Analysis of the Factors Affecting Poverty in Padasari Village

This study aims to determine the factors that cause poverty in Padasari Village, Cimalaka District, and Sumedang Regency, separately or simultaneously. This research uses quantitative methods with multiple descriptive and linear approaches. Determination of the sample in this study using the Slovin model. Data processing techniques are carried out through validity and reliability tests. Data were analyzed using the SPSS application. The results of the study show that if not adequately managed, natural resources can have a negative impact on poverty levels, human resources involve the quality and quantity of a region's workforce, and human resources who do not have access to education, skills, and training will be difficult for them to obtain welfare.


INTRODUCTION
The rate of increase in gross national product (GNP), both as a whole and on an individual basis, was the sole criterion by which economic growth was evaluated during the conventional economic era (Mahendra, 2017). It is assumed that an increase in GNP will naturally result in the creation of jobs and a variety of other economic opportunities, which will eventually promote the many conditions required to produce a more fair distribution of the rewards of economic and social growth (Achmad et al., 2022;Fretes, 2017). The term "trickledown effect" refers to this fundamental concept. In the meantime, the new economic view maintains that the primary objective of economic development is not only the expansion of the gross national product (GNP), but also the reduction of poverty, the elimination of income inequality, and the provision of employment within the context of an ever-expanding economy (Hanandita & Tampubolon, 2016;Todaro, 2000).
The problem of both natural and human resources is an important issue in development, because on the one hand it becomes an asset or capital for development, on the other hand it can become a burden for development. The resources owned must be of good quality in order to provide a multiplier effect for improving the economy (Achmad, 2022a;Prasetyo, 2008). Conversely, the low quality of resources can be one of the causes of low income, which has an impact on the income middle trap in Indonesia. The dimension of human development in Indonesia emphasizes education, health and mental revolution. Where the problem of poverty and unemployment is the implication (Saputra, 2017).
Even in some developing countries, low education is one of the causes of poverty problems in the economy. Kurniawan & Managi (2018) proves that the sources of poverty traps in Indonesia are education, health, geographic conditions, total assets and social capital. Poverty is a national problem that is urgent to be resolved, poverty is in plain view the root of many social problems in Indonesia (Nasution, 2014). Poverty is persistent or tends to last from time to time. Even the SDGs (sustainable development goals) with the aim of being a continuation of the MDGs (millennium development goals) continues to prioritize the problem of poverty as a development goal (Achmad, 2022;Ishatono & Raharjo, 2016). The problem of poverty is one of the MDGs agenda that has not been resolved until 2025.
Indonesia's rapid economic growth in the last decade relative to regional countries has not been able to significantly reduce poverty levels. Indonesia's economic growth driven by the household consumption sector has not produced quality economic growth that can significantly reduce poverty and create broad employment opportunities, and has not eliminated the level of disparity between the rich and the poor (Prianto, 2020).
Complexity of the poverty issue necessitates integrated policies and strategies, such as programs to increase productive employment opportunities, human empowerment, and ease of access to existing socioeconomic opportunities (Indra, 2001). Due to various government constraints, poverty alleviation programs and poverty-focused policies require a priority scale. Poverty has been exposed and is the topic of extensive discussion. The various definitions of poverty reflect a spectrum of ideological perspectives. Even a quantitative approach to defining poverty has been heavily debated by a number of scholars with an interest in this topic.
Poverty, according to Suparlan (2000), is the complete lack of valuable assets and objects suffered by a person or group of people who live in an environment that is all poor or lacks capital, in terms of money, knowledge, social power, politics, the law, and access to facilities. Public services, economic possibilities, and employment. Moreover, poverty is a condition in which individuals or groups lack the ability, freedom, assets, and access to meet their future needs, and are extremely vulnerable to risks and pressures caused by disease and sudden increases in the cost of food and school fees.
According to the target population, there are several sorts of poverty. This classification of types of poverty is intended to ensure that each program objective has distinct aims and objectives. Sumodiningrat, (1999) categorizes poverty into three groups: (1) Absolute poverty (income below the poverty line and unable to meet basic needs), (2) Relative poverty (poverty situation above the poverty line based on the distance between the poor and non-poor in a community), and (3) Structural poverty (this poverty occurs when people or groups of people are reluctant to improve their living conditions until there is assistance to push them out of these conditions).
Sumedang Regency is a district that is currently pursuing development. The goal of development itself is to create community welfare and bring services closer to the community. Even though the government's goals are noble, social problems in the form of an imbalance in income distribution, problems with education services, health services, illiteracy, stunting, illegal labor, all of which lead to the problem of community poverty, still exist in the community. Poverty is believed by Soesilo et al. (2008); Yudhistira & Sofiyandi (2018) that the greatest poverty is in rural areas, therefore there are policies that can be a solution for the community.
Padasari village in Sumedang district is one of the portraits of the community's inability to meet basic needs and other needs. Most of the people of Padasari village live by depending on the agricultural sector. The community's agricultural pattern is traditional and the orientation of crops is short-lived crops such as rice, corn, beans. The orientation of the farming system is for self-consumption and not market-oriented due to the limited production scale. The lifestyle of the people has been passed down from generation to generation until now and the processing approach has not shifted in line with advances in science and technology. The impact is limited production capacity, self-consumption for households in the short term, people's incomes decrease and are uncertain, as a result many people are still in the poor category. The World Bank's poverty measure is income of less than US$2 per day. Meanwhile, the poverty measure used by the Indonesian government is those who have an income of less than US$1 per day for urban residents and 80 US cents per day for rural residents (Majid et al., 2019;Soesilo et al., 2008).
Another description that supports the argument is that most of the Padasari village community are recipients of government social assistance in cash for parents (BLT), community health insurance assistance (Jamkesmas) and educational assistance for school children. The aim is for the general public and school children to serve as a stimulus for fulfilling the right to education, health, food, sanitation and clean water. Various real government programs for the poor continue to be carried out with assistance programs for recipients of livable housing, assistance for animals or pets such as cows and goats as a support for the family's future.
Efforts made by the poor to get out of poverty through various approaches. The triggers for community poverty are due to limited natural resources because rainfall has a very short time limit, human resources due to minimal creation of taking advantage of economic opportunities, minimal economic infrastructure such as markets and regulatory factors that are not in favor of small communities. The research objective was to determine the effect of natural resources, human resources and infrastructure on poverty partially.

METHODS
A quantitative methodology was utilized for this study. Padasari Village, which is located in the Sumedang Regency, was the location where the research was carried out. After doing the calculations with the Slovin formula, it was determined that the study had a population of 175 people, while the sample size was 100 people. Additional sources of corroborating evidence include secondary data obtained from the Padasari village office, which pertain to data on poverty and other data. Simple linear regression and multiple linear regression are the two types of analysis tools that are utilized here. It is possible to Multietnik di Desa Sea determine the effect of the independent variable (X) on the dependent variable (Y) partially and simultaneously with the help of the analysis tool. Data analysis used is descriptive statistics and multiple regression. Descriptive statistics to describe the data, multiple regression is used to measure the effect of the independent variables on the dependent variable. The testing steps in this study are the Validity and Reliability tests. Then, the Classical Assumption test was carried out including the Normality test, Multicollinearity test and Heteroscedasticity test, as well as the Autocorrelation test (Deny, 2008).
After that, multiple linear regression testing was carried out by looking at the F statistical test if the sig. < 0.05, the research model is considered feasible and it can be concluded that there is a simultaneous influence of all independent variables on the dependent variable. Meanwhile, in the t test if the sig. each independent variable < 0.05, it can be concluded that partially the independent variables have an influence on the dependent variable (Ghozali, 2013). The description of the findings in this study is used to measure how indicators can represent variables in several criteria.

RESULTS AND DISCUSSION
Natural resources have an impact on the lives of living things around or in other words natural resources have an important role in life including humans and other needs. Likewise, uncontrolled exploitation will have an impact on the environment and the sustainability of humans and other living things. As stated by Ilyasa et al. (2020);Wijaya et al. (2020), that excessive exploitation of natural resources creates a serious effect on the poverty level of the surrounding community. This is because natural damage affects the availability of water sources, drought, erosion and agricultural production capacity has decreased drastically.
The results showed that the poverty of the Padasari village community was due to excessive resource exploitation due to traditional and shifting agricultural patterns. The effect is that drought always hits agricultural areas and possible actions for the development of market-based agricultural cultivation are very limited. The majority of the people who work as farmers can only utilize short-lived agricultural crops (rice, corn and beans) for a limited period of time because the rainy season is very short. The following is the result of an analysis of the factors that influence the level of poverty in Padasari Village, Sumedang District (Table 1). The value of the correlation coefficient (R) between the variables of natural resources and the poor is 0.045, this means that the relationship between natural resources and the poor has a very weak relationship. Furthermore, the R Square value (coefficient of determination) is 0.002, meaning that the variation that occurs between the high and low levels of the poor population of 0.2% can be explained by natural resources and the remaining 99.8% is explained by other variables.
Unstandardized Coefficients obtained a Constant value of 2.443 and a natural resource coefficient value of 0.087 explaining that if natural resources change by 1 unit, then the poor population changes by 0.087 units, meaning that the size of the poor population variable (y) is influenced by the source variable natural resources (x1) of 8.7% and the remaining 91.3% is influenced by other x variables which are not included in this research model. while the value of 2.443 means that if there is no change in the value of the natural resource variable, then the poor population variable will remain at 2.443. This value is used to test the regression coefficient, which determines whether or not natural resource variables have a significant effect. This is done by comparing the calculated t value with the t table value or probability (Sig) at a level of 0.05, and the t value is used to test the regression coefficient. With a confidence level of 95%, the results of the analysis show that the t value for the natural resource variable is lower than the t table (0.459 < 1.983), which indicates that the hypothesis is not supported, which indicates that the natural resource variable does not have a significant impact on those who are economically disadvantaged.
These results contradict the findings of Ilyasa et al., (2020), which indicate that if natural resources increase, the poor population will decrease, and if natural resources decrease, the poor population will increase. This is supported by the hypothesis that natural resources have a negligible impact on the poor, given that the area of land owned by the poor, the number of livestock owned by the poor, and the quantity of crops owned by the poor are all extremely low. such that the number of poor will remain constant or increase from year to year. According to the forms of poverty theory According to Hadi et al., (2015) ;Todaro, (2000), there are two forms of poverty based on their nature: Natural poverty is caused by a lack of natural resources, while artificial poverty is the result of a modernization system that deprives people of many opportunities to use existing resources.
Another factor that has no less influence on community poverty is human resources. Aziz et al. (2016) said that human resources have a strategic role in development. This means that in tackling poverty, the human resource factor is important in finding solutions. The results of research and analysis of human resource data on poverty in Takarai village are shown in Table 2. The value of the correlation coefficient (R) between the variable human resources and the poor is 0.089, this means that the relationship between human resources and the poor has a very weak relationship. Furthermore, the value of R Square (coefficient of determination) is 0.0079, meaning that the variation that occurs between the high and low levels of the poor is 0.79%, which can be explained by human resources and the remaining 99.21% is explained by other variables.
Unstandardized Coefficients obtained a constant value of 2,433 and a human resource coefficient value of 0.127. It was explained that if human resources changed by 1 unit, then the poor population changed by 0.127 explaining that the variable size of the poor (Y) was influenced by the human resource variable (X2). of 12.7% and the remaining 87.3% is influenced by other X variables which are not included in this research model. While the value of 2.433 means that if there is no change in the value of the human resource variable then the poor population variable will remain at 2.433. This value is used to determine whether or not the human resource variable has a significant effect on the regression coefficient by comparing the estimated t value to the t table value or probability (Sig) at a significance level of 0.05. The results of the analysis indicate that the t value for the human resource variable is less than the t table (0.089 < 1.983) at the degrees of freedom with a 95% confidence level, or the probability value is 0.363 > 0.005, therefore the hypothesis is rejected and the resource variable is not significantly related to the dependent variable. Humans have a negligible impact on the poor. Sumarsono, (2009) asserts, based on his thesis, that human resources have an effect on the impoverished since human resources include people who are able to provide services or employment. Being competent to work entails being responsible for performing actions with economic value; these activities provide goods and services to satisfy societal requirements. On the basis of the preceding statement, it is possible to conclude that human resources are not important for the poor, as there are other factors that affect the poor, such as the distance between the school and their place of residence, which leads to a sense of hopelessness and a lack of sufficient funds, so that many poor people still rely on primary school education. According to the notion, those with a higher level of education will have access to good positions and high incomes.
Another factor that contributes to reducing the poverty rate is the availability of infrastructure as an important indicator (Purnomo et al., 2021). The availability of natural resources and the readiness of human resources without the support of infrastructure, the production results will not have use value (Table 3). The value of the correlation coefficient (R) between the infrastructure variable and the poor is 0.254, this means that the relationship between infrastructure and the poor has a weak relationship. Furthermore, the R Square value (coefficient of determination) is 0.065, meaning that the variation that occurs between the high and low levels of the poor is 6.5%, which can be explained by Infrastructure and the remaining 93.5%, explained by other variables.
The constant value of 1.331 and the infrastructure coefficient value of 0.433 can be explained in the following way: if there is a change of one unit in the infrastructure, then there is a change of 0.433 in the poor population. This indicates that the magnitude of the poor population variable is influenced by the infrastructure variable by 43.3%, while the remaining 56.7% is influenced by other X variables that are not included in the research model. In the meantime, the value of 1.331 indicates that the value of the variable representing the impoverished population will remain unchanged at 1.331 even if there is no change in the value of the infrastructure variable. The findings of the study indicate that the actual t value for the education level variable is higher than the t table value (0.254>1.983) in degrees of freedom. This indicates that the hypothesis can be accepted, which indicates that the variable does in fact have a relationship with education level. The lack of adequate infrastructure has a huge impact on those who are less fortunate.
Because infrastructure is the engine that drives economic expansion, it has an impact on low-income communities, as stated by (Mardiana et al., 2018). The development of infrastructure as the primary support for social and economic systems takes place within an environment that is both interconnected and comprehensive. It is impossible to disentangle the movement of a country's economic growth rate from the availability of infrastructure, which includes things like transportation, telecommunications, energy, and sanitation, among other things. The expansion of this industry must come first since it lays the groundwork for future economic growth.

CONCLUSION AND RECOMMENDATION
On the basis of the findings of the research and the subsequent discussion of the factors that influence poverty in Padasari village, Cimalaka sub-district, Sumedang district, several conclusions can be drawn. These include the findings that the natural resource variables have an insignificant effect on the poor, that the human resource variables have an insignificant effect on the poor, and that the infrastructure variable has a significant effect on the poor. It is not just a matter of natural resources, human resources, and infrastructure that contribute to the complexity of the issue of community poverty; there are also other variables that are not observable. Increasing the capacity of natural resources to reduce poverty; increasing the number of human resources to reduce poverty; limited availability of infrastructure leading to an everincreasing number of people living in poverty as a result.