scholarly journals PELUANG TERJADINYA PENGANGGURAN DI PROVINSI BENGKULU : SEBERAPA BESAR?

2020 ◽  
Vol 1 (2) ◽  
pp. 70-83
Author(s):  
Lisa Marini ◽  
Novi Tri Putri
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Marital Status ◽  
Labor Force ◽  
Logistic Regression Analysis ◽  
Work Experience ◽  
Population Characteristics ◽  
Training Course ◽  
Labor Force Survey ◽  
The Family

The aim of this research is to analyze how are opportunity occured unemployment based on characteristics of populations in Bengkulu province. Characteristics of populations that used are education, training/course certificate, age, gender, work experience, marital status, status in the family, and area of residence. The analytical method used to achieve this goal is the logistic regression analysis. Type of key data use row data derived from the National Labor Force Survey (Sakernas) February 2018. The result of the calculation using the program SPSS 20.0 was found that not all the variables of population characteristics significantly affect the chances of unemployment with a confidence level of 95 percent. Education and age are significantly affect of unemployment in Bengkulu Province, while training/course certificate, gender, work experience, marital status, status in the family and area residence are not significantly affect of unemployment in Bengkulu Province. Keywords: Logistic Regression Analysis, National Labor Force Survey  (Sakernas), Unemployment.

scholarly journals PELUANG ALUMNI PENDIDIKAN MATEMATIKA FKIP UMB DALAM MENDAPATKAN PEKERJAAN DENGAN MENGGUNAKAN ANALISIS REGRESI LOGISTIK

2017 ◽  
Vol 10 (2) ◽  
pp. 85
Author(s):  
Mahyudi Mahyudi
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Mathematics Education ◽  
Survey Data ◽  
Logistic Regression Analysis ◽  
Work Experience ◽  
National Origin ◽  
College Graduation ◽  
The Road ◽  
Ordinal Logistic Regression Analysis

Graduation or college graduation become the most exciting moment for a student. In addition to successfully get a degree, they are also eager to enter the workforce. But sometimes the spirit was lost in the middle of the road. Many fresh graduates complain of difficult to get a job at this time. Every year the number of graduates to grow while jobs are not directly proportional to the increase in the number of graduates. The study analyzed what are the chances of graduates Mathematics Education FKIP Muhammadiyah University of Bengkulu in getting a job. Samples taken as many as 78 graduates between September 2015 to April 2016. The factors considered were gender, age, GPA, national origin, jobs for college and the work areas as desired. Analysis of survey data using ordinal logistic regression analysis. The results showed that the dominant factors that affect the length of the graduates in getting a job is GPA, work experience in college and the desired field of work.

Social and Environmental Influences on Child Mortality in Brazil: Logistic Regression Analysis of Data from Census Files

1986 ◽  
Vol 18 (1) ◽  
pp. 87-102 ◽  
Author(s):  
Cesar G. Victora ◽  
Peter G. Smith ◽  
J. Patrick Vaughan
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Child Mortality ◽  
Logistic Regression Analysis ◽  
Family Income ◽  
Census Data ◽  
Multivariate Logistic Regression Analysis ◽  
Childhood Mortality ◽  
Piped Water ◽  
The Family

SummaryCensus data were used to investigate the influences of socioeconomic and environmental variables on child mortality rates in southern Brazil. By multivariate logistic regression analysis the effects of correlated factors were distinguished, after adjustment for maternal age and parity. Low family income and, to a lesser degree, low employment status of the head of the family were associated with high child mortality levels. Place of residence, education of the mother and of the head of the family, availability of piped water in the home, access to a toilet and type of housing were all associated with childhood mortality variation, even after allowing for the effects of income and employment. The contributions of the source of the water supply and type of sanitation facilities, however, were less clear and tended to become unimportant after controlling for the socioeconomic variables. There was also no apparent advantage in being covered by government health insurance.

scholarly journals Should I Stay or should I Go? Determinants of Evacuation upon Flood Warning among Households in a Flood Prone Area in Bukidnon, Philippines

2016 ◽  
Vol 50 ◽  
pp. 70-75 ◽  
Author(s):  
Michael Arieh P. Medina ◽  
Jackielyn M. Moraca
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
College Education ◽  
The Philippines ◽  
Flood Warning ◽  
The Family ◽  
Prone Area ◽  
Flood Prone Area ◽  
Socio Demographic Factors

To identify factors that influence the decision to evacuate upon flood warning by authorities, a study was conducted in a flood prone area in the province of Bukidnon in the Philippines. A survey of flood victims was conducted in Batangan Village, Valencia City, Bukidnon, Philippines wherein 150 respondents were interviewed. Logistic regression analysis was done to test the socio demographic factors that could influence a family’s decision to either evacuate or stay upon advice by government authorities. College education, presence of children in the home, poverty, and extent of flood experienced were found to significantly influence the decision of the family to evacuate. Based on this information, the study provides recommendations for disaster managers in case of future flood incidence in the area.

scholarly journals Agripreneurship and Agricultural Labour Market: Agripreneurial Intentions among Undergraduate Students in Ondo State, NigeriaAgripreneurship and Agricultural Labour Market: Agripreneurial Intentions among Undergraduate Students in Ondo State, Nigeria

2021 ◽  
Vol 3 (3) ◽  
pp. 76-85
Author(s):  
E. S. Ikuemonisan ◽  
A. E. Akinbola
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Labour Market ◽  
Undergraduate Students ◽  
Logistic Regression Analysis ◽  
Tertiary Institutions ◽  
Socioeconomic Characteristics ◽  
The Family ◽  
Ondo State ◽  
The Mean

This study examined agripreneurial intentions among students in the state-owned tertiary institutions in Ondo State. The study profiled students’ perceptions of learning (SPOL), teachers’ impact (SPOT), and mentorship and explored the effects of these on their agripreneurial intentions. Both descriptive and inferential statistics were used to analyze 120 students, who were randomly selected from the two state-owned tertiary institutions. A logistic regression analysis was performed to assess the effects of SPOL, SPOT, mentorship, as well as other socioeconomic characteristics, on students’ likelihood to have agripreneurial intentions. The study revealed that SPOL, SPOT & age significantly increased the likelihood of students having agripreneurial intentions, while perceptions of mentorship and the number of graduates in the family decreased it. Although the SPOL and SPOT were positive and statistically significant, the weak effects of the mean scores suggest that SPOL and SPOT should be improved upon to enhance students’ interest in agripreneurship.

scholarly journals Cohort research analysis of disaster experience, preparedness, and competency-based training among nurses

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244488 ◽  
Author(s):  
Krzysztof Goniewicz ◽  
Mariusz Goniewicz ◽  
Frederick M. Burkle ◽  
Amir Khorram-Manesh
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Work Experience ◽  
Disaster Response ◽  
Core Competencies ◽  
Statistical Significance ◽  
Significance Level ◽  
Disaster Experience ◽  
Training Programmes

Introduction It is expected that in unforeseen situations, nurses will provide appropriate medical interventions, using their expertise and skills to reduce the risks associated with the consequences of disasters. Consequently, it is crucial that they are properly prepared to respond to such difficult circumstances. This study aimed to identify the factors influencing the basic competences of nurses in disasters. Materials and methods The survey was directed to 468 nurses from all medical centres in Lublin. IBM SPSS Statistics version 23 was used for statistical analyses, frequency analysis, basic descriptive statistics and logistic regression analysis. The classical statistical significance level was adopted as α = 0.05. Results Based on the logistic regression analysis, it was found that work experience, workplace preparedness, as well as training and experience in disaster response are important predictors of preparedness. Conclusions These findings indicate that the nurses' core competencies for these incidents can be improved through education and training programmes which increase their preparedness for disasters. Nurses are among the most important groups of healthcare professionals facing a disaster and should be involved in all phases of disaster management, such as risk assessment and pre-disaster planning, response during crisis situations and risks’ mitigation throughout the reconstruction period.

scholarly journals FENOMENA MIGRASI SIRKULER DI KOTA MATARAM

GANEC SWARA ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 557
Author(s):  
NI PUTU FEBBY SUNDARI ◽  
PUTU KARISMAWAN ◽  
EMY SALMAH
Keyword(s):  
Distance Education ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Marital Status ◽  
Logistic Regression Analysis ◽  
Education Level ◽  
Level Of Education ◽  
Working Age ◽  
Labor Resources ◽  
The City

Theoretically, development of the city depends on labor resources. Generally, labor resources of the city come from periphery area. Developed infrastructure is a factor that mobilized labor resources from periphery to the city. There are two alternatives to the workers who come from periphery area; first they can stay in the city by renting apartment or the second as commuter. Many of the workers choose as commuter, so it is quite interesting to know what factors influence workers make choice as commuter. It is more specific whether factors such as income, length of work, age, distance, education level, and marital status influence the interest of workers to conduct circular migration. The analytical tool used is logistic regression analysis, Binary Regression Logistic. This research is a descriptive study that uses quantitative analysis using 1 dependent variable, namely interest in migration and six independent variables, namely income, length of working, age, distance, education level, and marital status. To achieve these objectives in this research logistic regression analysis was used, namely Binary Regression using primary data as many as 80 respondents. The results show that above variables; income, length of working, age, distance, level of education and marital status simultaneously and significantly influence on interest of workers in doing circulation migration to the Mataram City. Factors that partially influence significantly on the interest of workers doing migration to the Mataram City with a significance value with an alpha level of 5% are income, length of working, distance and level of education. While the age variable and marital status is not significant in effect.

scholarly journals PENGANGGURAN USIA MUDA DI JAWA BARAT (MENGGUNAKAN DATA SAKERNAS)

2019 ◽  
pp. 1049
Author(s):  
Adhitya Wardhana ◽  
Bayu Kharisma ◽  
Yayuf Faridah Ibrahim
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Marital Status ◽  
Logistic Regression Analysis ◽  
Youth Unemployment ◽  
Young Age ◽  
Crucial Issue ◽  
West Java ◽  
Micro Level ◽  
High Level

The high level of open unemployment at a young age in West Java Province is a crucial issue in the field of employment. This study aims to determine the factors that influence youth unemployment in West Java Province at the micro level. The results of the logistic regression analysis show that age, marital status, status in the household, education and household size have a significant impact on the probability of unemployment at a young age in West Java.

scholarly journals Status of Two-week Prevalence Rate in Tibet: Data Base on the Sixth Health Service Survey of Tibet, China

2019 ◽  
Author(s):  
Rendan Deng ◽  
Laba sangzhu ◽  
Zhaxi deji ◽  
Guihua Wang ◽  
Peiwei Hong ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Health Service ◽  
Marital Status ◽  
Logistic Regression Analysis ◽  
Prevalence Rate ◽  
Employment Status ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Important Indicator

Abstract Background Tibet is located in the high altitude area of southwest China, which health level is influenced by specific factors. However, there was little research on Tibetan health condition. And the two-week prevalence rate is an important indicator to health status of residents. The purpose of this study was to understand the two-week prevalence rate and its influencing factors in Tibet. Methods Two-week prevalence rate was calculated using data from a population of 10493 aged 15 and above obtained from the sixth Health Service Survey of Tibet in 2018. Multivariate logistic regression analysis was used to further screen factors for gender, age, marital status, employment status and so on. Results The two-week illness prevalence rate was 20.1% in Tibet. According to the Multivariate logistic regression analysis the two-week prevalence rate was associated with gender, age, residence, marital status, employment status, respectively. Digestive system diseases are given priority, hypertension is the most common disease. Besides, the severity of two-week illness has differences in different groups. Conclusion This study identified a number of factors that appear to have a significant relationship with the two-week illness prevalence. Moreover, the two-week prevalence rates of women and older people were significantly higher, which should be paid attention to in the utilization of health services.

ANALISIS HUBUNGAN SARANA, PENGETAHUAN, DAN SIKAP BIDAN PRAKTIK MANDIRI DENGAN KEPATUHAN MENJALANKAN STANDAR PELAYANAN ANTENATAL CARE DI KOTA PADANGSIDIMPUAN

2019 ◽  
Vol 2 (1) ◽  
pp. 27-33
Author(s):  
Megawati Sinambela ◽  
Evi Erianty Hasibuan
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Antenatal Care ◽  
Pregnant Women ◽  
Logistic Regression Analysis ◽  
Care Service ◽  
Multivariate Logistic Regression Analysis ◽  
Bivariate Analysis ◽  
Cross Sectional ◽  
The North

Antenatal care is a service provided to pregnant women to monitor, support maternal health and detect mothers whether normal or problematic pregnant women. According to the WHO, globally more than 70% of maternal deaths are caused by complications of pregnancy and childbirth such as hemorrhage, hypertension, sepsis, and abortion. Based on data obtained from the profile of the North Sumatra provincial health office in 2017, in the city of Padangsidimpuan in 2017 the coverage of ANC visits reached (76.58%) and had not reached the target in accordance with the 2017 Provincial Health Office strategy plan (95%). This type of research was an observational analytic study with a cross sectional design. The population in this study were independent practice midwives who were in the Padangsidimpuan, the sample in this study amounted to 102 respondents. The technique of collecting data used questionnaires and data analysis used univariate, bivariate and multivariate analysis with logistic regression analysis. Based on bivariate analysis showed that there was a relationship between facilities, knowledge and attitudes of independent midwives with compliance with the standards of antenatal care services with a value of p <0.05. The results of the study with multivariate logistic regression analysis showed that the factors associated with the compliance of independent midwives in carrying out antenatal care service standards were attitudes with values (p = 0.026).

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