Factors Affecting Employee Attrition and Predictive Modelling Using IBM HR Data

2019 ◽  
Vol 16 (8) ◽  
pp. 3379-3383
Author(s):  
Emad Afaq Khan ◽  
Sumaira Muhammad Hayat Khan
Keyword(s):  
Logistic Regression ◽  
Feature Selection ◽  
Confusion Matrix ◽  
Predictive Modelling ◽  
Problem Statement ◽  
Chi Square ◽  
Factors Affecting ◽  
The Past ◽  
Class 1 ◽  
Employee Attrition

Attrition can be defined as the gradual reduction of a member or person in an organization due to retirement, resignation, or death. The loss can be defined as the number of employees leaving the organization, including voluntary and involuntary resignations. This study is about identifying the factors that affect the attrition and establishing a predictive model for employee attrition. The study first focuses on the problem statement and a breakdown on what attrition does to the organization. Followed by a detailed conceptual breakdown on attrition which is then discussed in the light of predictive modeling with the past supporting researches. The research involves data preprocessing with chi square versus logistic regression for feature selection, machine learning models and their comparison using the confusion matrix, precision, recall and f1-scores. The best results obtained was the logistic regression model with feature selection and the accuracy of the model is 86% with a 98% recall for the class 1 of attrition. The researcher wants to change the view on how attrition problem is tackled. Rather than knowing who to retain, the organization should know who to hire. This research sets a ground rule and tries to change the perspective on tackling the attrition problem.

scholarly journals Predictive Modelling of Employee Turnover in Indian IT Industry Using Machine Learning Techniques

2019 ◽  
Vol 23 (1) ◽  
pp. 12-21 ◽  
Author(s):  
Shikha N. Khera ◽  
Divya
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Confusion Matrix ◽  
Predictive Modelling ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
It Industry ◽  
Knowledge Based ◽  
Employee Attrition

Information technology (IT) industry in India has been facing a systemic issue of high attrition in the past few years, resulting in monetary and knowledge-based loses to the companies. The aim of this research is to develop a model to predict employee attrition and provide the organizations opportunities to address any issue and improve retention. Predictive model was developed based on supervised machine learning algorithm, support vector machine (SVM). Archival employee data (consisting of 22 input features) were collected from Human Resource databases of three IT companies in India, including their employment status (response variable) at the time of collection. Accuracy results from the confusion matrix for the SVM model showed that the model has an accuracy of 85 per cent. Also, results show that the model performs better in predicting who will leave the firm as compared to predicting who will not leave the company.

Factors Affecting Implementation of Activity Based Costing in Selected Manufacturing Units in India

2019 ◽  
Vol 8 (3) ◽  
pp. 18-30
Author(s):  
Amit Kumar Arora ◽  
M.S.S. Raju
Keyword(s):  
Logistic Regression ◽  
Firm Size ◽  
Cost Accounting ◽  
Activity Based Costing ◽  
Chi Square ◽  
Factors Affecting ◽  
Total Cost ◽  
Overhead Cost ◽  
Chi Square Test ◽  
Size Diversity

The present article is an attempt to analyze the various factors affecting the adoption of an activity-based costing (ABC) system in selected manufacturing units in India. The following seven factors are considered: firm size, diversity of the product, percentage of overhead cost in total cost, listing of the company, cost audit compulsion, separate cost accounting department and the method of accounting. Logistic regression and a Chi Square test are applied to these factors and the use of an ABC system. On the basis of 72 sample units, the study found the size of the firm, percentage of overhead cost in total cost, cost audit compulsion and the method of accounting are statistically significant for the adoption of ABC system. While factors such as diversity of the product, separate cost accounting department and the listing of the company are found to not be statistically significant for the adoption of ABC system. The study has provided additional insights into areas relating to the factors affecting the implementation of ABC systems.

scholarly journals Factors affecting the occurrence of proximal endoleak after endovascular abdominal aortic repair for abdominal aneurysms

2020 ◽  
Vol 48 (11) ◽  
pp. 030006052097151
Author(s):  
Daniela Mazzaccaro ◽  
Girolomina Mazzeo ◽  
Gianmarco Zuccon ◽  
Alfredo Modafferi ◽  
Giovanni Malacrida ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Aortic Aneurysms ◽  
P Value ◽  
Chi Square ◽  
Factors Affecting ◽  
Axial Diameter ◽  
Abdominal Aortic ◽  
Type Ia

Objective This retrospective study was performed to assess the clinical and radiological variables associated with proximal type IA endoleak (EL) in patients treated with elective endovascular repair for abdominal aortic aneurysms. Methods The chi-square test, t-test, and logistic regression analysis were performed as appropriate. A P value of <0.05 was considered statistically significant. Results The data of 79 patients were analyzed. No mortality occurred. During follow-up (median, 28.5 months; interquartile range, 12.8–43.0 months), 10 patients developed type IA EL. In the logistic regression analysis, undersizing of the endograft diameter by <10% significantly affected the occurrence of type IA EL. When the diameter was used for measurements, less oversizing was significantly associated with a higher risk of type IA EL. When the area was used for measurements, oversizing of >20% significantly affected the occurrence of type IA EL. Conclusion When sizing endografts, a discrepancy was noted between the measurements of the diameter and area of the proximal neck. The area might represent a more accurate measurement than the axial diameter to optimize the proximal sealing and lower the risk of developing type IA EL.

scholarly journals Effects of the Agri-environmental Program Implemented in Sultan Reeds Area of Kayseri, Turkey

2019 ◽  
Vol 7 (12) ◽  
Author(s):  
Ismet Boz
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Agricultural Practices ◽  
Farm Size ◽  
Chi Square ◽  
Factors Affecting ◽  
Environmental Program ◽  
Chi Square Test ◽  
Sustainable Agricultural Practices

This study was initiated to evaluate the effects of agri-environment program implemented in the Sultan reeds area of Kayseri province, Turkey. The specific objectives of the study were to compare the farmers who enrolled in the program with those who didn’t enroll regarding their application of different sustainable agricultural practices, and to determine factors affecting their enrolment in the program. The main comparative indicators were selected from different sustainable agricultural practices either promoted by the agri-environmental program or not promoted but considered very useful for the locality. Two stratified samples of farmers (enrolled and not enrolled) were selected based on their farm size. Chi-square tests of independence were used to compare farmers on the selected sustainable agricultural practices. Logistic regression model was used to determine factors affecting the enrolment of the agri-environment program. The findings of the chi-square test showed that enrolled farmers use grow more forage legumes, are more conscious about pesticides use and chemical applications, and they use more pressurized irrigation systems. Findings of the logistic regression model sowed that using rental land negatively, but contacts with extension personnel, and using long term loans for farming investments positively influenced the enrolment of the agri-environment program. Governmental effort must concentrate on these issues when promoting agri-environmental programs in the region.

scholarly journals Analysis on factors affecting nausea and vomiting severity suffered by patients in the early phase of hemodialysis therapy

2020 ◽  
Vol 1 ◽  
pp. 30-34
Author(s):  
Muhammad Rafi Fathurrohman ◽  
Sri Suparti
Keyword(s):  
Logistic Regression ◽  
Sampling Technique ◽  
Total Sample ◽  
Nausea And Vomiting ◽  
Bivariate Analysis ◽  
P Value ◽  
Chi Square ◽  
Factors Affecting ◽  
Chi Square Test ◽  
Simple Logistic

Nausea and vomiting should be further checked and prevented, because these conditions can be a cause or complication during hemodialysis patients. Electrolyte and water imbalance (dehydration) can be considered as the main complication of nausea and vomiting itself. The aim of this study was to determine the factors that influence the severity of nausea and vomiting in patients undergoing hemodialysis. This type of research is quantitative with analytic descriptive method, with an approach using a retrospective cohort research design. The sampling technique in this study was a total sampling technique with a total sample of 57 patients. The research instrument used questionnaires and observations, data analysis using the Chi Square test and simple logistic regression analysis. The location of the study was the hemodialysis therapy site at the Islamic Hospital in Purwokerto in January-February 2020. The results showed that most of the respondents with the severity of nausea and vomiting, the patient's diet was not balanced (61.4%), the excess fluid had edema (63.2%), the gender was male (59.6%), female (40.4%). %), age 18-65 (57.9%), duration of HD <12 months (64.9%) and 58 respondents> 12 months (35.1). The results of bivariate analysis using logistic regression, obtained p value of the patient's diet 0.009, excess fluid, age and sex 0.001 and the duration of HD 0.003. From this analysis, there are 5 factors that can cause the severity of nausea and vomiting, namely the patient's diet, excess fluidity, gender, age, and duration of HD.

scholarly journals A study on demographic factors affecting quality of life among HIV positive individuals attending a district anti retroviral treatment centre in Mangalore

2017 ◽  
Vol 5 (1) ◽  
pp. 215
Author(s):  
Anusha Rashmi ◽  
Rashmi Kundapur
Keyword(s):  
Quality Of Life ◽  
Demographic Factors ◽  
People Living With Hiv ◽  
Physical Domain ◽  
Chi Square ◽  
Social Domain ◽  
Factors Affecting ◽  
Class 1 ◽  
Domain Scores

Background: Prevention and treatment in HIV greatly influences the quality of life (QOL). The objective of the study was to assess QOL of individuals with HIV and its association with demographic factors. Methods: 400 patients with HIV attending the district anteretroviral treatment (ART) centre were interviewed with WHO QOL BREF questionnaire using systematic random sampling. Descriptive statistics, Chi square and independent t test and logistic regression was done to analyse the results. Results: Mean quality of life score was highest in the physical domain (Mean=14.93, ±3.59). Least score was seen for Social domain (Mean=12.30, ±2.37). The physical domain score was highest among those belonging to class 1 SES (Mean=17.50, ±0.707). Domain scores varied significantly (p>0.05) with respect to gender. There was significant variation in domain scores across the different socioeconomic groups except in social domain. Conclusions: Gender, Socioeconomic and marital status significantly affected the QOL of People Living with HIV. 

Demographic Trends of Child Labour in India: Implications for Policy Reforms

2018 ◽  
Vol 19 (5) ◽  
pp. 1345-1362
Author(s):  
Bishnu Mohan Dash ◽  
Lokender Prashad ◽  
Mili Dutta
Keyword(s):  
Logistic Regression ◽  
Census Data ◽  
Participation Rate ◽  
National Sample ◽  
Child Labour ◽  
Sample Survey ◽  
Policy Reforms ◽  
Chi Square ◽  
Factors Affecting ◽  
Chi Square Test

The article highlights the situation of child labour using the Census data of Government of India from 1971 to 2011. This study has also utilized the National Sample Survey Organization 68th round data on employment and unemployment of child labour in India. In this study, bivariate and multivariate analysis has been carried out. The chi-square test has been used to study the association between child labour and various socio-economic characteristics. The multiple logistic regression technique has been used to find out the factors affecting child labour. All the analysis has been carried out in SPSS and STATA software. The article has highlighted the growth rate of child labour and its distribution with socio- economic characteristics and work participation rate of child labour in India. Using the logistic regression, the study has projected the estimates of child labour in India. Besides that, the article recommended various suggestions for the abolition and regulation of the incidences of child labour in India.

scholarly journals Prediction model of algal blooms using logistic regression and confusion matrix

2021 ◽  
Vol 11 (3) ◽  
pp. 2407
Author(s):  
Hongwon Yun
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Prediction Model ◽  
Logistic Regression Analysis ◽  
Algal Blooms ◽  
Statistical Tests ◽  
Confusion Matrix ◽  
Factors Affecting ◽  
Predicted Values ◽  
Marine Environmental

Algal blooms data are collected and refined as experimental data for algal blooms prediction. Refined algal blooms dataset is analyzed by logistic regression analysis, and statistical tests and regularization are performed to find the marine environmental factors affecting algal blooms. The predicted value of algal bloom is obtained through logistic regression analysis using marine environment factors affecting algal blooms. The actual values and the predicted values of algal blooms dataset are applied to the confusion matrix. By improving the decision boundary of the existing logistic regression, and accuracy, sensitivity and precision for algal blooms prediction are improved. In this paper, the algal blooms prediction model is established by the ensemble method using logistic regression and confusion matrix. Algal blooms prediction is improved, and this is verified through big data analysis.

scholarly journals FAKTOR YANG MEMPENGARUHI KEPATUHAN PENGOBATAN PENDERITA HIPERTENSI USIA PRODUKTIF DI DESA KARANGSONO KECAMATAN BARAT KABUPATEN MAGETAN

2021 ◽  
Vol 6 (2) ◽  
pp. 92
Author(s):  
Dara Aprilia Aurilita Mawanti ◽  
Avicena Sakufa Marsanti ◽  
Hanifah Ardiani
Keyword(s):  
Logistic Regression ◽  
Health Center ◽  
Medication Compliance ◽  
Simple Random Sampling ◽  
Chi Square ◽  
Factors Affecting ◽  
The Public ◽  
Regression Test ◽  
Working Status ◽  
Logistic Regression Test

In 2018, Karangsono Village is village with the highest number of medication incompliance by hypertension patients at productive age reaching 70,7% compared to other 8 villages in Tebon Health Center working area. This research for to analyze factors affecting the medication compliance of hypertension patients at productive age and factor which affects the medication compliance the most. This research was done through case control design with the research samples included 58 chosen using simple random sampling. The data was then analyzed using chi-square statistical test and logistic regression statistic.Results : Through the analysis using logistic regression test, it shows that the factors affecting the medication compliance by the hypertension patients at productive age in Karangsono Village, Barat Sub-District were working status (p=0.000), family support (p=0.001), and the length of time of the hypertension suffering (p=0.016).Conclusion : Among those factors, working status is the factor which affects the medication compliance the most (p=0.000; Exp(B)=9.9; 95%CI=2.379-36.505). The hypertension medication compliance therapy needs to be improved by providing drug hypertension card independently, while for the patients who can visit the public health center, they were suggested to join the posbindu.

scholarly journals Evaluation of Factors Affecting the Expression of Anti-HBs in Children in Hunan Province

2021 ◽  
Author(s):  
Shan Tan ◽  
Shizhou Li ◽  
Jianxiang Dong ◽  
Hongmei Dai ◽  
Minghua Yang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Hepatitis B ◽  
Zinc Deficiency ◽  
Multivariate Logistic Regression Analysis ◽  
T Test ◽  
Hunan Province ◽  
Likelihood Method ◽  
Chi Square ◽  
Factors Affecting ◽  
Chi Square Test

Abstract Background and objectives Vaccine is the most essential avenue to prevent hepatitis B infection in infants and preschool children in China, with the largest populations carrying hepatitis B virus in the world. This study aimed to evaluate the factors affecting the response level of anti-HBs in children, with a view to provide instructions for hepatitis B prevention clinically. MethodsThe children taking physical examinations in the Third Xiangya Hospital from January 2013 to April 2020 were recruited. Telephone follow-up were adopted to collect further information. Univariate logistic regression was used to analyse the relationship between age and anti-HBs expression. After grouping by age and anti-HBs expression, we used chi-square test and T test to compare the difference between positive and negative antibody expression in each age subgroup. The meaningful variables (P<0.10) in chi-square test and T test were assessed with collinearity and chosen for univariate and multivariate logistic regression analysis by the stepwise backward maximum likelihood method (αin=0.05, αout=0.10).ResultsA total of 5838 samples (3362 males, 57.6%) were enrolled. The outcomes showed that the expression of anti-HBs was associated with age [OR=1.037(1.022-1.051)] in whole sample. Anemia[OR=0.392(0.185-0.835)], age[OR=2.542(1.961-3.295)] and Vit D[OR=0.977(0.969-0.984)] in 0.5-2.99 years subgroup, Zinc deficiency[OR=0.713(0.551-0.923] and age[OR=1.151(1.028-1.289)] in 3-5.99 years subgroup, Vit D[OR=0.983(0.971-0.995)] in 12-18 years subgroup had significant effect on the expression of anti-HBs. Conclusions This retrospective study illustrated that age, anaemia status, zinc deficiency and vitamin D were associated with the expression of anti-HBs in different age groups children, which could serve as a reference for the prevention of hepatitis.

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