Ordinal Logistic Regression Analysis with Dummy Variables on Factors Affecting Architectural Design Costs: Case Study at PT Nata Racasa Nusantara (Journal of Applied Statistics and Data Science, 2025)
The architecture industry is a sector that has an important role in the development of infrastructure, housing, and the built environment globally. Architectural companies’ efforts to increase profitability levels in the face of increasingly complex market demands is to understand the factors that significantly affect design costs. This research aims to determine the ordinal logistic regression model in identifying factors that have a significant effect on architectural design costs. This research uses secondary data covering 245 design projects completed by PT Nata Racasa Nusantara during the 2016-2023 period. The five independent variables studied include project type, design style, project location, client age, and recommendation source. One dependent variable that is the main focus is design costs, which consist of low, medium, and high levels. The ordinal logistic regression model that was formed succeeded in predicting with an accuracy of 70,204% and the predictor variables as a whole affected the response variable by 73,7%. The results of applying ordinal logistic regression analysis show that the factors that have a significant effect on architectural design costs, especially at PT Nata Racasa Nusantara are project location, client age, and source of recommendations.