Sensitivity Comparison of AHP with The Combination of AHP and SAW for Facial Wash Recommendation System based on Skin Type

Novrido Charibaldi, Qurrotu'ain Hanifah, Rifki Indra Perwira

Abstract


Purpose: This research aims to design a facial wash recommendation system based on all skin types, namely normal, dry, oily, combination, and sensitive. This is to tackle the limitation of previous systems that were developed based on limited skin types which are normal, dry, and oily using Promethee II, Fuzzy Logic, and SAW methods.

Design/methodology/approach: This research uses the Analytic Hierarchy Process (AHP) method and a combination of AHP and Simple Additive Weighting (SAW) to consider the importance values of each criterion. Four criteria data are used, namely price, rating, content, and availability, along with 70 alternative data of facial wash products.

Finding/Result: Sensitivity testing was conducted on both methods, and the combination of AHP and SAW produced a higher sensitivity percentage, which is 67.51%, whereas the AHP method provided a lower sensitivity percentage of 59.26%.

Originality/state of the art: The combination of AHP and SAW is an innovation in designing a facial wash recommendation system, and the research results demonstrate that the combination of AHP and SAW is a superior method for recommending facial wash products.


Keywords


Decision Support System; Analytical Hierarchy Process; Simple Additive Weighting; sensitivity comparison; facial wash recommendation

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DOI: https://doi.org/10.31315/telematika.v20i2.9444

DOI (PDF): https://doi.org/10.31315/telematika.v20i2.9444.g5709

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