New Model of ARWCM Based on SDLC With Herman's Theorem Using Decision Tree Algorithm by Weka
Ambarka Ali Elghali · 2021 IEEE 1st International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering MI-STA · 2021
In this paper, a new model is developed which is called the adaptive work theoretical model through the stages of building information systems and The New Haberman brain lobe method of remote adaptive work system classification using the dialogic decision support (ARWCM) model. Identifying intangible human behavior such as preference or motor aspect is very difficult because of the many factors characteristic in a person's personality, through the answers to a questionnaire that combines the stages of building and developing information systems and Herman's theory thus determining the mode of work of individuals especially for remote work and finding the right work approach consistent with Dealing with different individuals remotely with different thinking patterns and disciplines remains the critical issue for most research. This research introduced the ARWCM model that accommodates individuals in a comfortable remote work environment improving the remote work system by placing it in the adaptive remote work model. Decision support tree algorithm technology it has been used to classify and predict the remote working method of individuals based on the stages of building and developing various information systems with Herman's theory and advanced system structure.