This study aims to determine the effect of variable interest rates and inflation on the credit system, namely Home Ownership Credit (KPR) using the ordinary annuity approach. This KPR can be influenced by several factors, especially the variable interest rate and inflation factors that affect the total monthly installments that must be paid by customers. In this study, the ordinary annuity approach is used to determine the KPR installment payments by taking into account fluctuations in variable interest rates and inflation. By looking at interest rate and inflation data from year to year. The results of this study indicate that inflation affects people's purchasing power while interest rates affect the amount of installment fees that must be paid. It is hoped that this study can help customers to understand the risks that can occur regarding KPR facilities in economic dynamics.

Micro MSMEs are the backbone of the economy. This study analyzes the effect of the amount of bank loans on the sales growth of micro MSMEs. Using a simple linear regression analysis method, this study shows that an increase in the amount of loans significantly contributes to the sales growth of micro MSMEs. These results emphasize the importance of wider credit access for micro MSMEs to support their sales growth. This study also indicates that changes in interest rates do not have a significant effect on the sales growth of micro MSMEs. The policy implications of these findings are the need for more inclusive and affordable financing programs for micro MSMEs, as well as increasing their access to various alternative funding sources.

Gambling in casino games is an uncertain business because it creates two possibilities between the hope of winning or the risk of losing. The risks faced by casinos are usually analyzed using the Risk of Ruin (ROR). The main focus of this study is to apply the mathematical model of ROR using the Poisson distribution to model random events in gambling by considering the house advantage (a) and the law of large numbers. This study discusses the relationship between variables, such as maximum bet limits and cash flows and examines how these factors affect the risk of casino bankruptcy. In its business characteristics, casinos operate as gambling business entities and utilize the house advantage to achieve their financial benefits. House advantage indicates the profitability of the casino. However, the uncertainty of this gambling can pose a risk of bankruptcy for them. In this study, the house advantage is included in our model for several popular casino games. In addition, a set of full-range scales is defined to facilitate effective assessment of the level of risk faced by the casino, considering its regulatory context. This study also uses the binomial random walk model to describe the race between the casino and the gambler, where each step has two possible outcomes, namely winning or losing. The results of this study are expected to provide insight into the risk in calculating risk in optimizing betting decisions and reducing the risk of bankruptcy.

The concept of aggregate loss models pertains to a stochastic variable representing the total sum of all losses encountered within a set of insurance policies. In the non-life insurance sector, it is employed to assess the potential losses that an insurance company may face when claims made by policyholders exceed the allocated claim reserves. The purpose of studying aggregate loss models is to ascertain risk measures such as standard deviation of premium principles, value at risk (VaR), and conditional tail expectation (CTE). These steps aid insurance companies in the management and quantification of risks associated with aggregate losses. The standard deviation of premium principles is calculated analytically by substituting expected values and variances, while VaR is estimated using the Monte Carlo method to determine quantile values and confidence intervals. CTE is evaluated by computing the average losses that surpass the VaR threshold. These distributions and parameters require the Pareto distribution, which characterizes claim sizes, and the Poisson or Negative Binomial distribution, which factors in the number of claims. It is crucial to carefully consider the selection of the appropriate distribution, as it plays a significant role in determining the accuracy and reliability of the model. Furthermore, other influencing factors, such as loading factors and confidence intervals, should also be taken into account. These factors have the potential to significantly impact the quantification of risk arising from the model.

Every insurance company undoubtedly seeks to gain profit, and one of the avenues for profit comes from premium reserves, which represent the amount of money held by the insurance company during the coverage period. Various methods, including the Frackler method employed in this study, are utilized to calculate premium reserves. In the calculation process, the author requires the premium value and the sum insured paid, inputting them into the Frackler method formula. The research findings indicate that the age of an insured individual at the time of enrolling in endowment life insurance influences the premium value. Consequently, it can be concluded that as the age of the insured increases, the premium reserve required for the policy tends to be higher.

The Covid-19 pandemic entered Indonesia in March 2020, so the government imposed restrictions on people's movement in various regencies. The imposition of restrictions on people's movement will have an impact on the economy to the point of poverty. Poverty is influenced by several factors such as population, health, education, employment and economic factors. The poverty of a district/city in Indonesia is grouped to assist the government in alleviating poverty more efficiently. The process of grouping data in data mining is to group districts/cities in Indonesia based on factors that affect poverty with the K-Medoids and CLARA algorithms, then compare the two methods based on the average value of the ratio of the standard deviations. The variables used in this study consist of 4 variables, namely human development index (HDI), gross regional domestic product (GRDP), unemployment rate, and population density. The results of this study indicate that using the K-Medoids obtained 2 clusters, while using the CLARA algorithm obtained 3 clusters. Based on the results of grouping the two algorithms, the best algorithm was obtained using cluster validation, namely the CLARA algorithm because it has the average value of the ratio of the smallest standard deviation of 0.106.

Developing a business is a manifestation of growth activities that will be the key to success in going through the continuity of a business. It becomes the basic basis for making decisions that are important for company policy in good situations or in unpredictable situations such as the covid 19 pandemic. A leader in a medium-sized business of course pays attention to all aspects of support that make the decision device taken by paying attention to reactions occurring both internally and in the market. You will see the character of a leader who is ready to face a crisis, especially in adapting information technology as part of the relocation of businesses to digital caused by the difficulty of penetrating the market directly. Researching how many medium-sized business owners in Bandung are adapting the use of information technology as a means of business in 2020-2022. As a result of the leadership crisis, it is feared that it can have an impact on the running of the business by analyzing qualitatively that the behavior of an agile leader will have an impact on the use of information technology in their business. For that it can be seen how much a leader is able to adapt or in other words he is able to accept changes quickly and apply them in his business. For this reason, this research is expected to be a reference tool in terms of leadership characteristics in dealing with crises due to the pandemic or post-Covid-19 pandemic.

The low nutritional status of toddlers indicates a non-optimal level of health. Family empowerment is the key to toddler care to improve nutritional status. Kia books are an excellent medium for monitoring nutritional status (Susilo et al., 2021). Cibeet Village is the village with the highest cases of malnutrition in the Ibun health center area of Bandung regency with toddler visits to posyandu only 50%. MCH books were used in this study to monitor the nutritional status of toddlers. The study was designed using an analytical crossectional study, with a sample of 57 mothers under five and family. Samples from each of these villages were randomly selected and re-selected from each posyandu. Data related to the use of Kia books by families are carried out through observation of family members and direct measurement of nutritional status. The results showed that mothers of toddlers who used MCH books periodically were 42.1%, mothers were family members who used MCH books 89.5%, nutritional status of toddlers 84.2% were bai k nutrition. Based on the analysis of the relationship between the use of MCH books and the nutritional status of toddlers, a p-value (0.00 0) was obtained, < with an alpha value (0.05). Thus there is a relationship between the use of MCH books and the nutritional status of toddlers. There is a relationship between the use of kia books and toddler caregivers obtained p-value (0.00 4) < alpha value (0.05). Kurang from half of the families of toddlers have not used the MCH book as a medium for determining the nutritional status of toddlers and there are still toddlers with malnutrition, in Cibeet village, the working area of the Ibun Health Center. Efforts are needed to empower families in utilizing Kia books so that family participation increases in maintaining family health.

A linear equation is an equation in which each term contains a constant with a variable of degree one or single and can be described as a straight line in a Cartesian coordinate system. A Linear equations system is a collection of several linear equations. A system of linear equations whose coefficients and variables are fuzzy numbers is called a fully fuzzy linear equation system. This study aims to apply a metaheuristic algorithm to solve a system of fully fuzzy linear equations. The objective function used is the minimization objective function. At the same time, the metaheuristic algorithms used in this research are Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and Cuckoo Search (CS). The input in this research is a fully fuzzy linear equation system matrix and parameters of the PSO, FA, and CS algorithms. The resulting output is the best objective function and the variable value of the fully fuzzy linear equations system. The work was compared for accuracy with the Gauss-Jordan elimination method from previous studies with the help of the Matlab programming language. The results obtained indicate that the Particle Swarm Optimization (PSO) algorithm is better at solving fully fuzzy linear equation systems than the Firefly Algorithm (FA) and Cuckoo Search (CS). This case can be seen from the value of the resulting objective function close to the value of the Gauss-Jordan elimination methodKeywords: Mathematics, investation

One of the assumptions in ordinary least squares (OLS) in estimating regression parameter is lack of multicollinearity. If the multicollinearity exists, Partial Least Square (PLS) and Principal Component Regression (PCR) can be used as alternative approaches to solve the problem. This research intends to compare those methods in modeling factors that influence the Human Development Index (HDI) of North Sumatra Province in 2019 obtained from the Central Bureau of Statistics. The result indicates that the PLS outperforms the PCR in term of the coefficient of determination and squared error