Antecedents of Using Financial Software Applications on MSME Sustainability in Banyumas Regency during the Covid-19 Pandemic

The Covid-19 pandemic has had an impact on various economic sectors in Indonesia, and consequently on Micro, Small, and Medium Enterprises (MSMEs) which have faced a decline in sales figures. The pandemic has forced MSME actors to reorganize their business strategies. Several MSMEs that could survive the impact of Covid-19 in Banyumas have implemented Technology-Based Financial Management which includes the use of software in managing their financial data so that MSME actors are able to calculate, manage, budget, predict expenses and profits to be achieved. The long-term goal of this research is to enrich the development of science, particularly, to examine bounded theory as the dominant factor influencing the intention of MSME actors in using financial software. Further, this research analyzes whether the financial software developed by the research team could help the process of MSME operational activities and has an impact on the sustainability of MSMEs during the Covid-19 Pandemic. Data collection for this study was carried out by distributing questionnaires through online media to MSME actors in the Banyumas Regency who were respondents and a direct approach to MSMEs concerning the use of financial software. The random sampling technique has been applied for this research, meanwhile, for data analysis the Statistical Product and Service Solution (SPSS), version 22.0, has been used. The expected results from this research may help to analyze and provide empirical evidence that bounded theory is the dominant factor influencing the intention of MSME actors in using financial software. The output of this paper can contribute to knowledge, especially regarding the implementation of financial software and theory development.

87 Validation of a Costing Algorithm in the Neonatal Intensive Care Unit and Identification of Cost Drivers for Neonates

Primary Subject area Neonatal-Perinatal Medicine Background Neonatal Intensive Care Units (NICUs) account for over 35% of pediatric in-hospital clinical costs, thus implying that a better understanding of care expenditures within these units is the first step for improving efficiency of care. The Canadian Neonatal Network (CNN) algorithm is the first to provide case-specific costs based on resource usage among preterm infants born < 37 weeks but has not yet been validated for other populations in the NICU. Objectives To validate the CNN costing algorithm in six case-mix categories with real-time costs obtained from hospital-specific financial software (CPSS) in a tertiary-level NICU and assess the variations in proportion of cost centers across case-mixes. Design/Methods A retrospective cohort study of all patients admitted within 24h of birth to a Level 3 medico-surgical NICU 2016-2019. Patient demographics, clinical information and CNN predicted costs were obtained from the CNN database. Real-time costs were obtained from the hospital financial software (CPSS). Total and daily costs were compared between sources using Pearson correlation coefficient (r) and paired Student’s t-test. Costs were adjusted to account for inter-institutional and -provincial price variations using the Cost of Standard Hospitalization Stay from the Canadian Institute for Health Information. Proportions of each cost center across the different case-mix categories were compared using Chi-square analyses. Results Among the 1795 live infants admitted into the NICU, 167 (9.3%) were < 29 weeks gestational age (GA), 193 (11%) were 29-32 weeks GA, 457 (25.5%) were 33-36 weeks GA, 144 (8%) had major congenital anomalies, 179 (10%) were term infants diagnosed with Hypoxic-Ischemic Encephalopathy (HIE) and 672 (37%) were term infants with no HIE or major congenital anomalies. Median NICU costs varied according to each case-mix from $10,025 for term infants without HIE or congenital anomaly to $180,145 for infants born < 29 weeks (Figure 1). Despite high variation in total NICU costs, there were small variations in median daily costs (range: $1,312-$1,941). Overall, the CNN algorithm strongly correlated with CPSS total costs across all 6 case-mix categories (r range 0.90-1.00, p-value < 0 .01) (Figure 2). We report a consistent strong predictive performance of the algorithm in 5/8 pre-specified cost centers among preterm infants (r range 0.77-0.99, p-value < 0 .01). Unit producing personnel (nurses and physicians) consistently comprised the largest proportion of total costs (64-78%) for all case-mix categories. Conclusion The CNN algorithm accurately predicts NICU total costs for six case-mix categories. Costs per day were comparable across different case-mix categories, and unit producing personnel represented the highest proportion of costs suggesting that reductions in length of stay would be the most efficient method to reduce NICU costs.

The Case for Agile Methodologies against Traditional Ones in Financial Software Projects

Agile methodologies have emerged to challenge traditional ones and overcome their limitations. Increasingly, software development organizations are scaling agile practices in order to meet the requirements of the quickly changing and regularly developing business environment. The main objectives of this study are to investigate the main differences between the traditional project management methodologies and agile methodologies, as well as to identify some key advantages and challenges of applying agile development in a financial software environment. The findings clearly show that using Agile methodologies in a financial software development environment increases the efficiency and transparency of the development process, as well as the stakeholders’ satisfaction, but the project managers must know how to adapt different Agile frameworks to the given context of their organization.

Pendayagunaan Software Asisten Dalam Pengelolaan Sistem Informasi Manajemen Keuangan Sekolah

This study aims to determine the management of the school's financial management system in Madrasah Aliyah Al-mu'awanah and the implementation of Assistant software utilization in the management of the school's financial management system in Al-Mu'awanah Madrasah. This research uses an approach to research and development (R & D) research. Research results show that in practice financial management in Madrasah Aliyah Al-mu'awanah is still based on a manual input data system so that in the process there are obstacles especially in data processing and school financial data recapitulation. Implementation of the use of assistant software in the process of school financial information management provides a positive picture, the statement is reinforced by the presence of a good response from respondents. Based on the distribution of the questionnaire that has been given to the respondents, the percentage of eligibility is 84%. The percentage of feasibility obtained shows that the utilization of computerized software or financial software is feasible to be used as school financial administration software, especially in Madrasah Aliyah Al-Mu'awanah.

A Bradley-Terry Model-Based Approach to Prioritize the Balance Scorecard Driving Factors: The Case Study of a Financial Software Factory

The prioritization of factors has been widely studied applying different methods from the domain of the multiple-criteria decision-making, such as for example the Analytic Hierarchy Process method (AHP) based on decision-makers’ pairwise comparisons. Most of these methods are subjected to a complex analysis. The Bradley-Terry model is a probability model for paired evaluations. Although this model is usually known for its application to calculating probabilities, it can be also extended for ranking factors based on pairwise comparison. This application is much less used; however, this work shows that it can provide advantages, such as greater simplicity than traditional multiple-criteria decision methods in some contexts. This work presents a method for ranking the perspectives and indicators of a balance scorecard when the opinion of several decision-makers needs to be combined. The data come from an elicitation process, accounting for the number of times a factor is preferred to others by the decision-makers in a pairwise comparisons. No preference scale is used; the process just indicates the winner of the comparison. Then, the priority weights are derived from the Bradley-Terry model. The method is applied in a Financial Software Factory for demonstration and validation. The results are compared against the application of the AHP method for the same data, concluding that despite the simplifications made with the new approach, the results are very similar. The study contributes to the multiple-criteria decision-making domain by building an integrated framework, which can be used as a tool for scorecard prioritization.