SPATIAL REGRESSION USING MULTIVARIATE CONDITIONAL AUTOREGRESSIVE (MCAR) CASE STUDY: EMPLOYEE’S HEALTH DATA OF A COMPANY

Health is a matter of concern. It is important to care for good health to preserve the body’s mass index as well as its level of triglycerides. Body Mass Index (BMI) is the measure to identify a person’s nutritional status as gaining weight and height. BMI is the simplest way to know if people are a...

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主要作者: Liana Putri Utami, Mei
格式: Final Project
語言:Indonesia
在線閱讀:https://digilib.itb.ac.id/gdl/view/47783
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機構: Institut Teknologi Bandung
語言: Indonesia
id id-itb.:47783
spelling id-itb.:477832020-06-21T09:32:28ZSPATIAL REGRESSION USING MULTIVARIATE CONDITIONAL AUTOREGRESSIVE (MCAR) CASE STUDY: EMPLOYEE’S HEALTH DATA OF A COMPANY Liana Putri Utami, Mei Indonesia Final Project Health Data, Spatial Regression, Multivariate Conditional Autoregressive (MCAR), Markov Chain Monte Carlo (MCMC) INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/47783 Health is a matter of concern. It is important to care for good health to preserve the body’s mass index as well as its level of triglycerides. Body Mass Index (BMI) is the measure to identify a person’s nutritional status as gaining weight and height. BMI is the simplest way to know if people are at risk of having a chronic illness. Triglycerides is one type of fat found in the blood. High levels of triglycerides are an indication of a person’s ailment, such as diabetes. Using the employee data of the company, it will see the effect of the free variable of height, weight, total cholesterol content in the blood, fat in blood, fast glucose level, tenure, and age band on bonded variables of BMI and triglycerides. To see that influence, it is used spatial regression using Multivariate Conditional Auto-Regressive (MCAR) by considering the spatial factor of the company’s employee district/city. Regression coefficients are estimated using a sample retrieval method, Markov Chain Monte Carlo (MCMC). At this final task, there were 100000 samples taken. From the samples, it was found that the weight and height variables had a significant impact on the BMI variable, with a DIC value of -253,8881. For triglycerides variable, total cholesterol and glucose fasting in the blood are variables that give a significant effect. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Health is a matter of concern. It is important to care for good health to preserve the body’s mass index as well as its level of triglycerides. Body Mass Index (BMI) is the measure to identify a person’s nutritional status as gaining weight and height. BMI is the simplest way to know if people are at risk of having a chronic illness. Triglycerides is one type of fat found in the blood. High levels of triglycerides are an indication of a person’s ailment, such as diabetes. Using the employee data of the company, it will see the effect of the free variable of height, weight, total cholesterol content in the blood, fat in blood, fast glucose level, tenure, and age band on bonded variables of BMI and triglycerides. To see that influence, it is used spatial regression using Multivariate Conditional Auto-Regressive (MCAR) by considering the spatial factor of the company’s employee district/city. Regression coefficients are estimated using a sample retrieval method, Markov Chain Monte Carlo (MCMC). At this final task, there were 100000 samples taken. From the samples, it was found that the weight and height variables had a significant impact on the BMI variable, with a DIC value of -253,8881. For triglycerides variable, total cholesterol and glucose fasting in the blood are variables that give a significant effect.
format Final Project
author Liana Putri Utami, Mei
spellingShingle Liana Putri Utami, Mei
SPATIAL REGRESSION USING MULTIVARIATE CONDITIONAL AUTOREGRESSIVE (MCAR) CASE STUDY: EMPLOYEE’S HEALTH DATA OF A COMPANY
author_facet Liana Putri Utami, Mei
author_sort Liana Putri Utami, Mei
title SPATIAL REGRESSION USING MULTIVARIATE CONDITIONAL AUTOREGRESSIVE (MCAR) CASE STUDY: EMPLOYEE’S HEALTH DATA OF A COMPANY
title_short SPATIAL REGRESSION USING MULTIVARIATE CONDITIONAL AUTOREGRESSIVE (MCAR) CASE STUDY: EMPLOYEE’S HEALTH DATA OF A COMPANY
title_full SPATIAL REGRESSION USING MULTIVARIATE CONDITIONAL AUTOREGRESSIVE (MCAR) CASE STUDY: EMPLOYEE’S HEALTH DATA OF A COMPANY
title_fullStr SPATIAL REGRESSION USING MULTIVARIATE CONDITIONAL AUTOREGRESSIVE (MCAR) CASE STUDY: EMPLOYEE’S HEALTH DATA OF A COMPANY
title_full_unstemmed SPATIAL REGRESSION USING MULTIVARIATE CONDITIONAL AUTOREGRESSIVE (MCAR) CASE STUDY: EMPLOYEE’S HEALTH DATA OF A COMPANY
title_sort spatial regression using multivariate conditional autoregressive (mcar) case study: employee’s health data of a company
url https://digilib.itb.ac.id/gdl/view/47783
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