scholarly journals Determinan Variabel Demografi Terhadap Cerai Hidup Wanita Di Pulau Sumatera: Survei Demografi Dan Kesehatan Indonesia 2017

2021 ◽  
Vol 6 (1) ◽  
pp. 23
Author(s):  
Angga Setyawan
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Quantitative Analysis ◽  
Logistic Regression Analysis ◽  
Health Survey ◽  
Secondary Data ◽  
Demographic Variables ◽  
Demographic And Health Survey ◽  
Analysis Method ◽  
Number Of Children

The purpose of this study was to analyze the demographic variables that affect the probability (chance) of divorce for women on the island of Sumatra. This research is a quantitative analysis, using secondary data from the 2017 Indonesian Demographic and Health Survey (IDHS) with logistic regression analysis method. The results showed that three variables that significantly influence the high and low chance of divorce for women are wife's education, number of children and wife's occupation. The wife's education has a significant effect on the chance of a woman's divorce, with the wife's education coefficient is positive, which means that the lower the wife's education, the higher the chance for a wife to be divorced. The coefficient value of the number of children is positive, which means that the fewer children (

scholarly journals Risk of Exclusion in People with Disabilities in Spain: Determinants of Health and Poverty

2018 ◽  
Vol 15 (10) ◽  
pp. 2129
Author(s):  
Angel Belzunegui-Eraso ◽  
Inma Pastor-Gosálbez ◽  
Xavier Puig-Andreu ◽  
Francesc Valls-Fonayet
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Chronic Illness ◽  
Social Integration ◽  
Social Exclusion ◽  
Logistic Regression Analysis ◽  
Health Survey ◽  
Social Determinants ◽  
Everyday Activities ◽  
Analyze Data

In this paper, we analyze data from the 2012 Encuesta de Integración Social y Salud (Social Integration and Health Survey) of the Instituto Nacional de Estadística (Spanish National Institute of Statistics) to obtain profiles created by combining disability, poverty and social exclusion. We hypothesize that the probability that people will experience social exclusion increases if they have a disability, chronic illness or limitation in conducting everyday activities, and that this probability is greater for women than for men. To conduct our analysis, we constructed a social exclusion model based on a series of social determinants that acts as a dependent variable. In this context, social exclusion is understood to go beyond the concept of financial poverty. We performed bivariate analyses, in which we calculated the Odds Ratios (OR) for certain variables considered to be predictors of social exclusion. We also performed a means comparison test and an ANOVA test to observe differences between individuals with recognized disability and those without. Finally, we conducted logistic regression analysis to determine which vulnerability profiles are most likely to experience a situation of social exclusion. We also discuss the limitations of our study, and suggest areas in, which the relationships between health, social exclusion and disability can be further investigated.

scholarly journals Pengaruh Merger, Pergantian Manajemen, Ketidakpuasan Perusahaan, Fee Audit, dan Audit Delay pada Auditor Switching

2020 ◽  
Vol 1 (1) ◽  
pp. 1-17
Author(s):  
Nonik Dia Permatasari ◽  
Haifah Haifah ◽  
Nanda Widaninggar
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Stock Exchange ◽  
Secondary Data ◽  
Audit Fees ◽  
Manufacturing Companies ◽  
Management Change ◽  
Auditor Switching

This study was conducted to find the effect of merger, management change, company dissatisfaction, audit fees, audit delay on auditor switching turnover in manufacturing companies listed on the Indonesian Stock Exchange (BEI) in 2014-2018. Data used in this study namely secondary data of companies listed on the Indonesia Stock Exchange in 20142018 with a sample of 76 companies. This study used logistic regression analysis. The results confirmed that (1) the merger variable had no effect on auditor switching (2) management change variable had no effect on auditor switching (3) company dissatisfaction had an effect on auditor switching (4) audit fees had an effect on auditor switching (5) audit delay had an effect on auditor switching.

scholarly journals The Influence of Previous Audit Opinion, Audit Tenure and Liquidity toward Going Concern Opinion in Manufacturing Companies for the Period of 2015-2017

2019 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Cindy Saputra Kuswara ◽  
Ery Yanto
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Significant Influence ◽  
Manufacturing Companies ◽  
Analysis Method ◽  
Audit Opinion ◽  
Going Concern ◽  
Going Concern Opinion ◽  
The Relationship

Going Concern Opinion issued by auditor when there is doubt of a company’s ability to continue as going concern. This research have the objective to determine the relationship between Previous Audit Opinion, Audit Tenure and Liquidity with Going Concern Opinion in manufacturing companies listed in IDX form years 2015 until 2017. The population of this research is 156 with total of sample are 37 manufacturing companies. The research of data using descriptive statistic and logistic regression analysis method. The result shows that Previous Audit Opinion and Liquidity have significant influence toward Going Concern Opinion and Audit Tenure does not have significant influence toward Going Concern Opinion.

scholarly journals Faktor-Faktor Yang Mempengaruhi Keputusan Teknologi Panen Dan Dampaknya Terhadap Pendapatan Usahatani Padi Di Kabupaten Aceh Besar

2019 ◽  
Vol 4 (1) ◽  
pp. 58
Author(s):  
Sri Mulyani ◽  
F Fajri ◽  
Suyanti Kasimin
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Data Analysis ◽  
Logistic Regression Analysis ◽  
Secondary Data ◽  
T Test ◽  
Working Time ◽  
Purposive Sampling ◽  
Post Harvest ◽  
Combine Harvester

This research aims to find out (1) some factors that influence the farmers in using post-harvest technology equipment in Aceh Besar Regency (2) the differences of farmers income using combine harvester and power thresher. The respondents were selected by purposive sampling in 3 Sub-district in Aceh Besar, the amount of the farmers was taken by Slovin’s. The data used were primary and secondary data and the method of the data analysis were logistic regression analysis and t test. The result of this research showed that the selected of post-harvest technology equipment and education influence the labor and grain dryness while the machine working time and grain dryness did not significantly influenced the farmers in choosing the technology of post-harvest equipment and there was a different income for the using of power thresher and combine harvester at 21,69%.

Investing Behaviour of the IT Millennials with Respect to Retirement Planning

2019 ◽  
Vol 9 (8) ◽  
pp. 188-201
Author(s):  
Rashmy Moray ◽  
Vanishree Pabalkar ◽  
Nema Buch
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Predictive Model ◽  
Logistic Regression Analysis ◽  
Financial Planning ◽  
Representative Sample ◽  
Retirement Planning ◽  
Demographic Variables ◽  
It Industry ◽  
The Relationship

The objective of this study is to identify the demographic factors and behavioural biases affecting the financial planning of the Millennials. For this purpose the investing behaviour of the Millennials in the IT Industry as a representative sample with respect to retirement planning has been studied using the Retirement Wellness Score. Logistic regression analysis was performed to determine the likelihood of whether the Millennials are ready for retirement with the main aim of showing the relationship between the study variables. An attempt has been made to develop a predictive model that would help in determining the Millennials’ readiness for retirement given their demographic variables and dominant bias presence. This research contributes to developing an understanding of Millennials’ financial planning for retirement.

scholarly journals Socio-economic and demographic correlates of stunting among adolescents of Assam, North- east India

2016 ◽  
Vol 79 (4) ◽  
pp. 409-425 ◽  
Author(s):  
Melody Seb Rengma ◽  
Kaushik Bose ◽  
Nitish Mondal
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Multiple Logistic Regression Analysis ◽  
Demographic Variables ◽  
Multiple Logistic Regression ◽  
North East India ◽  
North East ◽  
Demographic Correlates ◽  
Height For Age

AbstractThe prevalence of stunting (low height-for-age) is a key indicator of long-term chronic undernutrition which reflects an anthropometric failure to reach linear growth potentials due to prolonged food deprivation and/or disease or illness during the early stage of life. The present study assesses the prevalence and socio-economic and demographic correlates of stunting among adolescents of the North-east India. This cross-sectional study was undertaken among 1,818 (830 boys; 988 girls) adolescents (aged 10-18 years) belonging to ethnically heterogeneous populations of Karbi Anglong district of Assam, using stratified random sampling method. Anthropometric measurements of height and weight were recorded using standard procedures. Socio-economic and demographic variables were obtained using pre-structured schedule. The age-sex specific L, M and S reference values were used to calculate height-for-age Z-score (HAZ). According to WHO, HAZ found to be <−2SD was classified as stunting. The data were analysed using descriptive statistics, t-test, ANOVA, chi-square analyses, binary and step-wise multiple logistic regression analysis in SPSS (version, 17.0). The prevalence of stunting was observed to be significantly higher among boys (48.4%) than girls (37.8%) (p<0.01). Age-sex specific prevalence was found to be higher among boys than girls aged 14-18 years and contrary were observed among girls aged 10-14 years (p>0.05). The binary logistic regression analysis showed that several socio-economic and demographic variables were significantly associated with stunting (p<0.05). The step-wise multiple logistic regression analysis showed that sex (boys), age groups (13-15 years and 16-18 years), father’s occupation (cultivator) and Rupees ≤5000 household income was significantly associated with stunting (p<0.05). Appropriate nutritional intervention programmes and dissemination of knowledge at population level related to undernutrition are necessary to ameliorate their nutritional status.

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