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Analyzing the Influence of Socio-Demographic Characteristics on Travel Mode Choice in Banda Aceh City Through Association Rules

In formulating improvements to integrated transportation planning for the Banda Aceh city which has been urbanizing speedily and has experienced considerable changes in growing economy and motorization, it is necessary to understand the factors that influence community choice of travel modes, one of which is the influence of the sociodemographic characteristics of the community. This is due to the importance of knowing the characteristics and behaviour of modal users in designing transportation facilities and infrastructure to be provided. In this study, association rules are used to analyse the influence of demographic characteristics on the choice of travel modes in the Banda Aceh city. The data used in this study came from survey data conducted by the Aceh Transportation Agency in 2019. After the data analysed through setting up association rules, it shows that role of socio-demographic variables on the choice of travel modes is quite significant in many aspects.


Introduction
Transportation is a movement from the place of origin to the destination and occurs because of the process of fulfilling needs. The variety of human needs in terms of moving to a place affect the tendency in the choice of mode.
The choice of transportation mode is one of the most important things in transportation planning. This is because it is important to know the characteristics and behaviour of mode users in designing the transportation facilities and infrastructure that will be provided.
Banda Aceh city, the capital of Aceh Province, is one of the medium sized cities with the population around 270,321inhabitants and consists of 9 sub-districts and 70 villages [1]. As with many medium cities in Indonesia, Banda Aceh city has been urbanizing speedily and has experienced considerable changes in growing economy and motorization. In formulating improvements to integrated transportation planning for the city of Banda Aceh, it is necessary to understand the Data Prepared for Data Mining factors that influence community choice of travel modes which is one of the characteristics of travel behaviour. One of which is the influence of the socio-demographic characteristics of the community i.e. age, gender, income group, etc.
The choice of the transportation modes in urban area is a random process influenced by several factors, one of which is economical social status. The level of one's economical social status is determined by the education, occupation, and income.

Materials
The data used in this study came from survey data conducted by the Aceh Transportation Agency in 2019 about railway feasibility study in Banda Aceh city. The survey was conducted to see respondents' perceptions if railroad transportation operates in the city of Banda Aceh. However, in this paper the data used are the socio-demographic data of the community and the types of vehicles used today so that the socio-demographic relationship between the community and the choice of the mode of transportation used will be seen through setting up association rules.

Method
Before setting up association rules, there is a step called data pre-processing, which is one of the most important first steps in data mining. Pre-processing of a data set is required if the data set consists of data that is unnecessary and incomplete (missing), noisy (outlier) and inconsistent data [2]. This step can be seen in Figure 1 below:

Raw data
In the raw data about railway feasibility study in Banda Aceh city, there is socio-demographic information regarding respondents, namely age, gender, household income, level of education, and mode choice. In addition, there is also information on the character of the trip in the form of transportation costs incurred in a month, the purpose of the trip, the number of trips in a month,

Raw Data
Data Cleaning Data Integration Data Transformation Data Reduction and the type of transportation used. In the data set, there were 2280 respondent data, but because some of the respondent's data were incomplete and some of the respondent's information was not used in this study, the data was cleaned so that there were 2231 respondents.

Data cleaning
In this study, the following arrangements have been made on the data set, considering that it is appropriate to remove the record with the lost data from the database.
Because data such as trip origin, trip destination, travel time and others could not be combined and could not give meaningful relationships, it was removed from the data set. In addition, parts of the data that were left blank and expressed ambiguously belonging to some features were removed from the data set during the data cleaning phase.
There were 49 respondent data that were excluded from the data set because some parts of the information were blank and incorrect (erroneous). Hence, after cleaning the data, there are 2231 respondents' data left. While performing these operations, filter feature in Ms. Excel program was used.

Data arrangement and creating data set
The distributions of the data according to the features in the data set obtained after the data cleaning process are given in Figures 2, 3, 4, 5 and 6.   Figure 3, it can be seen that the largest number of travelers are men, which is 58% of the total respondents who traveled.  Figure 4 it can be concluded that the income of most of the people of Banda Aceh city is IDR 20,000.00 -2,415,000.00 which is 59%. This income value is below the provincial minimum wage set by the Governor of Aceh, which is IDR 3,165,031.00 [2]. From the distribution in Figure 5 above, it can be seen that the most dominant education level of the people of Banda Aceh and its surroundings is high school by 48%, followed by bachelor graduates by 35%. While the lowest education levels are vocational high school, associate degree, and doctorate whose respective percentages do not even reach 1%. From the distribution in the Figure 6, it can be concluded that the most common types of transportation used by the community are private vehicles, namely cars by 32% and motorbikes by 30%. Meanwhile, motorized rickshaws and taxis are the least used, each of them have a percentage of 1%.
Information in the data set for study analysis is classified and can be seen in Table 1. Classification of features in the data set is grouped into classes to build meaningful relationships.

Data Analysis
The large amount of data, as well as the heterogeneous and versatile features of them, enabled data mining applications to be used as a very effective method in analysis process. In this study the WEKA application is used because it is a good tool in completing various purposes in data mining, where there are four WEKA application interfaces, namely explorer, experimenter, knowledge flow, also simple command line [2].

Data Analysis Method
In this research, analysis of the relationship with association rules in data mining was carried out. Algorithms are used to scan all available data to reveal large collections of objects. On the first scan, the support level of each object is compared with the initial minimum support level to evaluate whether each object is large. Each subsequent scan starts from the broadly defined objects of the previous scan and a large object cluster is created. The support of this object set is calculated to the end of the data set. This process continues until no other large object set is found [4].
In association rules the concepts of trust level (support), level of support (confidence) and interest (leverage) are criteria that express the strength of the rules.

Data Analysis
Five different analyses were conducted in this study. The threshold values of the analysis and the variables used are given in Table 2. The first step carried out in the WEKA application, namely; choose "open file" where the data have been converted into .csv or .arff format. The next step is to select "NumericToNominal" in the filter section and press "apply". In the associate section select "apriori", enter the minimum support and lift value, then press "start" are applied. -358 of them are in the age group 2 (26-40 years), and from this age group 194 of them are in the household income group 2 (IDR 2,416,000.00 -4,811,000.00), where the confidence value is 0.54 and the lift value is 1.14.

Mode choice analysis of car
-336 of them are in the level of education group 6 (bachelor degree), and from this level of education 175 of them are in the household income group 2 (IDR 2,416,000.00 -4,811,000.00), where the confidence value is 0.52 and the lift value is 1.1.
-444 of them are in the gender group 1 (man), and from this gender group 191 are in the age group 3 (41-55 years old), where the confidence value was 0.43 and the lift value was 1.09.
Best rules found: When 679 data where the respondents chose motorcycle as the mode of transportation in the data set were analysed, shown in Figure 8 above; the followings are the reached.

Mode choice analysis of motorcycle
-394 of them are in the level of education group 3 (high school), and from this level of education group 149 of them are in the gender group 0 (woman) and household income group 1 (IDR 20,000.00 -2,415,000.00), where the confidence value is 0.38 and the lift value is 1.22.
-459 of them are in household income group 1 (IDR 20,000.00 -2,415,000.00), and from this household income group 151 of them are in the gender group 1 (man) and level of education 3 (high school) where the confidence value is 0.33 and the lift value is 1.19. When 246 data where the respondents chose motorcycle taxi as the mode of transportation in the Best rules found: data set were analyzed; the followings have been obtained.

Mode choice analysis of motorcycle taxi
-93 of them are in the level of education group 6 (bachelor degree), and from this level of education group 64 of them are in the age group 2 (26-40), where the confidence value is 0.69 and the lift value is 1.26.
-163 of them are in the age group 3 (41-55), and from this age group 58 of them are in the household income group 1 (IDR 20,000.00 -2,415,000.00), where the confidence value is 0.92 and the lift value is 1.23. When 384 data where the respondents chose bus as the mode of transportation in the data set were analyzed; the below findings are obtained.

Mode choice analysis of bus
-341 of them are in the household income group 1 (IDR 20,000.00 -2,415,000.00), and from this household income group 123 of them are in the level of education group 3 (high school) and gender group 1 (man), where the confidence value is 0.36 and the lift value is 1.11.
Best rules found: are the findings attained.

Discussion
In order to reveal the factors affecting the mode choice, the apriori algorithm was used in this study, and analyses were made by determining appropriate thresholds for support and lift values. In the respondents' data, mode choices were classified according to the respondents' choice which are car, motorcycle, motorcycle taxi, bus and minibus. Following, relevant analyses were carried out on the basis of this classification. Analysis of the choice of mode for motorized rickshaw and taxi was not carried out due to the small percentages available. As a result of these analyses using WEKA application; Best rules found: In the mode choice group 4 (bus) and 5 (minibus) which are public transportation, the dominant gender group is gender group 1 (man). Another interesting finding is that the household income group 1 (IDR 20,000.00 -2,415,000.00) dominates in the mode choice 2 (motorcycle) group. This can be caused by many things, one of which is the ease of owning a private vehicle, especially a motorcycle, and inadequate public transportation facilities in Banda Aceh city [5].

Conclusions
From the analyses it can be expressed that socio-demographic factors play an important role in the choice of transportation modes, especially in the city of Banda Aceh which can be seen that there are more private vehicle users than public transportation users influenced by age, gender, level of education, and household income. This can lead to various transportation problems such as congestion, increasing CO2 emissions, noise pollution, traffic clutter, and others. By looking at the socio-demographic analysis in this study, it is hoped that it will provide input to stage holders in making policies in the city of Banda Aceh. One effort that can be done is to improve the public transportation system so that people who use private vehicles want to switch to public transportation.