Penentuan Pemenang Tender Menggunakan Kombinasi K-Neareast Neighbor dan Cosine Similarity (Studi Kasus PT. Unichem Candi Indonesia) - Surya Dermawan; Edy Santoso; Lailil Muflikhah (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2018)
In decision of determination of auction in PT. Unichem Candi Indonesia is still manual. Due to this lack of knowledge in decision making. Data mining is also referred to as a series of processes to explore the added value of knowledge that has so far not been known manually from a data set. One of the technology that can be used for information system of tender winner determination is K-NN and cosine similarity which this technology become efficient and effective when applied to problem in PT. Unichem Candi Indonesia. The K-NN algorithm is a method that uses a supervised algorithm, where. The K value is the amount of nearest training data to the test data. From the test results the effect of the value of k obtained accuracy of 73% where the highest value, ie k = 2. Testing with the amount of trainee data and test data are balanced will affect the amount of accuracy that will be obtained. Based on the test results with the amount of training data and test data obtained an accuracy value of 83% where the highest value, ie k = 4. Keywords: Data Mining , k-nn Algorithm, Cosine Similarity.