Performance Comparison of AHP and Saw Methods For Selection of Doc Broiler Chicken Suppliers

Anik Vega Vitianingsih; Putu Gede Ari Krismantoro; Anastasia Lidya Maukar; Arizia Aulia Aziiza; Anindo Saka Fitri

doi:10.29407/intensif.v7i1.18634

Authors

Anik Vega Vitianingsih Universitas Dr.Soetomo Surabaya
Putu Gede Ari Krismantoro Universitas Dr. Soetomo Surabaya
Anastasia Lidya Maukar Universitas Presiden
Arizia Aulia Aziiza Universitas Surabaya
Anindo Saka Fitri UPN Veteran Jawa Timur

DOI:

https://doi.org/10.29407/intensif.v7i1.18634

Keywords:

DSS, AHP, SAW, Comparation Method, Performance Algorithm, Recommendation Alternatif

Abstract

Choosing the most suitable day-old chick (DOC) broiler chicken supplier is currently one of the most important issues that must be addressed. This is because selecting the most suitable supplier can reduce the amount spent on purchases and the risk of sick chickens being delivered by the supplier. Another problem related to supplier selection that has been happening so far is the quality of products that are not following company standards or rejected products. The number of products provided does not match what was ordered by the company. The decision support system (DSS) can evaluate and select suppliers using multi-criteria characteristics related to the solutions offered based on parameters quality, price, delivery, supplier certificates, and death claims after the chickens have been delivered. The Analytical Hierarchy Process (AHP) and the Simple Additive Weighting (SAW) methods are used in this study as a comparison to produce the best-recommended accuracy value to get the best decision results based on ranking. The test results state that the AHP and SAW methods go well. The test was carried out using a dataset of the last ten months of history of purchasing docs broiler chicken from suppliers. The comparison of the results of the F1-score value between the AHP and SAW methods is 94% and 87%, respectively. The results state that the AHP method is superior as a system recommendation that can produce the best alternative supplier.

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