AN IMPROVEMENT OF SIMILARITY IN CASE BASED REASONING USING SUBJECTIVE-GENERALIZED WEIGHT FOR TRADITIONAL INDONESIAN CUISINE | [Journal of Theoretical and Applied Information Technology • 2020]

Author(s):

1. SETYAWAN WIBISONO: Faculty of Information Technology, Universitas Stikubank, Semarang, Indonesia

2. WIWIEN HADIKURNIAWATI: Faculty of Information Technology, Universitas Stikubank, Semarang, Indonesia

3. HERNY FEBRUARIYANTI: Faculty of Information Technology, Universitas Stikubank, Semarang, Indonesia

4. MARDI SISWO UTOMO: Faculty of Information Technology, Universitas Stikubank, Semarang, Indonesia

Abstract:

In this study, a system for providing recommendations from a traditional Indonesian food recipe consultation using the CBR (Case Based Reasoning) method was designed. A recommendation is given based on the similarity of the input in the form of ingredients for cooking compared to the ingredients for cooking from a recipe that has been stored in the database. Increasing the accuracy of the similarity value is the goal to be achieved in this study. This method used is intented to give the weight to each food-forming material, then the Dice algorithm is used to calculate the value of similarity. Weighting is determined subjectively but takes into account the principle of appropriateness in general. Test the validity of the weight value using the weighting principles in the AHP (Analytical Hierarchy Process). This makes the value of the similarity of a recipe suggestion more accurate because it considers proportional weighting of the ingredients forming the recipe.

Page(s): 864-875

DOI: DOI not available

Published: Journal: Journal of Theoretical and Applied Information Technology, Volume: 98, Issue: 5, Year: 2020

Keywords:

AHP , CBR , Dice algorithm , weighting , consultation similarity value

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