remdesivir and Favipiravir. This study used the Kaplan-Meier method to evaluate the recovery time of COVID-19 patients based on two types of treatment: Remdesivir and Favipiravir. Survival analysis was conducted to compare the effectiveness of the two treatments in prolonging patient recovery time. The results showed a difference in effectiveness between the two types of treatment in terms of survival probability.
 
Comparative Analysis of the Altman Z-Score and Springate Models in Predicting Bankruptcy of Pharmaceutical Companies in Indonesia
Full text linkThe pharmaceutical industry is an important sector that not only focuses on making profit but also has a social responsibility to support public health. During the COVID-19 pandemic, this industry became much more active, especially in importing raw materials and producing medicines and health supplements. However, this growth also came with a large increase in debt, which raised the risk of financial problems. To deal with this, several bankruptcy prediction models have been developed, such as the Altman Z-Score and Springate models. These models are often used as early warning systems in many industries. Even so, research on bankruptcy prediction in Indonesian pharmaceutical companies is still limited. Therefore, this study aims to compare the two models in predicting bankruptcy in Indonesian pharmaceutical firms. The results show that the Altman Z-Score model is more suitable for long-term prediction, while the Springate model works better for short-term prediction
Land and Building Tax Revenue Model on Sub-District in Jambi City
Full text linkThis study aims to formulate a model of Determinants of Land and Building Tax revenue on Sub-district in Jambi City. This research applied the descriptive method by utilizing quantitative data. Time series data from 2020 to 2024 were used, as well as cross-section data from 11 sub-district in Jambi City. Panel regression analysis was used to examine the data for analyisis method. The result simultaneously showed that variable notification letters for land and building tax (SPPT), tax compliance, tax service, tax receivables, and tax digitalization significantly take effect on amount of Land and Building Tax revenue on sub-district in Jambi City with percentage of contribution on 99.09% during the 2020–2024 period. In partially, variable tax service, tax receivables, and tax digitalization have a positive and significant effect on amount of Land and Building Tax revenue in sub-district of Jambi City. Meanwhile, variable SPPT and tax compliance have no significant effect
The Influence of Entrepreneurial Orientation and Market Orientation on Business Performance Moderated by Government Support Policy
Full text linkThe objectives of this study are to analyze the moderating role of government support policy on business performance micro enterprises in the city of Bekasi with independent variables, namely entrepreneurial orientation and market orientation. This study uses a quantitative method with a non-probability sampling approach and purposive sampling technique, where the unit of analysis is the owner/leader of micro businesses. The number of samples that can be processed is 100 respondents. The collected data is analyzed using SmartPLS version 4. The findings of this study indicate that there is an influence of entrepreneurial orientation and market orientation on business performance. Government support policy was able to moderate the influence on business performance, but was unable to moderate the influence of entrepreneurial orientation on business performance. The theoretical implication of this study is that the moderating role of government support policy is a concrete manifestation of formal institutions that function as the main external context for the business performance of micro-businesses in the city of Bekasi. The limitations of this study are that the respondents were only owners/leaders of micro businesses in the Bekasi city area, with limited variables and research methods. Further research is recommended to involve more MSMEs with a wider geographical coverage, develop a research model with other exogenous variables, and be conducted using qualitative or mixed methods research
Value-at-Risk (VaR) Modeling of LQ45 Stocks Using the GARCH Approach
Full text linkThis study aims to model volatility and measure market risk of leading Indonesian stocks included in the LQ45 index using the GARCH approach. Daily closing price data from September 2022 to August 2025 were analyzed to estimate conditional volatility and Value-at-Risk (VaR) at 95% and 99% confidence levels. The GARCH model was selected to capture volatility clustering and conditional heteroskedasticity in stock returns. Residual distributions considered include normal, Student-t, and skewed-t to improve risk estimation, particularly for extreme events. Results indicate that most stocks are best modeled by GARCH(1,1) with a Student-t distribution, reflecting fat tails in return data. VaR estimates provide realistic maximum potential losses varying across stocks, with UNVR and ADRO showing relatively higher risk levels. Backtesting through Kupiec and Christoffersen tests confirms the accuracy and reliability of the GARCH-based VaR model for risk management. This study offers practical insights for investors and portfolio managers in understanding and managing risk exposures of top Indonesian stocks
Digital transformation and Public Procurement Performance: Analysing its Roles, Challenges and Opportunities in Developing Countries
Full text linkThough adoption and use of digital technologies among developing countries is not impressive, digital transformation in public procurement offers considerable benefits like to enhance effectiveness, transparency and accountability plus cost reduction. The intention of the study is to investigate the roles, challenges and opportunities for digital transformation in public procurement in Tanzania as a case for developing countries. In this study, the independent variables were, digital infrastructure (INF), IT competence of procurement staffs (CMP), digital processes (DP) and digital technology (DT), whereas dependent variable was procurement performance indicated by Benefit-Cost Ratio (BCR). A descriptive cross-sectional design was used. A self-administered semi-structured questionnaire was developed to gather data from 280 respondents selected from 40 government entities, and an interview guide to conduct interview to six heads of procurement department and six heads of ICT units from selected government entities. The collected data were analysed using descriptive, multiple linear regression model and content analysis. The findings demonstrate that the extent public agencies have digitalised their procurement activities is moderate. The results of regression analysis point out that INF, CMP and DP have positive and significant association with BCR, excerpt DT has negative and non-significant. Therefore, it was concluded that, improving INF, CMP and DP enhances performance of public procurement. Moreover, various challenges such as insufficient infrastructure to support digitalisation, restricted access to technology, and low level of technical expertise among procurement staffs have been identified. This study has filled a knowledge gap regarding the role digital transformation in public procurement plays in Tanzania, and developing countries. Based on the findings this study recommends the improvement of digital infrastructure and technology, capacity building of procurement staffs through training and development programs, improve accessibility of digitalised services and update regulatory and legal frameworks for optimum digital application
Analysis of the Impact of Tax Administrative Sanctions and Taxpayer Awareness on Taxpayer Compliance in the MSME Sector
Full text linkThis study investigates the influence of tax administrative sanctions and taxpayer awareness on taxpayer compliance in the Micro, Small, and Medium Enterprises (MSME) sector. Tax revenue plays a crucial role in supporting national development; however, taxpayer compliance among MSMEs in Indonesia remains relatively low despite their significant contribution to the economy. This condition highlights the importance of enforcement mechanisms and internal taxpayer factors in improving compliance behavior. Using a quantitative approach with a causal-comparative research design, this study involved 100 MSME business actors as both the population and sample. Data were collected through structured questionnaires and analyzed using IBM SPSS version 26. The analytical techniques applied included validity and reliability tests, classical assumption tests, multiple linear regression analysis, and hypothesis testing through partial (t-test) and simultaneous (F-test) analyses. The results demonstrate that tax administrative sanctions have a significant positive effect on taxpayer compliance, indicating that stricter and more consistent sanctions enhance compliance behavior. Taxpayer awareness also shows a significant positive effect on taxpayer compliance, suggesting that a higher level of understanding and consciousness regarding tax obligations encourages voluntary compliance. Simultaneously, tax administrative sanctions and taxpayer awareness significantly influence taxpayer compliance in the MSME sector