Rule-Based system for skin type Self-Assessment (RBSA) / Norfida Abu Bakar
A good health is an integral part of a happy life and successful personality. A healthy skin is also associated with/ good health. To retain a healthy skin people need to know their skin type because the use of unsuitable skin care products can make skin worse. Detem1ining the skin type is usually d...
| Հիմնական հեղինակ: | |
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| Ձևաչափ: | Թեզիս |
| Լեզու: | English |
| Հրապարակվել է: |
2010
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| Խորագրեր: | |
| Առցանց հասանելիություն: | https://ir.uitm.edu.my/id/eprint/34343/1/34343.pdf |
| _version_ | 1825737928494546944 |
|---|---|
| author | Norfida, Abu Bakar |
| author_facet | Norfida, Abu Bakar |
| author_sort | Norfida, Abu Bakar |
| collection | UITM |
| description | A good health is an integral part of a happy life and successful personality. A healthy skin is also associated with/ good health. To retain a healthy skin people need to know their skin type because the use of unsuitable skin care products can make skin worse. Detem1ining the skin type is usually done by skin specialist. The title for this project is Rule-Based for Skin Type Self-Assessment (RBSA). The system is a web based system that can provide online self assessment through questionnaires. The objectives of the project are to develop a rule-based system to determine skin type where it can accept the input and produce the result for users and recommendation of skin care product based on skin type. This project uses rule based technique to get the suitable results. This system has 24 rules to evaluate the result. It can determine sixteen types of skin. The rules that have been created are based on the theories of Leslie Baumann who is a skin specialist. The system will display different questionnaires based on skins sequentially. User must input the data and system will process the data based on the rule. The results will show user's skin type and the appropriate skin care product based on user's skin type. This system prototype was tested with thirty sample data of respondent. From the analysis, this project accuracy is 93.3%. As the conclusion, the rules that have been created are accurate and this technique is suitable to be applied in skin type determination. |
| first_indexed | 2024-03-06T02:25:45Z |
| format | Thesis |
| id | oai:ir.uitm.edu.my:34343 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T02:25:45Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | oai:ir.uitm.edu.my:343432020-09-11T01:06:01Z https://ir.uitm.edu.my/id/eprint/34343/ Rule-Based system for skin type Self-Assessment (RBSA) / Norfida Abu Bakar Norfida, Abu Bakar Back propagation (Artificial intelligence) Information theory Mathematical statistics. Probabilities Philosophy. Theory. Classification. Methodology A good health is an integral part of a happy life and successful personality. A healthy skin is also associated with/ good health. To retain a healthy skin people need to know their skin type because the use of unsuitable skin care products can make skin worse. Detem1ining the skin type is usually done by skin specialist. The title for this project is Rule-Based for Skin Type Self-Assessment (RBSA). The system is a web based system that can provide online self assessment through questionnaires. The objectives of the project are to develop a rule-based system to determine skin type where it can accept the input and produce the result for users and recommendation of skin care product based on skin type. This project uses rule based technique to get the suitable results. This system has 24 rules to evaluate the result. It can determine sixteen types of skin. The rules that have been created are based on the theories of Leslie Baumann who is a skin specialist. The system will display different questionnaires based on skins sequentially. User must input the data and system will process the data based on the rule. The results will show user's skin type and the appropriate skin care product based on user's skin type. This system prototype was tested with thirty sample data of respondent. From the analysis, this project accuracy is 93.3%. As the conclusion, the rules that have been created are accurate and this technique is suitable to be applied in skin type determination. 2010-11-02 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/34343/1/34343.pdf Rule-Based system for skin type Self-Assessment (RBSA) / Norfida Abu Bakar. (2010) Degree thesis, thesis, Universiti Teknologi MARA Cawangan Perak. <http://terminalib.uitm.edu.my/34343.pdf> |
| spellingShingle | Back propagation (Artificial intelligence) Information theory Mathematical statistics. Probabilities Philosophy. Theory. Classification. Methodology Norfida, Abu Bakar Rule-Based system for skin type Self-Assessment (RBSA) / Norfida Abu Bakar |
| title | Rule-Based system for skin type Self-Assessment
(RBSA) / Norfida Abu Bakar |
| title_full | Rule-Based system for skin type Self-Assessment
(RBSA) / Norfida Abu Bakar |
| title_fullStr | Rule-Based system for skin type Self-Assessment
(RBSA) / Norfida Abu Bakar |
| title_full_unstemmed | Rule-Based system for skin type Self-Assessment
(RBSA) / Norfida Abu Bakar |
| title_short | Rule-Based system for skin type Self-Assessment
(RBSA) / Norfida Abu Bakar |
| title_sort | rule based system for skin type self assessment rbsa norfida abu bakar |
| topic | Back propagation (Artificial intelligence) Information theory Mathematical statistics. Probabilities Philosophy. Theory. Classification. Methodology |
| url | https://ir.uitm.edu.my/id/eprint/34343/1/34343.pdf |
| work_keys_str_mv | AT norfidaabubakar rulebasedsystemforskintypeselfassessmentrbsanorfidaabubakar |