REKOMENDASI BARANG BERBASIS KASUS MEMANFAATKAN MULTI LEVEL ASSOCIATION RULES MINING (Studi Kasus : Omus Store); CASE BASED ITEMS RECOMMENDATION UTILIZING MULTI LEVEL ASSOCIATION RULES MINING (Case Study : Omus Store)

Tyas, Zahra A, Sri Hartati

2015 | Disertasi | FMIPA UGM

Recommendation system can produce a recommendation on a variety of ways and using various methods, one of which is utilizing piles of old cases or piles of old transaction data can produce information or rules with Multi Level Association Rules Mining (ML-ARM) method. But not all the rules generated can produce a recommendation because the rules do not match, to overcome this deficiency, this research will be a combination of methods ML-ARM and Case Based Reasoning (CBR). Rules established by the method of ML- ARM produces 5 rules that will be matched to user input. When the rule is found to match the consequent of the rule will be used as a result of the recommendation, but if consequent obtained still generate much product for recommendation so required similarity calculation with the help of CBR nearest neighbor method. The highest similarity used as a result of the recommendation, then when no matching rule is found then the process will perform the calculations on the similarity of all the goods with nearest neighbor method by indexing the design features. The test results of rules that created has a value accuracy of 94,12% and value of precision and F-measure for this recommendations system on rules recommendation process is higher value than case recommendation process. Instead recall value to the process through case higher than the processes through rules.

Kata Kunci : recommendation system; case based reasoning; multi level association rules mining; nearest neighbor; cross validation.