Assistance Recipients Research Articles

Comparative Analysis Of Saw And Topsis In Selecting Recipients Of Basic Food Assistance

The Basic Food Program is one of the Indonesian government's alternative programs for distributing aid to underprivileged or poor communities. A selection process needs to be carried out to determine recipients of basic food assistance. Decision Support Systems are effective systems used to produce calculations with output in the form of rankings. The methods that are quite widely used are the Simple Additive Weighting (SAW) method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). This research aims to apply the SAW and TOPSIS methods in selecting aid recipients so that appropriate results are obtained which can be proposed as solutions to decision-making problems. There are 6 criteria used in this case, including: residence, occupation of the head of the family, type of floor, type of wall, place to urinate, lighting source. The data used as a test is data from the Banyuurip village community in 2023. The calculation process is carried out by finding the weight value of each alternative for each criterion. The selected aid recipients are those who have the greatest value as the best alternative. From the calculation results of the SAW (Simple Additive Weighting) and TOPSIS methods, the calculation results of the two methods were obtained. The alternative with the largest value or rank 1 produced by SAW and TOPSIS was both selected as alternative A10. Of the 12 data tested, SAW and TOPSIS have 50% similar alternative ranking results, including: rank 1 = A10, rank 5 = A9, rank 7 = A7, rank 8 = A6, rank 11 = A2, and rank 12 = A12. The SAW method gets better results compared to the TOPSIS method, because it gets precise, stable results and shorter processing time.

Implementasi Pengelolaan Zakat dalam Pengembangan Modal Usaha (Studi pada BAZNAS Kota Payakumbuh)

Payakumbuh City BAZNAS Strategy in determining mustahik candidates who are given productive program assistance: setting goals and targets, announcing prospective mustahik beneficiaries, criteria for mustahik who will be given assistance, the form of business that will be given assistance, the process of announcing businesses, the administration that will have to be completed, receiving and selecting mustahik prospective recipients of assistance, announcing mustahik prospective recipients who pass and determining the nominal amount of assistance. The results of the research that the researchers conducted showed that the Payakumbuh City BAZNAS stipulated requirements and procedures for determining mustahik candidates and carried out a series of activities in monitoring efforts in an effort to activate the misuse of aid. So as a whole what is meant by the title above is that the author will describe the success or failure of productive businesses/business capital at BAZNAS Payakumbuh City in distributing zakat annually.

Implementation of Multi-Attribute Utility Theory Method for Selecting Social Assistance Recipients

Amil Zakat Infaq and Shadaqah Muhammadiyah Institution (LazisMu) Ayah is one of the national amil zakat institutions located in Ayah District, Kebumen Regency. Every month, LazisMu Ayah Service Office provides assistance to people in need in the form of house renovation programs, scholarships for high school or college level education, and business capital. The problem that is often encountered in determining potential aid recipients is that the large number of requests for aid is disproportionate to the number of officers processing the screening data. Apart from that, the selection process for aid recipients still uses manual methods, so it often causes problems such as the selection process for selecting aid candidates taking up to a week and miscalculations occurring, resulting in inaccurate results in the selection of potential aid recipients. Therefore, the method used as a solution model in providing decisions on the system for selecting potential aid recipients at LazisMu Ayah is a decision support system using the multi-attribute utility theory (MAUT) method. This method was chosen because it is able to select the best alternative from a number of alternatives, in this case, the intended alternative is people who are entitled to receive assistance based on 10 criteria. The results of the black box testing show that the system created is in accordance with the design and can be used as a tool. making decisions on determining aid recipients, so that LazisMu Ayah services can be improved because the selection process becomes faster, more accurate, and on target.

COMPOSITION OF SOCIAL INSURANCE COSTS AND GUIDELINES FOR EFFECTIVE USE

The article explores the financial analysis of Uzbekistan's social insurance system, encompassing economic-statistical analyses of different social insurance types and the results of pension and allowance disbursement software. It discusses the rise in recipients of social benefits and material assistance for low-income families, along with their financial sources. The implementation of the social insurance system necessitates financial resources, making social funds integral to economic mechanisms for income redistribution. These funds, whether state or non-state, depend on factors like the national economic development model. Acknowledging their role in financial relations, social funds have a specific financial purpose, crucial in priority areas. Ongoing research focuses on effective organization and financing of the social protection system, emphasizing the development of voluntary and mandatory medical insurance, improving unemployment benefit procedures, and enhancing pension system stability. Recent initiatives in Uzbekistan include the revision of pension procedures, fundamental pension system reform, laws on compulsory health insurance, and the development of the "Law on Social Insurance." Scientific research aims to strengthen social protection for specific groups and enhance the existing social insurance system.

Latin America at the margins? Implications of the geographic and epistemic narrowing of ‘global’ health

ABSTRACT To explore the narrowing of the concept of ‘global’ in global health, this article traces how Latin America has held a place of both privilege and power as well as marginalisation in the field. We employ a modified extended case method to examine how Latin America has been ‘seen’ and ‘heard’ in understandings of global health, underscoring the region’s shifting role as a key site for research and practice in ‘tropical medicine’ from the mid-nineteenth century through World War II, to a major player and recipient of development assistance throughout the ‘international health’ era after World War II until the late twentieth century, to a region progressively marginalised within ‘global health’ since the mid-1980s/1990s. We argue that the progressive marginalisation of Latin America and Southern theory has not only hurt health equity and services, but also demonstrates the fundamental flaws in contemporary ‘global’ thinking. The narrowing of global health constitutes coloniality of power, with Northern institutions largely defining priority regions and epistemic approaches to health globally, thus impoverishing the field from the intellectual resources, political experience, and wisdom of Latin America’s long traditions of social medicine and collective health.

IMPLEMENTATION OF RANDOM FOREST AND SMOTE METHODS FOR ECONOMIC STATUS CLASSIFICATION IN CIREBON CITY

The Indonesian government has tried various methods to eradicate poverty throughout the country, one of which is the fair distribution of social assistance to households based on their economic status classification. The determination of social assistance recipients can be influenced by political factors or personal relationships and can be misused, leading to assistance being given to individuals with specific political connections or support. This research aims to develop a household economic status classification system in Cirebon City using the Random Forest algorithm to address these issues. The data used in this research experienced an imbalance in the number of class instances, where the high-class instances were much fewer than the low and medium classes. To address this, the Synthetic Minority Oversampling Technique (SMOTE) was employed. In this study, various testing scenarios were conducted to obtain the best model for accurately predicting household economic status. Based on the research results, the best testing was achieved using Random Forest and SMOTE with a random state of 0, obtaining an accuracy of 93% and excellent performance in classifying each class. When testing unlabeled data, Random Forest successfully predicted 24 out of 30 actual data, resulting in an accuracy rate of 80%. Although this accuracy is lower than what was achieved by Random Forest and SMOTE with a random state of 0, it can be said that the application successfully classifies household economic status in Cirebon City effectively.

Effectiveness and Outcomes of Fishing Gear Assistance on Fishermen's Income in Pedes District Karawang

Fishing gear assistance is one of a series of activities undertaken by the Ministry of Marine Affairs and Fisheries by providing fishing gear, Gill Net and Trammel Net to fishermen. The study aims to analyse the level of effectiveness of activities, analyze the strength of supportive and inhibitory factors that influence, and analyse the outcome of fishing gear assistance on fishermen's reception. The research method used is quantitative descriptive. Primary data collection is obtained directly through questionnaires and interviews whereas secondary data is acquired through journal literacy and related scripts as well as data from related agencies. Sampling was done with a census of 40 fishermen. Data analysis on this study uses the likert scale, the guttman scale and the t test. The results of this study show that the overall distribution of aid is running effectively. Both supportive factors have strong influence and both inhibitory factors have weak influence in the distribution of aid. There has been a change in fishermen's reception before and after the distribution of fishing gear with a sig. (2-tailed) value of 0,000 < 0,05, whereas fisherman recipient of shrimp net assistance has not experienced any change in reception after the assistance of fish gear.

Predictions using Support Vector Machine with Particle Swarm Optimization in Candidates Recipient of Program Keluarga Harapan

Program Keluarga Harapan (PKH) is a conditional social assistance program as an effort to alleviate poverty which is allocated to poor vulnerable households. The determination of candidates for the Program Keluarga Harapan assistance recipients is still carried out in village meetings, so it takes quite a long time and there is potential for subjectivity in the assessment carried out by Village Government officials which can lead to differences of opinion between deliberation participants in assessing the eligibility of residents as PKH recipients. For this reason, this research will use an optimization method, namely Particle Swarm Optimization (PSO) to select the most optimal attribute out of 39 attributes. After that, a classification algorithm, namely the Support Vector Machine (SVM), was chosen to form a classification model for Candidates for Social Assistance for the Program Keluarga Harapan (PKH). The classification of Candidates for Social Assistance Recipients of the Program Keluarga Harapan (PKH) was carried out in 2 experiments, namely before and after optimization. Experiments before optimization give an accuracy value of 92.44%. While the Support Vector Machine accuracy value after optimization gives an accuracy value of 92.51%. Based on the experimental results, it can be concluded that the Particle Swarm Optimization method can increase the accuracy of the Support Vector Machine algorithm by 0.07%. And the best model is the Support Vector Machine after optimizing Particle Swarm Optimization by using the 17 most optimized attributes in determining class targets.

Meningkatkan Pengetahuan Tentang Bantuan Sosial Terhadap Warga Tapanuli Utara Yang Datang Ke Pelayanan Dinas Sosial Tapanuli Utara Melalui Pendampingan Dengan Menggunakan Metode Group Work

The lack of understanding of the community in North Tapanuli regarding knowledge about social assistance makes the process of distributing and distributing social assistance less efficient, where the community does not understand the criteria that social assistance recipients must have. Very often there are complaints to the North Tapanuli social service about unfair and unequal assistance, which makes the social service feel that it has to be responsible for providing insight and understanding to residents. In this case, the importance of cooperation between both regional and central governments is very necessary because the relationship and cooperation that requires them must be interconnected and have the same goals.The public's understanding of social assistance will be very beneficial for the prosperous lives of citizens because after understanding this, justice and public trust in the government will arise. so that the North Tapanuli Social Service always provides good guidance and explanations to residents because many residents come to the social service to ask for social assistance without knowing the background or criteria for the requirements for receiving social assistance and comparing themselves to aid recipients around them.

Model Komunikasi Polresta dalam Penyaluran Bantuan Tunai Pedagang Kaki Lima dan Warung (BTPKLW) di Pekanbaru

The distribution of cash assistance to street vendors and small shop owners (BTPKLW) is one of the efforts made by the Government to provide support to the informal sector in facing the economic impacts of the COVID-19 pandemic. One of the institutions involved in the distribution of Cash Assistance for Street Vendors and Small Shop Owners (BTPKLW) in Pekanbaru is the City Police Resort (Polresta). This study aims to analyze the communication model used by Polresta Pekanbaru in the distribution of cash assistance to BTPKLW, focusing on the Laswell communication model and the simple linear communication model with feedback. This research used a qualitative approach with data collection techniques such as observation, interviews, and documentation. The research respondents consisted of members of the Community Development Unit (Binmas) of Polresta Pekanbaru, street vendors, and small shop owners. The data analysis techniques used in this study are data reduction, presentation, and conclusions. The results of the study showed that Polresta Pekanbaru utilized various communication channels, including official websites and social media, as well as direct meetings with street vendors and small shop owners. The communicators, represented by the Binmas Unit of Polresta Pekanbaru, provided information on the requirements, schedule, and mechanism of cash assistance distribution to the vendors and shop owners. The messages conveyed by the communicators were clear and detailed. Feedback from the recipients was demonstrated through the completion of registration forms for prospective BTPKLW recipients. However, the study also identified several obstacles in the implementation of cash assistance distribution, particularly related to the verification of recipient data. These obstacles included inaccuracies in the data provided by the recipients, document authenticity, and data duplication. Based on the findings of this research, it is recommended that cash assistance recipients carefully pay attention to the information provided by the Binmas Unit of Polresta Pekanbaru, comply with the established procedures, complete the required documents accurately, ask for clarification when needed, maintain effective communication, and utilize the assistance wisely.

Pengelolaan Penyaluran Bantuan Rumah Layak Huni (RLH) pada Masa Pandemi Covid-19 di Kota Pekanbaru Provinsi Riau

The aim of this research is to determine management and the influencing factors. Qualitative research method with data sources namely primary and secondary data, data collection techniques based on observation, interviews, documentation and analysis. The result of the author’s research are that the management of distribution of livable housing assistance during the Covid-19 pandemic in Pekanbaru City, Riau Province is still not effective. The lack of innovation and quick solutions in distribution management during the Covid-19 pandemic has made distribution management less effective. There are still many deficiencies found, such as in providing socialization and registration for recipients of livable housing, assistance, it still uses a manual system and has obstacles, namely changes in distribution targets, distribution procedures that are not yet effective and the management of infrastructure is not in accordance with the budget provided, due to the impact due to the Covid-19 outbreak, the budget allocated was cut to handle Covid-19, but in the field the facilities avaulable to recipients of livable housing assistance were incomplet.

COMPARISON OF SPATIAL WEIGHTED MATRIX BETWEEN POWER AND QUEEN ON THE SPATIAL EMPIRICAL BEST LINEAR UNBIASED PREDICTION MODEL (Study on Per Capita Expenditure in East Java Province in 2019)

This study aims to make a comparison related to the spatial weighted matrix of power and queen in the SEBLUP model to estimate per capita expenditure in East Java in 2019. The data used is secondary data then the data were analyzed by the Spatial Empirical Best Linear Unbiased Prediction (SEBLUP). The results of this study indicate that the best spatial weighted matrix for estimating per capita expenditure in East Java using the SEBLUP model is the spatial weighted matrix of Queen, because it produces the smallest MSE value. In this study, the factors that significantly affect East Java's per capita expenditure are population density (X1), number of health facilities (X2), number of public elementary schools (X3), and the percentage of residents who have BPJS as the Fund Assistance Recipients (X5). The novelty of this study are combining multiple determinant factors that have demonstrated their substantial/significant effect on the average per capita expenditure and focusing on the regions characters in intermediate size (16<n<64).

Application of Data Mining to Classify Receiving Social Assistance Using the Naïve Bayes Method

The application of Naïve Bayes in classifying potential recipients of Non-Cash Food Assistance (BPNT) in Grujugan Kidul Village was made to solve problems in the process of distributing non-cash food assistance programs that had not run optimally and had not been on target. The purpose of this study is to find out how the Naïve Bayes Algorithm is applied in classifying Non-Cash Food Assistance Recipients in Grujugan Kidul Village so as to obtain optimal results. The method used in this study is the Naïve Bayes classification method. The Naïve Bayes algorithm is proven to have good performance in predictions, and produces high accuracy values. The stages of data analysis were carried out based on the CRISP-DM method while the algorithm testing was carried out on the RapidMiner 9.10.001 software as a comparison between manual calculations and software calculations. The results of the accuracy in this study were 89.19% from 8:2 Comparison of 80% test data, 20% test data.

EVALUASI IMPLEMENTASI PROGRAM INDONESIA PINTAR DI SMKN 1 LEMBAH MELINTANG KABUPATEN PASAMAN BARAT

The Smart Indonesia Program is cash assistance from the government that is given to students whose parents cannot afford to pay for their education (Regulation of the Ministry of Education and Culture of the Republic of Indonesia Number 12 of 2015). The purpose of this study was to evaluate the implementation of the Smart Indonesia Program at SMKN 1 Lembah Melintang, West Pasaman Regency. The problems in this research are the process of distribution and disbursement of aid funds that are not timely, program targets that are not quite right and monitoring and socialization that are still not optimal. The method used in this research is descriptive qualitative research. The researcher uses William N. Dunn's theory with indicators of effectiveness, efficiency, adequacy, alignment, responsiveness and accuracy. The results of the study found that the Evaluation of the Implementation of the Smart Indonesia Program at SMKN 1 Lembah Melintang, West Pasaman Regency, had not been maximized. Due to the lack of supervision or outreach from the education office to the schools regarding the implementation of the program. Suggestions given by researchers include increasing socialization regarding the program to schools, providing knowledge to parents or guardians regarding the use of aid funds, schools to be more careful in recording student assistance recipients so that they are right on target, and increasing active communication between the Education Office and School.

Eligibility of village fund direct cash assistance recipients using artificial neural network

<p>Bantuan Langsung Tunai Dana Desa (BLT-DD), or known as Village Fund Direct Cash Assistance is assistance from the Indonesian government which causes problems and conflicts in the community when the assistance is not on target. The classification algorithm is proven to use in determining BLT-DD recipients. In this study, the radial basis function (RBF) and elman recurrent neural network (ERNN) models compare to classify the eligibility of BLTDD recipients. In the experiment, the optimal performance of the RBF and ERNN compare in determining the eligibility of BLT-DD recipients. Also, it’s compared with the classification algorithm that implements the same data, namely BLT-DD data for Kubu Raya District. The experimental results show the effectiveness of the RBF model in recognizing test data, while the ERNN model is effective in identifying test data. The RBF and ERNN models can achieve the same total accuracy of 98.10%.</p>

Distribution Analysis and Ranking Analysis of Poverty Data From Three Data Sources in Bekasi Regency

In implementing evidence-based policies, it is necessary to support poverty data that is precise, accurate, and consistent. The goal is that various assistance, such as social assistance, PKH, groceries, pre-employment, and other subsidies, will be right on target for people experiencing poverty. The diversity of poverty data sources will have implications for the inaccuracy of targeting social assistance recipients. Until now, there are still three sources of poverty data, namely the Statistics Indonesia, the Ministry of Social Affairs (Kemensos) with Integrated Data on Social Welfare (DTKS), and TNP2K, which is now under the Coordinating Ministry for Human Development and Culture (Kemenko KMK) which also releases data targeting the Acceleration of Extreme Poverty Elimination (P3KE). The purpose of this study is to analyze the distribution of poverty data and rank analysis of poverty data from three data sources in the Bekasi Regency. The analysis method used ArcGIS 10.4 software and the administrative map shapefile for the Bekasi Regency area. In the ranking analysis of poverty data from three data sources in each sub-district in Bekasi Regency, the Preference Ranking Organization Methods For Enrichment Evaluation (PROMETHEE) method was used. The results of the analysis showed that the distribution of P3KE data is 1,317,098 people spread by decile-1 to decile-4 in all sub-districts of Bekasi Regency. Statistics Indonesia data is 229,367 people spread across each sub-district, and the number of DTKS in Bekasi Regency is 1,035,402 people, with the most distribution of data in Babelan District, namely 110,867 people out of 34,009. While the best ranking of the three sources of poverty data is Central Cikarang, Pebayuran District (0.7273), North Tambun (0.6364), Cibitung and Karang Bahagia (0.4242), North Cikarang (0.3939), South Tambun (0 .3636), Sukatani (0.2121), Serang Baru (0.1515), West Cikarang (0.1212), Tarumajaya (0.0909), East Cikarang (0.0606).

Politik Kesejahteraan Sosial dan Pemberdayaan Masyarakat: Kasus Ketergantungan Kebijakan Bantuan Sosial di Temanggung, Jawa Tengah

<p>One of the government's strategies for overcoming poverty is to reduce the burden of public expenditure, which is realized in the form of social assistance. The government's social welfare policy in the form of social assistance is something that is truly phenomenal and is always eagerly awaited by the recipients. One of the effects is to provide a sense of security and feel like you are in a comfort zone, in other words, dependence on social assistance. But there are beneficiaries who are dissatisfied with their situation, they want positive changes and not to be recipients of social assistance forever. They made conscious changes by empowering their group of fellow recipients of the Family Hope Program's social assistance. This research is field research in the form of a case study located in Temanggung Regency with the research object being a Joint Business Group which carries out the establishment and initial capital independently, namely from the results of setting aside some of the social assistance money they receive. The research method used is a qualitative descriptive method, while data is obtained from observations, interviews and documentation studies from related sources. This article tries to review the theme with Anthony Giddens' structuration theory, which states that all social action requires agents and structures where agents and structures cannot be separated from each other because they are dual. This also happens to Joint Business Groups as agents and government policies as structures, both of which are interrelated and influence each other.</p><p> </p>

The Implementation of MOORA method in the Selection of Direct Cash Aid Recipients

This research aims to implement the Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA) algorithm as a Decision Support System for selecting recipients of Direct Cash Assistance in Cempaka Putih village, Gorontalo. With a dataset of 112 prospectus recipients, the study focuses on developing an efficient approach to assist the village head in the beneficiary selection process. By combining multi-objective optimization and ratio analysis, the MOORA algorithm objectively evaluates and ranks recipients based on eligibility and suitability. The findings demonstrate the effectiveness of MOORA in streamlining the selection process, ensuring transparency and optimizing resource allocation for those most in need. This research contributes to decision support systems by showcasing the practical application of MOORA, enhancing assistance distribution, and improving community welfare. The results show that Alternative A1 receives the highest ranking, which is 1, with a Yi value of 1.32. Therefore, Alternative A1 is recommended as the best candidate to receive direct cash assistance in the Cempaka Putih village. The method has the capability to rank the top 12 suitable candidates who are eligible to obtain direct cash aid. However, there are instances where certain Yi values match, resulting in the same ranking for those alternatives. This similarity necessitates further observation and analysis.

Decision Support System for Selecting Social Assistance Recipients using The Preference Selection Index Method

This research aims to solve the problem of selecting social assistance recipients in the Nagori Moho area, Java Marajah Bah Subdistrict, Jambi, Simalungun District; in order to obtain the right targeted recipients of social assistance, the Nagori office carries out the selection of its residents, this selection is carried out by implementing a computer-based decision support system (DSS). The decision support system uses the PSI method. The criteria used in this method consist of economic condition, income, jobs, age, and dependents of the school children. The results obtained from this research are recommendations for the population receiving aid with results consisting of rank 1 with the alternative value S_Purba with a value of 0.9286, then rank two with the alternative F_Azhar with a value of 0.7599, and rank 3 is Jumiati with a value of 0.7163. This decision support system can make it easier for the Nagori office to select residents worthy of assistance.

Enhancing data accuracy with design of a web-based citizen data management application for neighborhood/residential unit

Citizen data is critical in making appropriate decisions by neighborhoods/residential units (RT/RW) and sub-districts. Therefore, citizen data must have a high level of validity. In Tiban Lama Sub-district, Batam City, at the RT/RW level, citizen data management is still done manually, so problems often occur such as inaccurate data, delays in updating data, limited data access, difficulties in analysis, and difficulties in data coordination, decision-making errors in determining social assistance recipients, and obstacles in data management at Integrated Service Centers (Posyandu). To overcome this problem, a web-based citizen data management application is needed, where residents can upload the required data through the application by attaching supporting documents and the data will be verified by the RT/RW. This application can help villages and RT/RW manage citizen data and make the right decisions for their citizens. Based on the implementation of the activity, a positive response was obtained from the Head of Tiban Lama Village and the RT/RW level of Tiban Lama regarding the use of web-based applications.