Analyzing the influence of age groups of motorcycle riders on traffic violations and accidents in small city using a structural equation model

Over the last three years, there has been a tremendous increase in the amount of road accidents in Mataram City-Lombok with majority of the victims being motorcycle riders between the ages of 16-40 years. The age difference may have an impact on the rider’s behavior which in turn leads to road accidents. This study aims at investigating the influence of age groups on motorcycle riders resulting to traffic violations and road accidents in Mataram City. Data was collected using questionnaire survey for which 600 respondents participated covering 6 sub-districts in Mataram City. A Structural Equation Modeling (SEM) using AMOS V.22.0 was constructed to analyze the motorcycle rider behavior. The developed model was made up of behavioral, violation and accident latent variables, with four variables of behavior, three variables of violation, and two observed variables of accident. Three age groups were used in this study with three categories consists of 15-24 years, 25-44 years, and 45-64 years old. This study found that these riders behaviors varied significantly with regards to traffic violations. The age groups of riders between 15-24 years and 45-64 years has a 65% influence on traffic violation compared to those between the ages of 25-44 years. Traffic violations with regards to road accidents was however, found to be less significant for all age group. Traffic violations committed by riders between ages of 45-64 years were found to be 14% less than those between the ages of 15-44 years. The analysis obtained from the data indicates that there are differences among the three listed age groups.


Introduction
Traffic accidents are influenced by a couple of factors, such as environmental factors, vehicle factors, road factors and human/ driver factor (ability, discipline, emotion, and driver behavior). One of the factors associated with human factors is age. The differences in the age group of drivers have been attributed to influencing motorcycle riders. Accidents are as a result of traffic violations. A traffic violation can be defined as an intervening variable (mediation variable) between the driver and the road, thereby, leading to a traffic accident. Violations and traffic accidents in Mataram City is mainly made up of motorcyclists. Therefore, there is the urgent need to study, the driving behaviors motorcycle riders have on traffic accidents, using Structural Equation Modeling (SEM). SEM was used in this study because it can explain more clearly on multivariate data. The data obtained show that violations and accidents in Mataram-Lombok City mostly involve riders between 16-40 year old (70.9%). During the last three years, the number of traffic accidents in Mataram City-Lombok has increased significantly. Based on the data obtained from the last three years, over four thousand accidents occurred with these victims from several age groups. The accident victim for the age group of 16-40 has increased since 2015 with its victims rising from 1,061 victims in 2015 to 1,115 victims in 2016, and decreasing to 820 victims in 2017. This range of ages is different from the research result obtained from research conducted in England, where young male drivers between the ages of 18-25 and older male drivers' between the ages of 35-50 were analyzed and examined of their driving ability. Both groups showed different conceptions of their own accident risk, further generating subjective ratings of the risk of accident with fatality injury rate. The number of accident victims based on age groups from 2015 to 2017 is presented in Table 1.   Mataram  15  33  21  94  124 105  50  55  36  25  36  22  15  34  34  699   2 Res Lobar  10  11  3  63  81  35  39  22  6  25  16  9  10  6  5  341   3 Res Loteng  32  14  12  84  88  74  53  24  32  23  30  15  11  11  15  518   4 Res Lotim  27  32  6  240 269 185 104  82  80  54  58  50  16  48  3  1254   5  Res SBW  Barat  4  6  9  15  21  13  14  18  0  10  5  7  4  8  2  133   6  Res  Sumbawa  15  23  9  71  83  43  56  41  13  25  35  4  10  14  9  analysis, the researcher used the SEM method using the AMOS software. One of the sole reasons for using the AMOS software it is its user-friendliness.
The objectives of this research are as follow: 1) to investigate the influence of motorcyclist behaviors on traffic violations among several age groups in Mataram City, 2) to evaluate the impact of traffic violations on traffic accidents by comparing the differences in several age groups in Mataram City, and 3) to examine the significance influence value for each age group.

Definition of age
Age can be defined as the unit of time used to measure the time of existence of an object or creature (living or dead). For example, if someone is fifteen years old, it means that age has been measured from the day he was born until the day it was calculated.

Definition of traffic violation and traffic accident
Traffic violations are actions that are contrary to traffic laws, either intentionally or unintentionally committed. According to the 2009 Indonesian Traffic Law No. 22 Road Traffic and Transportation Laws, traffic accidents are an unexpected and unintentional accident involving vehicles, with or without other road users, resulting in human casualties and/ or property damage. According to Suwardi [1], traffic accidents can be defined as an incident in road traffic were at least one vehicle, is damaged and to the detriment of the victim and owner of the vehicle.

Traffic accident factors and driver behavior
Accident factors are identical to the factors responsible for traffic, such as road users, vehicles, roads, and environmental conditions. According to Warpani (2002), the primary cause of road accidents in Indonesia is human. This is either due to the negligence or neglect of motorists or as a result of the deliberate disobedience of traffic laws on public roads. According to Lulie (2005), a driver's behavior is defined as the behavior of a vehicle owner or user in driving and caring for a vehicle how a person drive has a significant impact on whether or not there will be an accident. Dwiyogo and Prabowo [2], beams that a driver's behavior originates from the interaction of human factors with other factors such as vehicle's condition and the road.

Structural Equation Model
Santoso [3], defined SEM as a multivariate statistical technique which comprises of factor analysis and regression analysis (correlation), with the aim of testing the inter-variable relationships that exist within a model, either inter-indicator with its constructor the relationship between constructs.

Initial of research model
The multivariate statistical technique is defined as a combination of factor and regression analysis (correlation), used to test the inter-variable relationships in a model. This The hypothesis used in carrying out this research study is as follows, 1) H1: Used to denote the hypothesis that driving behavior positively affects the number of traffic violations; 2) H2: Used to denote the hypothesis that traffic violations have a positive effect on traffic accidents.

Validity test
The instance is valid if the value of r count > r table and also if the questionnaire instrument can be used for data collection. Alternatively, when r arithmetic < r table, the instance will be declared invalid and will no longer be used in data collection. The formula used for a validity test using the product of moment technique is: where R = relation coefficient, X = the first score, in which case X is the scores of the item to be tested for its validity, Y = the second score, in this case Y is the number of scores by each respondent, ΣXY = number of first score multiplication result with second score, ΣX² = quantity of first scores result, ΣY² = quantity of results of the second scores. Validity testing was carried out using the SPSS program. The validity of each item can be seen by the total correlation value for each corrected question.

Reliability test
Reliability is described as the extent to which the measurement results obtained remain consistent, through multiple repetitions of the experiment with matching tools and circumstances.
Where r 11 = reliability instrument, k = the number of questions, Σσb² = number of variance point, σ1² = all of variance. The level of reliability based on Alpha values can be seen in Table 2.

Sampling technique
The population in this study consist of motorcycle riders covering six sub-districts in Mataram City. The data obtained proofs that there is an estimated total population size of 459.314 motorcycle riders. The data was obtained from the 2017 official statistic motorcycle riders statistics. According to Sugiyono [4], the sample research number can be determined using Slovin formula: where α = denotes the deviation of the desired population or degree of reliability (5%), N = population size (459.314 people), n = sample size.

Data collection method
Data was collected through the use of questionnaires distributed to the motorcyclist respondents. The questionnaire used in carrying out this research study made use of a Likert scale, 1-5, to measure the attitudes of respondents towards each question. The Likert scale used in this research is as follows ( Table 4).

Structural equation modeling (SEM) analysis with the AMOS program
The SEM process cannot be manually performed. In addition to the various limitations associated with human capabilities, the complexity of the models and statistical tools used make manual calculations inefficient. So it's essential to make use of special software for calculation such as the AMOS program. Models analyzed in this study using the AMOS program can be seen in Fig. 2. Table 6 shows that overall (multivariate) data are normally distributed with respectto the critical ratio above 1.96 for 5% significance but outside ± 2.58 for 1% significance.   Table 6. Critical Ratio Value of each age groups.

Modified SEM models
In AMOS, when the SEM model is found not be a fit, it is a recommendation that the model is modified. Recommendations for model modifications will appear on the AMOS modification indices output. The result of the validity test for the revised model are shown in Tabel 7. The fit model test recommendation used to modify model is summarized Table  8. Figure 3 shows SEM models after modification for 15-24 age group.

Analysis of indicator relationship with variables and inter-variables
The results of the data analysis of the indicator's relationship using variable and the intervariable is presented in Table 9.  Table 10 shows the output of standardized regression weight. Table 11 shows a close relationship between constructs to every age goups.

Conclusions
Based on data analysis and discussions, a few main conclusions were made. Driving behavior positively and significantly influences traffic violations. The magnitude of influence on riders of age group 15-24 years and 45-64 years is 65% higher than riders of age group 25-44 years. This indicates that the traffic violations are more common among riders of age group 15-24 years and 25-44 years old. Traffic violations have a weak relationship to traffic accidents with factor loadings < 0.5. The magnitude of the effect of violations committed by riders of the age group 45-64 years is 14% smaller than the number of influence riders of the age group 15-44 years. This is an indication that traffic violations do not always cause traffic accidents. There are differences in driving behavior between motorcycle riders of the age group 15-24 years, 25-44 years, and 45-64 years.