scholarly journals Analysis of Factors that Influence Migration in Alian and Ayah Subdistrict, Kebumen Regency, Central Java

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Diah Tiara Rahmasari ◽  
Abdul Aziz Ahmad
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Influential Factor ◽  
Primary Data ◽  
Or Education ◽  
Central Java ◽  
The Family ◽  
Medium Level ◽  
Work Skill ◽  
The Government

This research aimed to analyses migrants’ income contribution to income of the family at hometown, the influences of income, age, numbers of family to be responsible to, education, and marriage status on decision about migration in Kebumen. The method used in the research was survey of primary data which is gained through interviews and questionnaires. The data in this research were 91 migrants in Alian and Ayah Districts. Data analysis techniques used were binary logistic regression. The results showed that the contribution of migrants’ income to family’s income after migrating to the two districts was in medium level. It showed that the needs to live in migration place were expensive. Consequently, the income obtained in migration place could not give enough contribution to the family in hometown. Based on the analysis, the variable of the numbers of people the migrants had positive and significant effect for migration. Income and marriage variables status had negative and significant effect. While age and education variables had no contribution to the migration. Income is the most influential factor in migration, so the government or related organizations should give attentions to the citizen’s prosperity by creating making the job activities. The government and the society should cooperate in developing the economic potential in each area. It is also by giving the society some loans and work-skill coaching or education to increase their income. Those are to encourage the society to be more creative and autonomous.Keywords: Binary Logistic Regression, Citizen’s Prosperity, Marriage Status.

scholarly journals Binary Logistic Regression Analysis of Variables That Influence Poverty in Central Java

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Sendi Nugraha Nurdiansah ◽  
Laelatul Khikmah
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Binary Logistic Regression ◽  
Equation Model ◽  
Binary Logistic Regression Analysis ◽  
Poor People ◽  
Regional Government ◽  
Central Java ◽  
The Government

The phenomenon of poverty is a serious problem faced by almost every country in the world. This is because poverty can affect various aspects of people's lives. One of the causes of poverty is due to lack of income and assets to meet basic needs such as food, clothing, housing, health level and acceptable education. In addition, poverty occurs because of the powerlessness of society to get out of the problems it faces. The Central Java regional government incorporated poverty issues into the Regional Medium-Term Development Plan (RPJMD) because Central Java has a high number of poor people. This was done as an effort by the Central Java government to reduce poverty. Therefore, research is needed to find out the variables that most influence poverty in order to assist the government in developing the RPJMD. To find out what factors influence poverty in Central Java with the dichotomous categorical response variable, binary logistic regression analysis was used. The results showed that based on the analysis conducted did not obtain a logistic regression equation model because there were no significant parameters because there were no variables that had a sig value <0.05. Existing variables are Number of Population, Female Head of Household, Number of Children not in School, Number of Disabled Individuals, Number of Chronic Disease Individuals, Unemployment, Non-Electricity Lighting Sources, Unprotected Drinking Water Sources, Kerosene and Wood Cooking Fuels, Location Facilities Defecation (BAB) Not Available, so there are no variables that affect the level of poverty in Central Java Province.

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI STATUS PENERIMAAN BERAS KELUARGA MISKIN MENGGUNAKAN REGRESI LOGISTIK BINER DI KECAMATAN LANGSA BARAT

2020 ◽  
Vol 14 (2) ◽  
pp. 181-192
Author(s):  
Amelia Amelia ◽  
Fitra Mulyani ◽  
Ulya Nabilla
Keyword(s):  
Logistic Regression ◽  
Economic Status ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Binary Logistic Regression Analysis ◽  
Binary Logistic Regression Model ◽  
The Status ◽  
Rice Consumption ◽  
The Government

Poverty is an inability to meet basic needs measured by expenditure, including rice consumption. Based on data from the Central Statistics Agency (BPS), as much as 95% of Indonesia's population consumes rice as the main food, with an average rice consumption of 102 kg/person/ year (BPS, 2013). Furthermore, BPS stated that almost 1/4 of them or around 25.95 million people were included in the category of the poor population as of March 2018. So the government made a policy to tackle the problem through the program of giving poor family rice (Raskin), namely subsidized rice assistance to households poor. However, in the implementation of the Raskin program, there was a deviation of around 40% of Indonesia's population with a middle-upper social-economic status receiving Raskin and 12.5% ​​of the population with a socio-economic status upon receiving Raskin. Therefore this study aims to analyze the significant factors that affect the status of rice in poor families using binary logistic regression analysis. The location of the study was conducted in the District of West Langsa because the district was one of the districts receiving the most Raskin in the City of Langsa. The data used in this study are primary data and secondary data. The results of the analysis show that the factors that influence Raskin's acceptance status are the level of education, type of floor, type of fuel, expenditure for food, and frequency of purchasing new clothes. The binary logistic regression model obtained is

scholarly journals KLASIFIKASI REGRESI LOGISTIK MULTINOMIAL DAN FUZZY K-NEAREST NEIGHBOR (FK-NN) DALAM PEMILIHAN METODE KONTRASEPSI DI KECAMATAN BULAKAMBA, KABUPATEN BREBES, JAWA TENGAH

2022 ◽  
Vol 10 (4) ◽  
pp. 476-487
Author(s):  
Erysta Risky Rismia ◽  
Tatik Widiharih ◽  
Rukun Santoso
Keyword(s):  
Logistic Regression ◽  
Classification Accuracy ◽  
Nearest Neighbor ◽  
Multinomial Logistic Regression ◽  
K Nearest Neighbor ◽  
Contraceptive Methods ◽  
Family Planning Services ◽  
Central Java ◽  
The Family ◽  
The Government

The characteristics of society in choosing contraceptive methods are also the crucial factors for the government to prepare the family planning services needed at Bulakamba District, Brebes Regency, Central Java. In this case, a classification process needs to be done to assist the process of classifying the characteristics of society in the selection of contraceptive methods. Multinomial Logistic Regression classification is good in exploring data information  meanwhile Fuzzy K Nearest Neighbor (FK-NN) classification is good for handling big data and noise. These two methods used in this study because they are relevant to the data applied and will be compared their classification accuracy through APER and Press's Q calculations.The classification accuracy results obtained based on the APER calculation for Multinomial Logistic Regression is 88,25% and Fuzzy K Nearest Neighbor (FK-NN) is 88,92%.  Meanwhile, the Press's Q value of both methods are 9600,945 and 9518,014 greater than χ 2𝛼,1 which is 3,841, so that it is statistically accurate. Based on the results obtained, it can be concluded that Multinomial Logistic Regression classification method has a better classification accuracy than Fuzzy K Nearest Neighbor (FK-NN) method. 

scholarly journals PENGARUH PROGRAM KELUARGA HARAPAN TERHADAP DISINSENTIF BEKERJA RUMAH TANGGA KELUARGA PENERIMA MANFAAT

2020 ◽  
Vol 5 (2) ◽  
pp. 118-132
Author(s):  
Syahna Salsabila ◽  
◽  
Evi Purwanti ◽  
Keyword(s):  
Logistic Regression ◽  
Analytical Method ◽  
Household Income ◽  
Binary Logistic Regression ◽  
Working Hours ◽  
Work Hours ◽  
Primary Data ◽  
Household Work ◽  
The Family ◽  
The Impact

The purpose of this study is to analyze the impact of PKH on Beneficiary Families (KPM) households work incentives that can be seen from the reduction in household hours worked. This type of data used is primary data obtained through an individual survei of 100 Beneficiary Families (KPM) in Bulakamba District, Brebes Regency. The analytical method used in this study is binary logistic regression. The results of the study on the overall of Beneficiary Families (KPM) household scopes showed that the variable proportion of PKH assistance, the proportion of household income significantly influence the reduction in the number of working hours of Beneficiary Families (KPM) households in Bulakamba District. The reduction in household working hours is concentrated or dominated by the decrease of wife's working hours. While the reduction in working hours of the head of the family does not have a big role in reducing household work hours. This shows that the wife's working hours are more responsive than the head of thefamily's working hours when there is a social assistance provided.

Perceptions of an ageing agricultural workforce and farmers’ productivity strategies: Evidence from Prachinburi Province, Thailand

2021 ◽  
pp. 003072702110250
Author(s):  
Sylvia Szabo ◽  
Chidchanok Apipoonanon ◽  
Malay Pramanik ◽  
Kevin Leeson ◽  
Devendra Raj Singh
Keyword(s):  
Agricultural Sector ◽  
Labour Force ◽  
New Technology ◽  
Negative Influence ◽  
Farm Size ◽  
Primary Data ◽  
Intergenerational Support ◽  
Ageing Workforce ◽  
The Family ◽  
The Government

Thailand’s agriculture is facing an ageing workforce, which could negatively influence agricultural production. Yet, there is still limited evidence regarding the perception of the ageing agricultural labour force in the country and a lack of insights into farmers’ strategies to improve agricultural output. To fill this gap, we analysed primary data from questionnaire-based surveys of 365 households in Prachinburi Province, Thailand. The results show that household poverty, farm experience, retirement, health concerns, and farm accidents are positively associated with the farmers’ perception on the ageing workforce, whereas education level, having an ageing farmer in the family, farm size, mentoring and access to new technology have a negative influence on the perception of the ageing workforce. Given the anticipated implications of the population ageing in Thailand, the government should consider establishing policy options to encourage younger entrants into the agricultural sector and prioritising policies related to intergenerational support.

scholarly journals Analysis of Consumers’ Preference for Local Rice among Households in Ekiti State, Nigeria

2020 ◽  
pp. 18-23
Author(s):  
G. T. Ajayi ◽  
A. Ajiboye
Keyword(s):  
Logistic Regression ◽  
Control Policy ◽  
Structured Interview ◽  
Sampling Procedure ◽  
Primary Data ◽  
Multi Stage ◽  
Good Taste ◽  
The Mean ◽  
The Government

Consumers’ preference for local rice determines its demand. Therefore, the study was carried out to analyze consumers’ preference for local rice among households in Ekiti State. A multi-stage sampling procedure was used to select respondents for this study. A total of 240 women were randomly selected from three Local Government Areas (LGAs) in the State. Primary data were obtained with the use of a well-structured interview schedule. Data collected were analyzed using descriptive statistics as well as inferential statistic like logistic regression. The mean age of the respondents was 38 years and more than half (53.3%) of the respondents were females. Most (70.0%) of the respondents had a mean family size of 7 persons. Most (87.0%) preferred local rice and factors influencing consumers’ preference for local rice include good nutritional value, quality of rice and good taste. Local rice was very much preferred by the respondents. Logistic regression shows that significant influence exists between price, taste, availability of rice and presence of particles and preferred choice of rice. Therefore, efforts should be made by the government to formulate price control policy on local rice for its affordability by the consumers and there should be improvement on processing technology of local rice to eliminate presence of particles for improved quality and good taste to enhance the consumers’ preference for choice of rice. Also, the government should support farmers through provision of incentives and credit facilities so as to produce more local rice for its availability all year round.

THE INNOVATION OF VULNERABLE FISHERIES USING ECOSYSTEM-BASED FISHERY MANAGEMENT APPROACH: A TEST CASE IN KARIMUNJAWA ECOSYSTEM, CENTRAL JAVA, INDONESIA

2016 ◽  
Vol 78 (4-2) ◽  
Author(s):  
Mayanggita Kirana ◽  
Indah Susilowati ◽  
Kuperan Viswanathan
Keyword(s):  
Fisheries Management ◽  
Fishery Management ◽  
Meta Analysis ◽  
Marine Ecosystem ◽  
Primary Data ◽  
Management Approach ◽  
New Paradigm ◽  
Initial Finding ◽  
Central Java ◽  
The Government

The sustainability of marine ecosystem has become a major concern the government; however, the implementation of sustainability-based fisheries management has not been fully carried out and well controlled. Therefore, having a concept of ecosystem-based fisheries management (EBFM) is essential in protecting it preserved. The aim of this study was to analyze the implementation of EBFM in Karimunjawa ecosystem, Central Java, Indonesia. The analysis of this study was based on the primary data collected from fishermen and stakeholders using in-depth interviews, and the secondary data gathered from stakeholders of Karimunjawa documentation. Meta-analysis with triangulation was invoked in this study. The result showed that the vulnerability of marine ecosystem, particularly fisheries’ resource in the pilot project is in progress. The conventional approach has not yet succeeded in managing fisheries’ resource in terms of sustainability attributes. Moreover, the EBFM has not yet proven to be a suitable approach for some reasons; although, this concept is very promising in encouraging a new paradigm for sustainable management in Indonesia with a protocol concept. This initial finding needs to be furthered in order to explore other aspects of development. 

scholarly journals Identifikasi Perilaku Pasangan Usia Subur Terhadap Keikutsertaan Program Keluarga Berencana Dengan Pendekatan Teori Perilaku Yang Terencanakan (Theory Of Planned Behaviour)

2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Anggie P Putri
Keyword(s):  
Family Planning ◽  
Theory Of Planned Behaviour ◽  
Family Planning Program ◽  
Population Data ◽  
Subjective Norm ◽  
Planning Program ◽  
Planned Behaviour ◽  
Central Java ◽  
The Family ◽  
The Government

Abstract: Attitude, Subjective Norm, Behaviour Control, Family Planning, Behaviour To Undergo Family Planning. This study aims to identify the influences of attitude, subjective norm, behaviour control and intention to attend Family Planning program using Theory of Planned Behaviour. The frame of this theory is tested to analize the influences of the constrution of this study, the understanding of attitude, subjective norm, behaviour control, intention to attend a program set by the government to controlling the population. Data collection was done by giving the questionnaire to 109 respondents who were undergoing Family Planning program in Jetiskarangpung, Sragen, Central Java Indonesia; but there are 100 valid questionnaires. The data is analized using T-test and then the variabels are analized using multiple Regression. The findings of this study shows that attitude (sig. 0,006), subjective norm (sig. 0,002), behaviour control (sig 0,012) gives significant influence of the intention to undergo the Family Planning program. This findings is aline with the philosphy within Theory of Planned Behaviour.

scholarly journals Model Kemandirian Masyarakat dalam Upaya Pemberdayaan Sosial melalui Program PKH di Kota Surabaya

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Kokoh Prasetyo ◽  
Ertien Rining Nawangsari ◽  
Johan Vivaldi Alex Sander
Keyword(s):  
Basic Principle ◽  
Large Population ◽  
Secondary Data ◽  
Poverty Rate ◽  
Data Sources ◽  
Primary Data ◽  
The Family ◽  
The Government ◽  
Social Empowerment ◽  
The City

Indonesia is a country that has quite a large population, one of which is the largest population in the city of Surabaya as a metropolis. With this large number of people, the poverty rate for families in the community is high, so the government provides a program to break the poverty chain, the Family Hope Program (PKH). The purpose of this study is to determine the implementation of social empowerment in the city of Surabaya through the family hope program that can make the community / beneficiary socially and economically independent life and measure the family hope program as a manifestation of community independence. This study used descriptive qualitative method. Data sources consist of primary data and secondary data. Primary data sources were obtained from observations and interviews. Data processing is done through the process of data reduction, data presentation, and conclusion checking or verification. The analysis used in this research is to use the basic principle model of community independence. The results of this study, show that social empowerment through the family of hope program by using a model of community independence is still not going well to create an economically and socially independent community. This can be seen from the data of the community / beneficiaries can live independently after receiving a family of hope program. Through the basic principle model of community independence from Sunyoto Usman (2003) which includes: creating climate, strengthening power, and protecting.Keywords: Human Development Index, Social Empowerment,Welfare

scholarly journals The Impact of International Remittances on Poverty Alleviation in Bangladesh

2019 ◽  
Vol 4 (1) ◽  
pp. 67-86 ◽  
Author(s):  
Bezon Kumar
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Poverty Alleviation ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Binary Logistic Regression Model ◽  
Household Poverty ◽  
International Remittances ◽  
The Impact

This article mainly explores to what extent international remittances alleviate household poverty in Bangladesh. This study uses primary data collected from 216 households and employs multi-methods. Firstly, I measure the level of household poverty through Foster-Greer-Thorbecke index. The article secondly focuses on the impact of remittances on household poverty using a binary logistic regression model. I found that the level of poverty among remittance recipient households is notably lower than households that are not receiving remittances. Similarly, the probability of a household being poor is alleviated by 28.07 per cent if the household receives remittance. It can be suggested that nursing international remittances can be useful for poverty alleviation in Bangladesh. 

Sign in / Sign up

Export Citation Format

Share Document