Open AccessBANGKITAN PERJALANAN BERDASARKAN STRUKTUR DAN PENDAPATAN RUMAH TANGGA DI KECAMATAN MUTIARA KABUPATEN PIDIE
Author(s) -
Edward Zeen,
Renni Anggraini,
Sugiarto Sugiarto
Publication year - 2020
Publication title -
jurnal arsip rekayasa sipil dan perencanaan
Language(s) - English
Resource type - Journals
eISSN - 2620-7567
pISSN - 2615-1340
DOI - 10.24815/jarsp.v3i1.16453
Subject(s) - license , population , service (business) , geography , socioeconomics , sample (material) , business , family income , stratified sampling , economic growth , economics , mathematics , statistics , demography , sociology , marketing , political science , chemistry , chromatography , law
Mutiara Sub-district to this day continue to develop. The land that was once a rice field and vacant land has now been converted to become a store building. Increasing population in the area resulted in an increase in the number of transport movements, which will affect road capacity. This study aims to determine the pattern of rise of movements based on structure and household income reviewed in mandatory and non mandatory activities in Kecamatan Mutiara. The population in Mutiara sub-district is 20,810 people, through Slovin formula, the sample is 393 people. The sampling technique used is proportionate stratified random sampling. Calibration of regression parameters used Ordinary Least Square (OLS) method with Statistical Product and Service Solution (SPSS) version 22 software. The result showed that mandatory activity of movement of household structure 2 children influenced by gender factor, age and ownership of SIM , the rise of household income movements 3 million is influenced by age factor, number of family members already employed, number of motorcycles in the family, number of cars in the family, and ownership of driving license. In non-mandatory activities the rise of household income movements of 3 million is influenced by sex factors, and education level, the rise of household income movements 3 million is influenced by occupational factors, number of family members already employed, number of family members still in school, the number of motorcycles in the family, the number of cars in the family, and the ownership of the driver's license