分析印尼十区公共交通工具或非永久流动工人的选举情况

Chotib Chotib
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引用次数: 3

摘要

有几种类型的非永久性流动,通常与居住地点和工作地点之间的地点差异有关。非永久性流动包括通勤、循环和季节性迁移。通勤是一种非永久性的流动方式,指一个人在不同的地方工作,每天早上离开,下午或晚上返回。流动是指一个人在工作地点(与其居住地不同)居住少于三个月但超过一天的非永久性流动。季节性移徙是一种非永久性流动,人们在工作场所(目的地地区)居住3至6个月。本研究旨在确定印度尼西亚10个大都市区工人使用公共交通工具的可能性,包括搬家和停留,即Mebidang(棉兰大都市区),Palapa(巴东大都市区),Patungraya Agung(巨港大都市区),Jabodetabek(大雅加达),万隆Raya(万隆大都市区),Kedungsepur(三宝琅大都市区),Gerbangkertosusila(泗水大都市区),Sarbagita(登巴沙大都市区),班贾尔巴库拉(班贾尔马辛大都市区)和Maminasata(望加锡大都市区)。对2017年Sakernas数据的二元Logistic回归分析结果表明,使用公共交通的概率因个人特征、出行模式和大都市圈而异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analisis Pemilihan Moda Angkutan Umum atau Pribadi Pekerja Mobilitas Non-Permanen di Sepuluh Wilayah Metropolitan Indonesia
There are several types of non-permanent mobility which are generally related to location difference between places of residence and places of work. Non-permanent mobility consists of commuting, circular, and seasonal migration. Commuting is a type of non-permanent mobility where a person works in a different place from his residence, he/she leaves in the morning and returns in the afternoon or evening every day. Circular is a type of non-permanent mobility where a person lives in a workplace (which is different from his place of residence) for less than three months but more than one day. Whereas seasonal migrantion is a type of non-permanent mobility where the person lives in the workplace (destination area) between 3 and 6 months. This study aims to identify the probability of public transportation use by workers, both as movers and stayers, in ten metropolitan regions in Indonesia, namely Mebidang (Medan metropolitan area), Palapa (Padang metropolitan area), Patungraya Agung (Palembang metropolitan area), Jabodetabek (Greater Jakarta), Bandung Raya (Bandung metropolitan area), Kedungsepur (Semarang metropolitan area), Gerbangkertosusila (Surabaya metropolitan area), Sarbagita (Denpasar metropolitan area), Banjar Bakula (Banjarmasin metropolitan area), and Maminasata (Makassar metropolitan area). The results of the analysis with Binary Logistic Regression on the Sakernas 2017 data shows that the probability of using public transportation varies according to individual characteristics, patterns of mobility and varies over Metropolitan Areas.
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