Open AccessImproving measureable external factors influence on construction project duration estimation
Author(s) -
Basuki Adho,
Yusuf Latief,
Krishna Mochtar
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/650/1/012020
Subject(s) - multivariate statistics , regression analysis , index (typography) , statistics , variables , duration (music) , regression , econometrics , variable (mathematics) , external variable , logistic regression , goodness of fit , mathematics , structural equation modeling , multivariate analysis , computer science , art , literature , mathematical analysis , world wide web , programming language
The purpose of this study was to determine whether the use of building function variables as dummy variables affected the duration of construction projects, together with identified measureable external factors. Multivariate regression is a technique that estimates a single regression model with more than one outcome variable. When there is more than one predictor variable in a multivariate regression model, the model is a multivariate multiple regression. Goodness of Fit (R 2 ) of the equation regression analysist used as sensibility benchmarks. Variables are transformed to index number for unit synchronize. If the result is unsatisfied for predicting a project duration, an implementation of dummy variables could be tried if there any improvement of R 2 . The trial on this research, 43 data show that in first stage, five influence factors: Education Index, Technology Absorption Index, Labor Experience Index, New Technology Availability Index, and Innovation Index generate regression equation without full fill the mathematical requirement. At the second stage, by adding dummy variables based on type of building, apartment, office, hotel and other then the three type together with the five external factors, afford a good R 2 .