Waiting time prediction system using linear regression method

Ibrahim, Syamsul Ikhmal (2022) Waiting time prediction system using linear regression method. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Malaysia now has a wide range of dental facilities. In reality, the number of patients does not decrease because treatment in government clinics is still far less cost than treatment in private clinics. This project is about developing a management queue system that will solve current problems that dental clinics are experiencing, especially government clinics. In this study, prediction systems using 2 machine learning techniques, Linear Regression and Random Forest were developed and analysed to overcome this difficult scenario. This model was developed in Python using Jupyter Notebook. To examine the performance of this machine learning technique, the regression metrics Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were used. A previously selected dataset from dental clinics was used to predict the duration of queueing in real life for this method. As a result, the RMSE and MAE values were shown in a table result, and Linear Regression has lower RMSE and MAE values than Random Forest, indicating a good machine learning performance model. The dataset's waiting time is displayed in minutes by developing a graphical user interface (GUI).

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