MODELING MATERIALS PRICE FOR BUILDING MATERIAL IN PALANGKA RAYA - Yulin Patrisia; Revianti Coenraad (Jurusan Pendidikan Teknologi dan Kejuruan, FKIP, Universitas Palangkaraya, 2016)
One of the components that play a vital role to the success of a construction project is construction prices, namely material prices, leasing and purchasing equipment prices, and construction wages. In the planning stage, the price used is the approximate price that will valid at the time of the project activities. At the implementing stage, the price used is the result of detailed estimates approaching real conditions at the time of the project activities. At the stage of monitoring and evaluation, the price will be reviewed to the conformity of the realization in the field, both the quantity and quality, further compared with employment contract. Research on the affecting factors of price construction materials is important. Furthermore, the affecting factors will be analyse to get a model approach for relevant price of construction materials. The construction material object in this research was timber. The study was conducted to obtain primary data and secondary data. Secondary data was performed to establish the factors that are predicted to affect the price of wood materials. Primary data were collected by distributing a questionnaire to 15 contractors in the city of Palangka Raya. Data obtained from the questionnaire and then analyzed by Severity Index (SI) for establishing the factors that affect the price of wood materal. Furthermore, the data were analyzed by the PLS model to obtain a model of approach to wood material prices. The study states there are several factors that affect the price of wood materials, namely economic factors, location factors, material resources factors, transport factors, and regulatory and government policies factors. Model approach to set the price of wood material by using PLS analysis showed that the material resources has an effect on the price of wood material, while the most dominant variable is the location factor.