Open AccessPrediksi Tingkat Kepenuhan Penumpang Pesawat dari Bandara Hang Nadim Batam
Author(s) -
You Ari Faeni,
Nyanwar Eko Pribadi,
Jackson Bobby Romano Daba
Publication year - 2019
Publication title -
jurnal sistem cerdas
Language(s) - English
Resource type - Journals
ISSN - 2622-8254
DOI - 10.37396/jsc.v2i2.28
Subject(s) - computer science , support vector machine , decision tree , data mining , artificial intelligence
Batam is a very strategic area located in the Indonesia Malaysia Singapore Growth Triangle region. Transportation is an important factor in the economic growth of Batam City, especially air transportation. Various types of data are collected, but only a few are analyzed so that they can generate new knowledge. This research will analyze flight data from Hang Nadim Batam airport to predict the fullness of aircraft from Batam to various destinations. The results showed that the support vector machine (SVM) model showed a higher level of accuracy than decision tree in predicting the fullness of the aircraft