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Putri Previa Yanti
Institut Teknologi Bandung
Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering

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Klustering Jumlah Penumpang pada Halte Bus Rapid Transit Kota Tangerang Erni Dianawati; Putri Previa Yanti; Yulia Suryandari
Jurnal Sistem Cerdas Vol. 2 No. 3 (2019): Transformasi dan Inovasi Kota Cerdas
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (901.563 KB) | DOI: 10.37396/jsc.v2i3.34

Abstract

Bus Rapid Transit (BRT) Trans Tangerang is a local public transportation system developed in the main corridor of the Tangerang City area as well as a feeder for Transjabodetabek and rail transport. BRT Trans Tangerang is one part of the Bus Rapid Transit program which is implemented and launched by Department of Transportation. The BRT Trans Tangerang system began operating at the beginning of December 2016. Some problems faced by Trans Tangerang Bus Rapid Transit such as the number of passengers that need to be increased to reduce congestion in the city of Tangerang and the placement of the right bus stops to attract passengers. Therefore, to overcome this problem, data and information about BRT Trans Tangerang are needed to find patterns of passenger distribution. The process of finding this information can be done by using data mining method. Within this method, there is a clustering technique which is useful to clustering all data in groups which have similar data. The algorithm used to classify the data is called simple k-means algorithm. In this study, all the data will be clustered into five cluster. The clustering results have almost the same nature between the data in one cluster, namely the total number of passengers per month, so that by performing clustering characteristics, knowledge of the busy schedule of passengers in one day can help related parties to anticipate the density of passengers on certain days.
A Survey : Application of Big Data in the Travel and Tourism Industry Putri Previa Yanti
ITEJ (Information Technology Engineering Journals) Vol. 5 No. 1 (2020): June
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v5i1.38

Abstract

The development of information technology has increased the travel and tourism industry. The travel and tourism data are available in many sources such as telephone, social media, sensor system on the internet of things, and others. The application of big data has great potential in the development of the travel and tourism industry. Big data can take advantage of new things in making the right decisions and seeing opportunities in doing better business. This paper provides a survey that discusses big data in the travel and tourism industry. Big data is used to ticket price and demand prediction. In addition, big data is also used to build a tourism plans and recommender system with the personalized and adaptive method. Combination of using the internet of things and big data can help the industry to price their product. The result of this study is some of the implementation of big data in the travel and tourism industry. We conclude that big data can be used to explore new things in making the right decisions, seeing opportunities more observant, and doing business more efficiently
Co-Authors Erni Dianawati Yulia Suryandari