Using classification data mining methods to predict the level of efficiency of services in dental clinics during the COVID-19 pandemic
Keywords:
Database, Relational Database, SQL, ODBC, Multivariable Analyses, CHIAID algorithm, Logistic Regression algorithm, Two-Step Clustering algorithm, Dental ClinicsAbstract
The Covid-19 pandemic has always affected all life facilities, dental clinics, like other institutions. research goal is to reach the patient's evaluation of the competency of the service offered to him in the clinic during the pandemic.
Three classification- data mining algorithms -decision tree, logistic regression and cluster analysis- were used to rank clinic reviewer opinions.
Using the programming languages (HTML, PHP, My-SQL) an electronic system has been created that provides services and facilitates the procedures for organizing reservations and making appointments.....Etc., according to the necessary, safety instructions during the pandemic. The System Development Lifecycle (SDLS) methodology is used to determine the level of service efficiency, and ODBC is used to send data from the database to SPSS-V26.
The study variables, like the possibility of returning to the clinic, which has the greatest potential to classify observations and is contributing the most to differentiating for each of the two clusters, have a statistically significant relationship with the likelihood that you will recommend this clinic to others, A list of findings were included in the research's conclusion..
