PREDIKSI KEBERHASILAN TELEMARKETING BANK UNTUK MENCARI ALGORITMA DENGAN PERFORMA TERBAIK
Abstract: To search algorithm
has the best performance in predicting the success of telemarketing in a
banking course researchers have conducted various test materials several
algorithms to the data in proleh of uci data sets, and have as many as 17
attributes, some algorithms that had previously been in ujikan in research
this. to look for the best performance algorithm uses an algorithm writers
among others, is to use an algorithm based on particle swarm optimization to
optimize some attribute values and to improve the accuracy of the algorithms
and higher data classification, and can produce higher accuracy value again.
From the algorithm neural network (NN) based PSO get the result 91.80%, Support
Vector Machine (SVM) to get the accuracy of 90.20%. Naive Bayes (NB) with
89.41% accuracy results, and to use it algorithms Decision Tree (DT) with hasi
accuracy of 90.93%. Then obviously Neural Network-based PSO algorithm generates
higher accuracy of some algorithms in ujikan with 91.80% accuracy results.
Those results went into the classification is very good (excellent
classification).
Keyword: Neural Network,
Particle Swarm Optimization, Suport vector Machine, Naive Bayes, Decision Tree
Penulis: Elin Panca Saputra
Kode Jurnal: jptkomputerdd170257
