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All Journal IJISTECH (International Journal Of Information System & Technology) IJISTECH
Rahmadenti, Nadhia Ayu
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

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Journal : IJISTECH (International Journal Of Information System

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Classification of Domestic Flight Passengers at Main Airports Using the K-Means Clustering Method Syaoqiyah, Syifa Siti; Anisa, A; Selvina, Yudhi Yulianti Selvina; Rahmadenti, Nadhia Ayu; Aria, Ririn Restu
IJISTECH (International Journal of Information System and Technology) Vol 8, No 1 (2024): The June edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i1.340

Abstract

The aviation business in Indonesia has recently experienced quite significant growth, which can be seen from the fact that many people tend to choose air transportation to travel and connect them to cities in Indonesia. With air transportation, the time spent traveling to one area or city can be reduced. accomplished in a short time. This causes the number of passengers per flight to be quite high, especially in domestic flights which occur at the main airport. This research will use the K-Means Clustering algorithm to find out the schedule for the busiest month for the highest domestic airlines at major airports. The data source for this research comes from the central statistics agency regarding the number of domestic airline passengers at major airports. The criteria used in this research are divided into 3 clusters, namely high, medium, and low. The results of this research show that the highest number of passengers (C1) occurs in January to April, while the moderate number of passengers (C2) occurs in May to December, and the lowest number of passengers (C3) occurs in August to November.
Co-Authors A Anisa Ririn Restu Aria Selvina, Yudhi Yulianti Selvina Syaoqiyah, Syifa Siti