Skin care routine decision support system using fuzzy logic

• Main Author: Siti Nur Syahirah, Zulkifli
• Format: Undergraduates Project Papers
• Language: English
• Published: 2019
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/26959/1/Skin%20care%20routine%20decision%20support%20system%20using%20fuzzy.pdf; http://umpir.ump.edu.my/id/eprint/26959/; http://fypro.ump.edu.my/ethesis/index.php

This research about Skin Care Routine Decision Support System using Fuzzy Logic which is skin care nowadays is important issues to everyone not only for women but men also. However, although this issue important but still many people not concerns about it and doesn't know whether the skin care products used, match with their skin type or not. As for solution, skin care routine decision support system using fuzzy logic is a system that able to determine the skin symptom of four skin types such as normal skin, oily skin, combination skin and dry skin. This system will diagnosis skin type by using a set of score rules that will be entered by the user based on age, gender, sleep time and skin condition, then the user input, will be processed to determine skin type based on maximum rate. The previous system, the Skin Care Routine Support System (SCRSS), where the system that detects the skin in the range of skin condition is not exactly accurate in the standard range and also some of the core features of the feature that indicate skin type is not included, it is difficult for users who have various types of skin symptoms that are not included in the system. This research has developed to aims to overcome this problem by using fuzzy logic in the Skin Care Routine Decision Support System (SCRDSS). As a result, a system has been developed to solve the user's problem in determining skin care routines. The Skin Care Routine Decision Support System (SCRDSS) used fuzzy logic method using a decision support framework. Test results, obtained from public respondents to determine their skin symptoms based on respondents' inputs in the Skin Care Routine Decision Support System (SCRDSS). User knowledge testing has been carried out on this improved SCRDSS. The test was conducted on 15 respondents where only 80% respondents responded. The test results show the increased rate of skin-related consumer knowledge and skin care routine that is 20% compared to user knowledge before using this system. This suggests that the proposed system benefits public users in keeping their skin. However, the assessment of the resulting rules cannot be evaluated given the time constraints to referring to a beauty expert.