scholarly journals The Determinant Factors of Muzakki Toward Paying Zakat, Infaq, Sedekah (ZIS) in Zakat Institutions

2020 ◽  
Vol 3 (2) ◽  
pp. 143
Author(s):  
Hening Pratika Nila Hapsari ◽  
Unggul Priyadi
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Regression Model ◽  
Logistic Regression Analysis ◽  
Logistic Regression Model ◽  
Primary Data ◽  
Role Of Government ◽  
Financial Accountability ◽  
Objective Study

Introductions to The Problem: Zakat is one of worship which is often mentioned in the Al Quran. It's just that the potential for Zakat, Infaq, Alms (ZIS) is not comparable to the actual actual figures. Many factors influence muzakki in paying ZIS.Purpose/Objective Study: This study aims to analyze the factors that influence muzakki to pay ZIS in zakat institutions, namely Yatim MandiriDesign/ Methodology/ Approach: The sample in this study amounted to 200 respondents. LAZ Yatim Mandiri was chosen because it is an Amil Zakat Institution that is consistent in collecting ZIS funds from the smallest amount to the large amount. This study uses logistic regression analysis and the data used are primary data. Based on the analysis that has been done, it is found that 61% results can be predicted correctly in the logistic regression model in this study.Findings: The consistency of muzakki in paying ZIS at the Yatim Mandiri Amil Zakat Institution is influenced by the variables of religiosity, income, trust, shariah compliance, knowledge, justice, data publication, financial accountability, motivation, the role of ulama, the role of government. And the consistency of muzakki in paying ZIS at the Yatim Mandiri Amil Zakat Institution is not influenced by the variables of shariah compliance and financial accountability.

scholarly journals Understanding Primary Ciliary Dyskinesia: Experience From a Mediterranean Diagnostic Reference Centre

2020 ◽  
Vol 9 (3) ◽  
pp. 810
Author(s):  
Miguel Armengot-Carceller ◽  
Ana Reula ◽  
Manuel Mata-Roig ◽  
Jordi Pérez-Panadés ◽  
Lara Milian-Medina ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Regression Model ◽  
Logistic Regression Analysis ◽  
Situs Inversus ◽  
Primary Ciliary Dyskinesia ◽  
Logistic Regression Model ◽  
Productive Cough ◽  
Simple Logistic ◽  
Ciliary Dyskinesia

Background: Due to the lack of a gold standard diagnostic test, reference centres with experienced personnel and costly procedures are needed for primary ciliary dyskinesia (PCD) diagnostics. Diagnostic flowcharts always start with clinical symptoms. Therefore, the aim of this work is to define differential clinical criteria so that only patients clinically compatible with PCD are referred to reference centres. Materials and methods: 18 variables from 476 Mediterranean patients with clinically suspicious PCD were collected. After analysing cilia function and ultrastructure, 89 individuals were diagnosed with PCD and 387 had a negative diagnosis. Simple logistic regression analysis, considering PCD as a dependent variable and the others as independent variables, was done. In order to define the variables that best explain PCD, a step-wise logistic regression model was defined. Aiming to classify individuals as PCD or PCD-like patients, based on variables included in the study, a classification and regression tree (CART) was designed. Results and conclusions: Simple logistic regression analysis shows statistically significant association between age at the beginning of their symptomatology, periodicity, fertility, situs inversus, recurrent otitis, atelectasis, bronchiectasis, chronic productive cough, rhinorrea, rhinusinusitis and recurrent pneumonias, and PCD. The step-wise logistic regression model selected situs inversus, atelectasis, rhinorrea, chronic productive cough, bronchiectasis, recurrent pneumonias, and otitis as PCD predictive variables (82% sensitivity, 88% specificity, and 0.92 Area Under the Curve (AUC)). A decision tree was designed in order to classify new individuals based on pansinusitis, situs inversus, periodicity, rhinorrea, bronchiectasis, and chronic wet cough.

scholarly journals LOGISTIC REGRESSION ON THE PRIMIPARAL AGE OF WOMEN IN GOMBE, GOMBE STATE

2020 ◽  
Vol 5 (7) ◽  
pp. 7-16
Author(s):  
A.U. Kinafa ◽  
M.B. Mohammed ◽  
A. Abdulkadir
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Regression Model ◽  
Logistic Regression Analysis ◽  
Logistic Regression Model ◽  
Healthcare Providers ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Challenging Problem ◽  
First Child

Failure of women to undergo a successful first child delivery is becoming one of the most challenging problem and a major concern to most of our healthcare providers. In this paper, we apply the binary logistic regression analysis to investigate whether age of women at first birth have a relationship with the outcome of their delivery (Success or failure). The data was collected from Gombe Town Maternity and was subjected to analysis. From the result of the analysis, we observed that most of the women at tender age (12-17) are classified to fail (69%) during their first child delivery while most of the women at higher age (19 and above) have a better chance of succeeding during their first parturition. Also, the result shows that the average age at which women ought to conceive successfully is 19 years. The Wald statistics result also shows that the logistic regression model fits the data very well.

scholarly journals Gender and Age Differences in the Study Plan of University Students

2020 ◽  
Vol 14 (01) ◽  
pp. 62 ◽  
Author(s):  
Hilary I Okagbue ◽  
Sheila A Bishop ◽  
Anjoreoluwa E Boluwajoko ◽  
Adaeze M Ezenkwe ◽  
Glory N Anene ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Undergraduate Students ◽  
Logistic Regression Model ◽  
Simple Random Sampling ◽  
Chi Square ◽  
Ogun State ◽  
Gender And Age ◽  
Study Plan

<p class="0abstract">Effective study plan is a predictor of good academic performance. However, there are few evidences available on the role of gender and age in the study plan for students. This paper investigated the role of gender and age in the adoption of study plan that can guarantee success. A questionnaire was designed and administered to undergraduate students of a world class privately funded university located in Ogun State, Nigeria. Simple random sampling was used and 294 students responded. Chi-square test of independence revealed that gender and age are not associated with frequency of study, study environment, study content preferences and study motivation. There is no Gender difference in the preference of study type, factors that drive, motivation for study and satisfaction with the study plan whereas, age is significantly associated. The logistic regression model was significant and correctly classified 66.3% of satisfaction with the study plan. Gender was not significant and age of students can predict their satisfaction with their study plan. Older students have more odds to be satisfied with their study plan. As students progressed from year one to the final year, they tend to adopt a study plan that can help them obtain high grades and graduate with good result. Artificial Neural Network correctly classified 71.4% of satisfaction using only age as the only factor because, only age contributed significantly to the logistic regression model. Timely academic advising or mentorship is advocated especially for freshers.</p>

Role of social performance in predicting learning problems: Prediction of risk using logistic regression analysis

2012 ◽  
Vol 33 (6) ◽  
pp. 615-630 ◽  
Author(s):  
Zilda Aparecida Pereira Del Prette ◽  
Almir Del Prette ◽  
Lael Almeida De Oliveira ◽  
Frank M. Gresham ◽  
Michael J. Vance
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Social Performance ◽  
Learning Problems

scholarly journals Circulating miR-30d Predicts Survival in Patients with Acute Heart Failure

2017 ◽  
Vol 41 (3) ◽  
pp. 865-874 ◽  
Author(s):  
Junjie Xiao ◽  
Rongrong Gao ◽  
Yihua Bei ◽  
Qiulian Zhou ◽  
Yanli Zhou ◽  
...  
Keyword(s):  
Heart Failure ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Univariate Logistic Regression Analysis ◽  
Kaplan Meier ◽  
All Cause Mortality

Background/Aims: Identification of novel biomarkers to identify acute heart failure (AHF) patients at high risk of mortality is an area of unmet clinical need. Recently, we reported that the baseline level of circulating miR-30d was associated with left ventricular remodeling in response to cardiac resynchronization therapy in advanced chronic heart failure patients. However, the role of circulating miR-30d as a prognostic marker of survival in patients with AHF has not been explored. Methods: Patients clinically diagnosed with AHF were enrolled and followed up for 1 year. Quantitative reverse transcription polymerase chain reactions were used to determine serum miR-30d levels. The univariate logistic regression analysis and multivariate logistic regression analysis were used to determine the predictors for all-cause mortality in AHF patients. Kaplan–Meier survival analysis was used to analyze the role of miR-30d in prediction of survival. Results: A total of 96 AHF patients were enrolled and followed up for 1 year. Serum miR-30d was significantly lower in AHF patients who expired in the one year follow-up period compared to those who survived. Univariate logistic regression analysis yielded 18 variables that were associated with all-cause mortality in AHF patients, while the multivariate logistic regression analysis identified 4 variables including heart rate, hemoglobin, serum sodium, and serum miR-30d level associated with mortality. ROC curve analysis showed that hemoglobin, heart rate and serum sodium displayed poor prognostic value for AHF (AUCs not higher than 0.700) compared to miR-30d level (AUC = 0.806). Kaplan–Meier survival analysis confirmed that patients with higher serum miR-30d levels had significantly lower mortality (P=0.001). Conclusion: In conclusion, this study shows evidence for the predictive value of circulating miR-30d as 1-year all-cause mortality in AHF patients. Large multicentre studies are further needed to validate our findings and accelerate the transition to clinical utilization.

scholarly journals Determinants of acute respiratory infection among under-five children in rural Ethiopia

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Amanuel Mengistu Merera
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Regression Model ◽  
Respiratory Infection ◽  
Acute Respiratory Infection ◽  
Logistic Regression Model ◽  
P Value ◽  
Under Five ◽  
Under Five Children ◽  
Rural Ethiopia

Abstract Introduction In low- and middle-income nations, acute respiratory infection (ARI) is the primary cause of morbidity and mortality. According to some studies, Ethiopia has a higher prevalence of childhood acute respiratory infection, ranging from 16 to 33.5%. The goal of this study was to determine the risk factors for acute respiratory infection in children under the age of five in rural Ethiopia. Methods A cross-sectional study involving 7911 children under the age of five from rural Ethiopia was carried out from January 18 to June 27, 2016. A two stage cluster sampling technique was used recruit study subjects and SPSS version 20 was used to extract and analyze data. A binary logistic regression model was used to identify factors associated with a childhood acute respiratory infection. The multivariable logistic regression analysis includes variables with a p-value less than 0.2 during the bivariate logistic regression analysis. Adjusted odds ratios were used as measures of effect with a 95% confidence interval (CI) and variables with a p-value less than 0.05 were considered as significantly associated with an acute respiratory infection. Results The total ARI prevalence rate among 7911 under-five children from rural Ethiopia was 7.8%, according to the findings of the study. The highest prevalence of ARI was found in Oromia (12.8%), followed by Tigray (12.7%), with the lowest frequency found in Benishangul Gumuz (2.4%). A multivariable logistic regression model revealed that child from Poor household (AOR = 2.170, 95% CI: 1.631–2.887), mother’s no education (AOR = 2.050,95% CI: 1.017–4.133), mother’s Primary education (AOR = 2.387, 95% CI:1.176–4.845), child had not received vitamin A (AOR = 1.926, 95% CI:1.578–2.351), child had no diarrhea (AOR = 0.257, 95% CI: 0.210–0.314), mothers not working (AOR = 0.773, 95% CI:0.630–0.948), not stunted (AOR = 0.663, 95% CI: 0.552–0.796), and not improved water source (AOR = 1.715, 95% CI: 1.395–2.109). Similarly, among under-five children, the age of the child, the month of data collection, anemia status, and the province were all substantially linked to ARI. Conclusions Childhood ARI morbidity is a serious health challenge in rural Ethiopia, according to this study, with demographic, socioeconomic, nutritional, health, and environmental factors all having a role. As a result, regional governments, healthcare staff, and concerned groups should place a priority on reducing ARI, and attempts to solve the issue should take these variables into account.

scholarly journals Challenges of and Opportunities for Market Access by Pineapple Agripreneurs in Rangwe Sub County, Homa Bay County, Kenya

2021 ◽  
pp. 130-140
Author(s):  
Winstone Asugo Nyaguti ◽  
Job Kibiwot Lagat ◽  
Hillary Bett ◽  
Fredrick Onyango Ogutu
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Model ◽  
Market Access ◽  
Descriptive Analysis ◽  
Household Head ◽  
Education Level ◽  
Primary Data ◽  
Limited Attention ◽  
Survey Tool

Pineapple farming is among the fastest-growing agricultural sub-sectors in Homa Bay County, Kenya specifically Rangwe sub-county. However, limited attention has been given to the market access of this produce. Evidenced by vast quantities of pineapples harvested from the farms and stacked along main highways without targeting a specific market. This result to a small portion being sold and the rest deteriorating, consequently reducing returns for pineapple agripreneurs. Therefore, this paper sought to determine those factors that influences access to formal market by pineapple agripreneurs and as well as find out challenges of and opportunities for accessing formal markets by the Rangwe pineapple agripreneurs. The survey was undertaken in Rangwe Sub-county, and multisampling method was used to select a sample of 183 pineapple agripreneurs from the study area, primary data was collected using a semi-structured survey tool. Data was analyzed by descriptive analysis and Logistic regression model. Results indicated that pineapple agripreneurs were faced with numerous challenges in accessing pineapple market, also there existed several market access opportunities for pineapple agripreneurs. The results of logistic regression analysis revealed extension contacts, education level and price of pineapple as factors that were positively and statistically significant in influencing access to formal markets. While those that were statistically and negatively influencing access to formal market comprised of; age of household head, household size, and type of road. The study recommends;  improvement of road infrastructure in pineapple producing areas so as to improve on their market access; development of policies that encourages capacity building of pineapple agripreneurs in Rangwe sub-county 

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 Determinants of Acute Respiratory Infection among Under-Five Children in Rural Ethiopia

2021 ◽  
Author(s):  
Amanuel Mengistu Merera
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Regression Model ◽  
Respiratory Infection ◽  
Acute Respiratory Infection ◽  
Logistic Regression Model ◽  
P Value ◽  
Under Five ◽  
Under Five Children ◽  
Rural Ethiopia

Abstract Introduction: In low- and middle-income nations, acute respiratory infection (ARI) is the primary cause of morbidity and mortality. According to some studies, Ethiopia has a higher prevalence of childhood acute respiratory infection, ranging from 16 % to 33.5 %. The goal of this study was to determine the risk factors for acute respiratory infection in children under the age of five in rural Ethiopia. Methods: A cross-sectional study involving 7,911 children under the age of five from rural Ethiopia was carried out from January 18 to June 27, 2016. A two stage cluster sampling technique was used recruit study subjects and SPSS version 20 was used to extract and analyze data. A binary logistic regression model was used to identify factors associated with a childhood acute respiratory infection. The multivariable logistic regression analysis includes variables with a p-value less than 0.2 during the bivariate logistic regression analysis. Adjusted odds ratios were used as measures of effect with a 95% confidence interval (CI) and variables with a p-value less than 0.05 were considered as significantly associated with an acute respiratory infection. Results: The total ARI prevalence rate among 7,911 under-five children from rural Ethiopia was 7.8%, according to the findings of the study. The highest prevalence of ARI was found in Oromia (12.8 %), followed by Tigray (12.7 %), with the lowest frequency found in Benishangul Gumuz (2.4 %). A multivariable logistic regression model revealed that child from Poor household (AOR=2.170, 95% CI: 1.631-2.887), mother’s no education (AOR=2.050,95% CI: 1.017-4.133), mother’s Primary education (AOR=2.387, 95% CI:1.176-4.845), child had not received vitamin A (AOR=1.926, 95% CI:1.578-2.351), child had no diarrhea (AOR=0.257, 95% CI: 0.210-0.314), mothers not working (AOR=0.773, 95% CI:0.630-0.948), not stunted (AOR=0.663, 95% CI: 0.552-0.796), and not improved water source (AOR=1.715, 95% CI: 1.395-2.109). Similarly, among under-five children, the age of the child, the month of data collection, anemia status, and the province were all substantially linked to ARI. Conclusions: Childhood ARI morbidity is a serious health challenge in rural Ethiopia, according to this study, with demographic, socioeconomic, nutritional, health, and environmental factors all having a role. As a result, regional governments, healthcare staff, and concerned groups should place a priority on reducing ARI, and attempts to solve the issue should take these variables into account.

Sign in / Sign up

Export Citation Format

Share Document