Most people's dream is to have white, healthy, clean and well-maintained facial skin. However, the treatment does not pay attention to skin type, causing new problems such as acne, dry skin and others. Before carrying out skin care, determining the type of facial skin is very necessary because the determination of skin care must be adjusted to the type of facial skin. The role of a skin specialist is highly expected in determining the type of facial skin care according to skin type. The limited number of dermatologists , doctor's office hours , and the very long queue process and long travel distances result in obstacles that are often experienced. In order to make it easier for the public to recognize skin problems on the face, we need a system that can assist doctors in the initial diagnosis of facial skin problems. In this study, the forward chaining method and certainty factor were used in diagnosing facial skin problems to calculate the accuracy of the types of problems experienced based on the symptoms felt by the user. From the test results obtained in dealing with facial skin problems with an accuracy rate of 99.99 % . The resulting expert system can assist patients in consulting to deal with facial skin problems
Lecturers are academic staff who are in charge of planning and implementing the learning process, guidance and training, and are able to bring students into activities held by the University, both official and non-official. Selection of favorite lecturers chosen by students can encourage lecturers to communicate more with students to be able to invite students to take part in groups or organizations involving students and lecturers. However, in reality, Universitas Putra Indonesia YPTK Padang is still not actively conducting this election. To overcome these problems, a Decision Support System was designed to determine the student's favorite lecturers by using the simple additive weighting method. The Decision Support System for Determining Favorite Lecturers of Student Choice is a system that is able to increase the ease of decision making in determining lecturers who have student attractiveness so that students are more active and more competent in the guidance of the selected lecturers. In this system the lecturer's assessment is based on 5 criteria. The criteria used are responsibility, discipline, attitude, initiative, and presence. To get the final conclusion as an alternative decision to determine the lecturer of this choice requires the calculation process stage on each variable that has been determined based on the criteria. The position of the decision support system in this study is as a decision supporter, not replacing the role of the decision maker, so that the decision maker has the right to fully refer to the decision support system or not. The research results from the calculated simple additive weighting method can be concluded that the favorite lecturer of the student's choice is lecturer 2 with a score of 1.00 which is the result of the highest ranking and can be used as an alternative for determining the favorite lecturer of the student's choice.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.