Classification of Super Air Jet Initial Cabin Crew Candidates Using K-Nearest Neighbor (KNN) Method

Klasifikasi Calon Awak Kabin Awal Super Air Jet Menggunakan Metode K-Nearest Neighbor (KNN)

Authors

  • Ahmad Jurnaidi Wahidin Universitas Bina Sarana Informatika
  • Reza Maulana Sekolah Tinggi Teknologi Terpadu Nurul Fikri

DOI:

https://doi.org/10.35706/sys.v3i2.5804

Abstract

At the time of the corona virus outbreak that hit Indonesia and the world which had an impact on various sectors including transportation, optimistically that the Indonesian domestic flight market was still open with strong demand, a new airline, Super Air Jet (SAJ) was created in March 2021. In an effort to improve SAJ services screening qualified human resources, including the process of screening candidates for initial cabin crew. To support this process, it is necessary to have a method used to classify candidates for initial cabin crew at the administrative stage. K-Nearest Neighbor (KNN) which is one method for classifying is expected to provide a solution to the problems discussed. This study uses 10 training data that have 8 criteria to predict categories in 6 test data. From the calculation results using a value of k=5, the same results as the label on the initial test data resulted, which resulted in 2 data with the Stop prediction class and 4 data with the Advanced prediction class. To measure the performance of the KNN method, a test was conducted using a confusion matrix which resulted in a 100% accuracy value, a 100% precision value and a 100% recall value.

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Published

2021-08-01

How to Cite

[1]
Ahmad Jurnaidi Wahidin and Reza Maulana, “Classification of Super Air Jet Initial Cabin Crew Candidates Using K-Nearest Neighbor (KNN) Method: Klasifikasi Calon Awak Kabin Awal Super Air Jet Menggunakan Metode K-Nearest Neighbor (KNN)”, Systematics Journal, vol. 3, no. 2, pp. 249–262, Aug. 2021.

Issue

Vol. 3 No. 2 (2021): August 2021

Section

Articles

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Copyright (c) 2021 SYSTEMATICS

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