The poverty becomes a serious problem because of the impact it causes. The factors that affect poverty are economic growth, low education, the limitation of natural resources, the limitation of employment opportunities, capital, and family burdens. All of these factors constitute a vicious circle in the problem of poverty. The problems studied are lag-1 investment, lag-2 investment, employment opportunities, and provincial minimum wages and their effects on the poverty rates in Riau Province, Indonesia. The fundamental problem faced by Riau Province today is the high level of poverty amidst government policies that have not met the expectations. The purpose of this study is to analyze government policies in order to reduce the poverty. The research method used was an explanatory study or hypothesis testing study that aims to explain and test hypotheses for the relationship among variables. The relationship described is a causal (cause-effect) relationship. The data were arranged in the form of time series during 1997-2018. The research model was formulated as a linear function based on the Nerlove's Partial Adjustment Model approach and was recursively analyzed using linear regression through the Ordinary Least Square (OLS) method. The findings of this research model are lag-1 investment, lag-2 investment, employment opportunities, and provincial minimum wages have a significant effect on the poverty rate in Riau Province.

The indicators of success in macro development can be measured from the economic growth, which is reflected in changes in the Gross Regional Domestic Product (GRDP). The factors which affect the economic growth are very complex. This study analyzes the economic growth and the factors that affect Sumatra island. The data used is panel data with descriptive analysis techniques and multiple linear regression. Based on the research results: Education, economic openness, road infrastructure, and investment have a positive and significant effect on economic growth and poverty and unemployment have a negative and significant effect on economic growth. Besides, the results of panel data explained that the openness of the economy to economic growth is very low, while the highest is education.

One of the main goals of every individual or household is to achieve financial well-being. Previous research has shown that various factors influence financial well-being. This research aims to develop an integrated family financial welfare model by examining various factors that affect it. This study uses data of 1,158 households taken using an online survey. The data is analyzed using a structural equation model. The results show that financial experience, financial knowledge, financial status, and marital status directly affect financial well-being. Financial behavior significantly mediates the influence of financial behavior, financial knowledge, and locus of control on financial well-being. Furthermore, marital status strengthens the effect of financial knowledge on financial well-being, but it does not strengthen the effect of financial experience on financial well-being. This study suggests that the Government and financial authorities need to improve further the effectiveness of financial literacy and financial inclusion programs and campaign for a more frugal life among households to avoid financial difficulties.

The aim of this research was to evaluate the impact of decentralization and electronic participatory budgeting on managerial performance. Additionally, the study sought to investigate the management accounting system's role in strengthening the effect of decentralization and electronic participatory budgeting on managerial performance. This quantitative research involved 30 regional units, using primary data collected through questionnaires of 108 fund management officials. The findings of this study demonstrated that decentralization and electronic participatory budgeting both have a positive and significant effect on managerial performance. Furthermore, the management accounting system was found to act as a moderator between decentralization and performance, but not between electronic participatory budgeting and performance.

Tuberculosis (TB) is still a major public health concern in many regions of the world, including Indonesia's West Java Provinces. Accurate TB risk factor prediction can enhance overall TB control efforts by directing focused therapies. In this study, utilizing a combination of Negative Binomial Mixed Models (NBMMs) and Feed-Forward Neural Networks (FFNNs), we offer a unique method for the predictive modeling of TB risk variables. A variety of sociodemographic, behavioral, and environmental factors that are known to be linked to TB are included in the dataset utilized in this investigation. To correct for overdispersion and include both fixed and random effects in the model, we first fitted an NBMM major problem in epidemiological investigations is modeling count data with overdispersion, and the NBMM component of the model offers a versatile and effective framework for doing so. Following that, we include an FFNN component in the model, which helps us to detect relevant predictive features and alter the model's weights accordingly. Backpropagation methods are used by the FFNN to adjust model parameters and enhance accuracy. The resulting Negative Binomial Mixed Model Neural Network (NBMMNN) model has a high accuracy value of up to 0.944. Our research suggests that the NBMMNN model outperforms conventional models that are frequently used to predict TB risk factors. By contrast to simpler models, the NBMMNN model can capture complicated and nonlinear interactions between predictors and outcomes. Additionally, the inclusion of random variables in the model enables us to take into account potential sources of variability in the data as well as unmeasured confounding. This work emphasizes the opportunity to enhance TB risk prediction and control efforts by integrating NBMMs with FFNNs. In West Java Provinces and other comparable contexts, the NBMMNN model might be a helpful tool for identifying and resolving TB risk factors, guiding targeted interventions, and enhancing overall TB control efforts.

This study investigates the effect of perceived risks, i.e., financial risk, product risk, and convenience risk, as well as the COVID-19 pandemic situation on online shopping behavior among Malaysians. This study uses convenience sampling techniques and comprises 185 respondents who have experience buying online. In addition, the study setting was non-contrived, and data was gathered using a closed-ended questionnaire through an online survey. Descriptive analysis was conducted using SPSS version 25.0 software and SmartPLS version 3.2.8 to test the proposed hypotheses. This study found that perceived risk factors such as financial, product, and convenience risk did not influence online shopping behavior. In contrast, the COVID-19 pandemic positively influences online shopping behavior among consumers. It showed a new development in the theory of online shopping behavior, where users continue to make purchases despite being aware that there may be various risks due to the spread of COVID-19. The role of the ministry, business owners, and consumer associations needs to be given attention to form a sustainable electronic commerce system and protect the rights of consumers. This research can help consumers understand their rights.

Gold is one of the most attractive commodities and popular investments. Investment experts often recommend investing in gold because gold is one of the safest investments. It is a stable classic hedge, although the conditions of currency volatility or global markets are depreciated. However, the gold price fluctuations can be influenced by some other factors, such as the USD Index, which reflect and measure the strength of the US Dollar currency, and the Index of Dow Jones Industrial Average (DJIA) or a reflection of the political and economic conditions of the stock market. In this study, we conduct a global gold price forecast (USD) based on the USD Index, the DJIA Index, and the influence of time trends. Based on the data's characteristics, we face the fact that the data is nonlinear, contains outliers, and its pattern is not easy to specify parametrically. Due to the complexity of the model, we then propose a more flexible, robust modeling technique called the Bayesian Nonparametric Quantile Generalized Additive Model method. According to the results for the median case, the proposed method shows an accurate forecasting category due to the value of the Mean Absolute Percentage Error, MAPE less than 10 percent.

Companies today strive to integrate manufacturing processes with the environment to strike a balance. This study aims to examine the impact of green implementation for companies on the performance of manufacturing companies. Data was collected using Google Forms distributed online to the manufacturing companies domiciled in East Java. The criterion for the companies is that they have been committed to implementing a green approach to the production process, procurement of environmentally friendly raw materials, and green products. The partial least square technique analyzed data from as many as 115 respondents, with the position as senior staff level and higher, who have worked for at least two years and are permanent employees. The results showed that the implementation of eco-design has an impact on green purchasing and green manufacturing. Eco-design and green information systems implemented by the company can improve manufacturing performance by producing adequate overall product quality, and the number of products produced varies according to market demand. Therefore, the green information system affects green manufacturing and purchasing in manufacturing companies. Therefore, green manufacturing and green purchasing can impact manufacturing performance. The research results contribute to practitioners, especially top management, in committing to implementing Green which affects the performance of manufacturing companies. The theoretical contribution of the research is to enrich green supply chain management and sustainable performance for manufacturing companies.

The purpose of this study is to analyze the influence of digital marketing, word of mouth, and service quality on purchasing decisions through a quantitative questionnaire using an accidental sampling method. The research is designed to find out the relationship between the influence of digital marketing, word of mouth and service quality on consumer purchasing decisions using a quantitative approach method. The variables in this study consist of independent variables and dependent variables. The variables studied include digital marketing, word of mouth, service quality and consumer purchasing decisions. The research was conducted at food SMEs in Jakarta, Indonesia. Sources of data in this study were primary data including consumer responses to digital marketing, word of mouth, service quality and purchasing decisions obtained from the results of distributing online questionnaires. The sample size used in this study was 680 people. The data collection method used in this study was an online questionnaire distributed by social media. The data were analyzed using SPSS software and structural equation modeling (SEM) with SmartPLS software tools. The results of this study indicate that the higher the digital marketing, word of mouth, and service quality, the higher the purchasing decision. SMEs must further optimize the use of digital marketing in marketing their companies such as uploading interesting content on one of the existing social media. From a word-of-mouth point of view, companies must promote more to their closest circle of benefits what they get from using SEMs products. Service quality must continue to provide excellent service to consumers or customers so that these consumers feel comfortable and satisfied.

Plastic bags are used by many people because they are inexpensive, lightweight, durable, and waterproof. Plastic bags, on the other hand, do not break down and can pollute the environment if not handled properly. Indonesia produces a lot of plastic waste and is one of the top ten countries that has a problem with plastic waste. In this study, we used three months of data of real transactions from a grocery store. This study shows how the decision tree can identify patterns on plastic bag usage at a small grocery store by using demography and products purchase. The attribute weights showed that in the hometown, the total of several products bought were the factors that affected the use of plastic bags.