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All Journal JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JURNAL MAHAJANA INFORMASI Jurnal Sains dan Teknologi Jurnal Tekinkom (Teknik Informasi dan Komputer) INFOKUM Journal of Computer Networks, Architecture and High Performance Computing Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN)
Windania Purba
Program Studi Sistem Informasi Universitas Prima Indonesia Medan
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Other

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ANALISIS DAN PERANCANGAN SISTEM LAYANAN DAN RESERVASI TIKET BUS ONLINE MELALUI PENDEKATAN BERBASIS WEBSITE Palma Juanta; Windania Purba; Evta Indra; Mario Gota Manalu; Aguan Aritonang
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.944

Abstract

In this day and age the bus is the most common means of transportation used by the community because of the low price and easy way of ordering simple and accurate and still affordable for the economic community middle down. Generaly bus ticket bookings are made with go directly to the point of sale of bus tickets or by calling to the counter office. This ordering process has a weakness, namely the clerk or managers have difficulty recording, and errors often occur when recording ticket reservations. Regarding the time of ordering, usually prospective travelers book tickets a day or two before departure, and some are don't book tickets a few days in advance and buy tickets on the day departures, which often results in them not getting tickets that are society wants. The aim of this work is to design the system online bus ticket reservation developed using an application. Program it is built using Python programming and machine learning to make it easier to generate data automatically and make predictions Accurate. The result of this research is a bus ticket reservation system which offers a new alternative to the bus ticket booking process without distance and time constraints. In addition, the public will also receive information regarding bus schedules, ticket prices, and possible changes to departures bus.
PENERAPAN METODE REGRESI LINEAR MEMPREDIKSI TINGKAT PENJUALAN SEPEDA MOTOR HONDA PADA PT. PLATINA MULIA ABADI Palma Juanta; Saut Parsaoran Tamba; Windania Purba; Yoel Ferdinand Zai; Steven Steven; Elbert Ghozali
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.941

Abstract

This research aims to obtain predictions of Honda motorbike sales based on Honda motorbike sales data at PT. Platina Mulia Abadi is a company engaged in transportation and automotive services, especially sales of Honda motorbikes. The linear regression method is used to predict the number of sales of Honda motorbikes. The uncertainty in the number of sales of Honda motorbikes to this company has slightly hindered the company's development, because the company cannot take a definite policy regarding the sales that occur. Therefore, this company estimates future sales of Honda motorbikes for this company, so that management can estimate future consumer demand. So that the company is able to serve and provide consumer demand. To carry out estimates, the Multiple Linear Regression method is used. The results of this research obtained an estimated sales of manual motorbikes in 2023 in January of 64,003 or 64 units of Honda motorbikes in the manual category. This means that there is an increase in the number of manual Honda motorbikes by 8 motorbikes, while the results until May 2023 are 72,123 motorbikes. Through the application of this method, the estimated sales of Honda motorbikes in the next 5 months at PT. Eternal Precious Platinum can be done easily and quickly.
Co-Authors Ade Syahpitri Aguan Aritonang Angelin Angelin Ayu Elpriyani Sidabutar Derry Rosanta Br.sitanggang Desty Rukmana Elbert Ghozali Evta Indra Fransisco Andreas Sirait Grace Fitri Anggi Munthe Henry Triadi Manurung Irsan Jaya Sihombing Lina Sari Harefa Mario Gota Manalu Maxwell Paulus Siregar Nur Ainun Siahaan Okta Jaya Harmaja Palma Juanta Riski Nofarianus Gulo Saut Parsaoran Tamba Siti Aisyah Steven Steven Tonny Tendean Yessy Yessy Yoel Ferdinand Zai