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.

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. 

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 Microcredit Accessibility in Rural Households: Evidence from Indonesia

2019 ◽  
Vol 65 (1) ◽  
pp. 67
Author(s):  
Danang Budi Santoso ◽  
Christopher Gan
Keyword(s):  
Logistic Regression ◽  
Interest Rates ◽  
Marital Status ◽  
Household Income ◽  
Rural Households ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Economic Welfare ◽  
Education Attainment ◽  
Factors Affecting

Extant literature suggests that microcredit may improve borrowers’ social and economic welfare. This study aimed to investigate the microcredit accessibility of rural households in Indonesia. Binary Logistic regression was used to distinguish the characteristics of microcredit borrowers and non-borrowers, and the factors affecting the approval of microcredit application. Primary data was collected through a survey on 488 rural households in Bantul, Yogyakarta. The empirical results suggested that age, marital status and education attainment significantly affect the characteristics of clients and non-clients of microcredit. The results also revealed that age of borrowers, household income, interest rates, and loan duration are key determinants affecting microcredit accessibility. The implications of the findings were provided.

scholarly journals The Impact of Literacy to Shariah Financial Service Preferences

ETIKONOMI ◽  
2016 ◽  
Vol 15 (1) ◽  
pp. 43-62 ◽  
Author(s):  
Anna Sardiana
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Financial Literacy ◽  
Financial Services ◽  
Binary Logistic Regression ◽  
Financial Service ◽  
Primary Data ◽  
Binary Logistic Regression Analysis ◽  
Descriptive Research ◽  
The Impact

The purpose of this study was to determine whether the Islamic financial literacy and the indicator as the knowledge, ability or skills and the confidence have a significant effect together and partially to the preferences of using the Islamic financial services. This type of research is descriptive research, while the method of analysis used in this study is the method of binary logistic regression analysis. The data used is primary data by the method of distributing questionnaires to users and non-users of Islamic financial services in Jakarta spread to the period April to May 2014. The results of this study indicate that Islamic financial literacy significant influence preference use Islamic financial services. In further testing, the knowledge indicator is partially significant toward the preferences of the use of Islamic financial services, as for indicators of ability and confidence does not affect the preferences of the use of Islamic financial servicesDOI: 10.15408/etk.v15i1.3115

scholarly journals EPID-34. THE DETRIMENTAL EFFECT OF BIOPSY PRECEDING RESECTION IN SURGICALLY ACCESSIBLE GLIOBLASTOMAS: RESULTS FROM THE NATIONAL CANCER DATABASE

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii85-ii86
Author(s):  
Ping Zhu ◽  
Xianglin Du ◽  
Angel Blanco ◽  
Leomar Y Ballester ◽  
Nitin Tandon ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Failure Time ◽  
Binary Logistic Regression ◽  
Rank Test ◽  
Imaging Features ◽  
National Cancer Database ◽  
Prolonged Length ◽  
Logistic Regression Models ◽  
Operative Outcomes ◽  
The Impact

Abstract OBJECTIVES To investigate the impact of biopsy preceding resection compared to upfront resection in glioblastoma overall survival (OS) and post-operative outcomes using the National Cancer Database (NCDB). METHODS A total of 17,334 GBM patients diagnosed between 2010 and 2014 were derived from the NCDB. Patients were categorized into two groups: “upfront resection” versus “biopsy followed by resection”. Primary outcome was OS. Post-operative outcomes including 30-day readmission/mortality, 90-day mortality, and prolonged length of inpatient hospital stay (LOS) were secondary endpoints. Kaplan-Meier methods and accelerated failure time (AFT) models with gamma distribution were applied for survival analysis. Multivariable binary logistic regression models were performed to compare differences in the post-operative outcomes between these groups. RESULTS Patients undergoing “upfront resection” experienced superior survival compared to those undergoing “biopsy followed by resection” (median OS: 12.4 versus 11.1 months, log-rank test: P=0.001). In multivariable AFT models, significant survival benefits were observed among patients undergoing “upfront resection” (time ratio [TR]: 0.83, 95% CI: 0.75–0.93, P=0.001). Patients undergoing upfront GTR had the longest survival compared to upfront STR, GTR following STR, or GTR and STR following an initial biopsy (14.4 vs. 10.3, 13.5, 13.3, and 9.1, months), respectively (TR: 1.00 [Ref.], 0.75, 0.82, 0.88, and 0.67). Recent years of diagnosis, higher income and treatment at academic facilities were significantly associated with the likelihood of undergoing upfront resection after adjusting the covariates. Multivariable logistic regression revealed that 30-day mortality and 90-day mortality were decreased by 73% and 44% for patients undergoing “upfront resection” over “biopsy followed by resection”, respectively (both p < 0.001). CONCLUSIONS Pre-operative biopsies for surgically accessible tumors with characteristic imaging features of Glioblastoma lead to worse survival despite subsequent resection compared to patients undergoing upfront resection.

scholarly journals Adoption of improved agricultural technology and its impact on household income: a propensity score matching estimation in eastern Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Muluken G. Wordofa ◽  
Jemal Y. Hassen ◽  
Getachew S. Endris ◽  
Chanyalew S. Aweke ◽  
Dereje K. Moges ◽  
...  
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Technology Use ◽  
Household Income ◽  
Agricultural Technology ◽  
Primary Data ◽  
Farm Income ◽  
Agricultural Technologies ◽  
Eastern Ethiopia ◽  
The Impact

Abstract Background Adoption of improved agricultural technologies remains to be a promising strategy to achieve food security and poverty reduction in many developing countries. However, there are limited rigorous impact evaluations on the contributions of such technologies on household welfare. This paper investigates the impact of improved agricultural technology use on farm household income in eastern Ethiopia. Methods Primary data for the study was obtained from a random sample of 248 rural households, 119 of which are improved technology users and the rest are non-users. The research employed the Propensity Score Matching (PSM) procedure to establish the causal relationship between adoption of improved crop and livestock technologies and changes in farm income. Results Results from the econometric analysis show that households using improved agricultural technologies had, on average, 23,031.28 Birr (Birr is the official currency of Ethiopia. The exchange rate according to the National Bank of Ethiopia (NBE) was 1 USD = 27.6017 Birr on 04 October 2018.) higher annual farm income compared to those households not using such technologies. Our findings highlight the importance of promoting multiple and complementary agricultural technologies among rural smallholders. Conclusions We suggest that rural technology generation, dissemination and adoption interventions be strengthened. Moreover, the linkage among research, extension, universities and farmers needs to be enhanced through facilitating a multistakeholders innovation platforms.

scholarly journals Analisis Dampak Tax Morale Terhadap Kepatuhan Pajak UMKM: Studi Kasus Kota Semarang

2018 ◽  
Vol 1 (1) ◽  
pp. 14
Author(s):  
Muslimah Mahmudah ◽  
Deden Dinar Iskandar
Keyword(s):  
Small And Medium Enterprises ◽  
Tax Compliance ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Binary Logistic Regression Analysis ◽  
Ethical Business ◽  
Tax Morale ◽  
Business Size ◽  
Medium Enterprises ◽  
The Impact

This study aims to analyze the impact of tax morale on Micro, Small, and Medium Enterprises (MSMEs) tax complianceSemarang City as the case study. This study uses primary data generated from 117 samples of MSMEs in Semarang. Data analysis is performed  using binary logistic regression analysis. The results showed that environmental, institutional, ethical, business, and business size variables significantly influence MSMEs tax compliance. On the other hand, variables whose effect on tax compliance is not statistically significant include happiness, religiosity, gender, age, education, and marital status.

scholarly journals Impact of Microfinance on Income and Employment in Pakistan: A Primary Data Analysis

2017 ◽  
Vol 3 (1) ◽  
pp. 69-82
Author(s):  
Shahina Imran ◽  
Rana M. Imran Arshad
Keyword(s):  
Household Income ◽  
Positive Impact ◽  
Small Enterprise ◽  
Local Context ◽  
Primary Data ◽  
Control Group ◽  
Primary Data Analysis ◽  
Gender Education ◽  
Household Assets ◽  
The Impact

Purpose: This paper investigates impact of microfinance on household income and employment. It is a primary data research conducted in the Bahawalpur division, Pakistan. The study employed the tool developed by Assessing the Impact of Microenterprise Services (AIMS) and Small Enterprise, Education and Promotion (SEEP). The tool has been modified in local context. The sample consists of 1524 respondents, out of which 773 are established clients (treatment group) and 751 are incoming ones (control group), belonging to different microfinance providers of Pakistan.  Independent Sample T-Test and Multiple regressions have been used for analysis. The regression analysis shows that participation to microfinance program has strong positive impact on household income while very minute positive impact on employment. Other independent variables such as prior access to any other loan, micro saving, household assets, age of respondent, gender, education and household size have positive impact on household income but a mixed impact on income generating activities.

scholarly journals Faktor Keberhasilan Usaha UMKM Jajanan Asing Kaki Lima di Kota Serang

2018 ◽  
Vol 12 (2) ◽  
pp. 187
Author(s):  
Fauzan Anggi Prasatya ◽  
Tjahja Muhandri ◽  
Eko Ruddy Cahyadi
Keyword(s):  
Logistic Regression ◽  
Analytical Method ◽  
Success Factors ◽  
Sampling Method ◽  
Descriptive Analysis ◽  
Binary Logistic Regression ◽  
Success Factor ◽  
Street Food ◽  
Product Innovations ◽  
Start Up

The competition of food business is currently very strict and diverse product innovations. To achieve the market share and win the business competition needs to know the affecting success factors. This study has two main objectives that include the following to: (1) mapping the characteristics of non traditional street food entrepreneur in Serang City, (2) identify the most affected success factor of non traditional street food business. Sampling method was used by purposive sampling 100 respondents. The analytical method used descriptive analysis and binary logistic regression. This research showed most of successful vendor are woman, because they are very conscientious than mens and tend to avoid risk. Affecting success factors on non traditional street food business were price of the product, business name and start up capital.

scholarly journals Binary logistic regression to estimate household income efficiency. (south Darfur rural areas-Sudan)

2016 ◽  
Vol 4 (1) ◽  
pp. 31
Author(s):  
Sofian A. A. Saad ◽  
Amin Adam ◽  
Afra H. Abdelateef
Keyword(s):  
Logistic Regression ◽  
Rural Areas ◽  
Household Income ◽  
Household Head ◽  
Binary Logistic Regression ◽  
Statistical Technique ◽  
Household Expenditure ◽  
Response Variable ◽  
Explanatory Variables ◽  
Main Factors

<p>The main objective behind this study is to find out the main factors that affects the efficiency of household income in Darfur rejoin. The statistical technique of the binary logistic regression has been used to test if there is a significant effect of fife binary explanatory variables against the response variable (income efficiency); sample of size 136 household head is gathered from the relevant population. The outcomes of the study showed that; there is a significant effect of the level of household expenditure on the efficiency of income, beside the size of household also has significant effect on the response variable, the remaining explanatory variables showed no significant effects, those are (household head education level, size of household head own agricultural and numbers of students at school).</p>

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