PROFIT PREDICTION USING MULTIPLE LINEAR REGRESSION METHODS PYTHON PROGRAMMING LANGUAGE AT PT TRI ERDNOV REZEKI - Tri Pamungkas, Ferdy; Isfenti Sadalia; Iskandar Muda (International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS), 2023)
PT. Tri Erdnov Rezeki is a national private company founded in 2016 and fully under the leadership and ownership of Indonesian entrepreneurs. PT. Tri Erdnov Rezeki is also engaged in Construction Development Planning and Repair and Maintenance of Steam Aircraft and Pressure Vessels, Supply of Technical Equipment, Industrial Work Equipment, Electrical Equipment, and Machinery, especially in the Palm Oil Plantation and Power Plant Sectors. In carrying out a project, the company does not only carry out technical design but also must carry out the economic design so that the company can determine the economic feasibility of a project. However, companies often experience cost calculation errors. Data science can be utilized to predict the value achieved in a period using previous data. Data science will analyze patterns related to data with other data to produce a reference or a formula that can be used as a value prediction in the future. So, the author will use the multiple linear regression method using the Python programming language, which functions to perform statistical analysis, namely predicting profits in a project. The analysis results in this study show that the profit variable is influenced by 99.7% by the variables material cost, labor cost, and utility cost. In comparison, other variables outside the study influence the other 0.3%. The material cost variable has the most significant influence, where the value is below 0 .05 compared to the variable labor cost and utility cost to the profit variable. The average percentage of Python prediction errors is 0.97%, where the average percentage of Python prediction errors is smaller than the average percentage of SPSS prediction errors which is 2.04%.