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The 3 International Conference
rd
on Vocational Education and Technology (IConVET)
th
Universitas Pendidikan Ganesha - Bali | 7 November, 2020
COMPARATIVE ANALYSIS OF NAÏVE BAYES AND
KNN ON PREDICTION OF FOREX PRICE
MOVEMENTS FOR GBP/USD CURRENCY AT TIME
FRAME DAILY

K S Y Pande , D G H Divayana , G Indrawan 1,c
1,b
1,a

1 Computer Science, Magister Program, Ganesha University of Education,
Bali, Indonesia - 81116

a
E-mail: sudana.yasa.pande@gmail.com,
b hendra.divayana@undiksha.ac.id, gindrawan@undiksha.ac.id,
c

Abstract. This study aims to analyze the comparison of the Naïve Bayes and
kNN on the Prediction of Forex Price Movements for GBP / USD on Time
Frame Daily. The data used is taken from the metatrader-4 application which
is often used by forex traders when making transactions. There are 2,145
data rows consisting of the date, hour, open price, high, low, close, and
transaction volume columns. From this data, a column for the target class is
created with the name 'result'. The result column is filled with increasing or
decreasing values. The value of increase or decrease is obtained from the
comparison of the previous closing price with the closing price of the next
day. This study analyzes the results of the comparison of the data mining
classification algorithm between the Naïve Bayes algorithm and kNN. The
2,145 data were divided into 2 parts, namely 80% for training data and 20%
for testing data. The analysis is done by comparing the precision, recall, and
accuracy test results for each algorithm. The conclusion of this study is that
the kNN algorithm is better than the Naïve Bayes algorithm in case
prediction of forex price movements for GBP/USD currency at time frame
daily.

| IConVET 2020 | 41

https://conference.undiksha.ac.id/iconvet/ | 41 |