Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Sainteks: Jurnal Sain dan Teknik
Vivien Nopella Valentina
Univertas Palangka Raya
Chemical Engineering, Chemistry & Bioengineering Chemistry Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Analysis of Interest In Using Electrical Bicycles in Palangka Raya Vivien Nopella Valentina; Robby Robby; Sutan Parasian Silitonga
Sainteks: Jurnal Sain dan Teknik Vol 5 No 2 (2023): September
Publisher : Universitas Insan Cendekia Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37577/sainteks.v5i2.606

Abstract

Every year the number of population growth is increasing, therefore the use of transportation is also increasing. With the existence of environmentally friendly transportation products, it is hoped that more and more people will contribute to using them to reduce the impact of global warming. One of the environmentally friendly transportation products is an electric bicycle. This study specifically aims to analyze the characteristics of electric bicycle mode selection and analyze the electric bicycle mode selection model in the city of Palangka Raya. The development of electric bicycles in anticipation of depleting reserves of fuel oil has begun. Palangka Raya City is one of the cities where the use of electric bicycles is gaining popularity. The Logit Binomial model was used to analyze the data from the sort of survey employed in this research, which was based on respondents' expressed preferences. According to the findings of the research, it was shown that what influenced interest in choosing the mode of electric bicycle use were the variables age (X1), gender (X2), family structure (X3), motorcycle ownership (X11), long distance traveled (X15), education/school (X22), spending per month (X24) it is obtained that the overall model prediction rate variable is 79%.
Co-Authors Robby, Robby Silitonga, Sutan Parasian