ANALYSIS OF ACCEPTANCE AND USE OF ONLINE TRANSPORTATION ON GRAB AND GO-JEK APPLICATION FOR THE PUBLIC USING THE UTAUT2 MODEL (CASE STUDY: BANDUNG)

The development of online transportation using grab and go-jek applications is now very rapidly developing and more influencing in changing people’s lives. This research was focus on Bandung, West Java, Indonesia. In 2021, Grab and Go-jek applications are not only developing in Indonesia but have spread throughout Southeast Asia such as Singapore, Malaysia, and Thailand. However, use of the online transportation can make competition between other public transportation. This research will help online transportations to evaluate their performance on the acceptance and use of grab and go-jek applications. With this research grab and go-jek applications can know which part they need to improve and suggestions for grab and go-jek applications to increase their service and quality of orders. This research takes eleven major factors UTAUT 2 models that have an impact on how a customer can accept and use online transportation for grab and go-jek applications. Those factors are performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit, and then add two external variables are service quality and customer satisfaction. This research will use survey and distribution of questionnaires method to gain some information from the customer. After collecting some data and information. This research will use SPSS and AMOS to process the data to know which hypotheses are accepted and rejected. The method using by this research in AMOS is SEM. SEM will give a significant point for every question to know the result can accept or reject.


Introduction
Grab and go-jek applications are growing fast enough for online transportation service companies that use android applications. Many people are starting to switch to online transportation for reasons of speed, timeliness, and also low prices compared to public transportation (Silalahi, Handayani, & Munajat, 2017). Thus, some public transportation or conventional transportation has moved to online transportation. The purpose of all this is none other than to win the competition with the existing competitor people as users or consumers of online transportation will choose to use transportation with easy access, comfort, and at low rates. Thus, online transportations are the main choice for consumers.
Along with the development of online transportation technology, it has become the choice of a community to facilitate their destinations (Septiani, Handayani, & Azzahro, 2017). In this study, the researchers will discuss online transportation using the grab and go-jek applications the grab and go-jek applications have become a means of public transportation for the community, both online motorcycle taxis in the form of motorbikes and cars. Online transportation itself is one of the vehicle choices for the community because it is considered to fulfill a sense of security, safety, affordability, and convenience in using an application-based motorcycle taxi service as online transportation, which makes it very easy for the community (Hardaningtyas, 2018).
In Indonesia, there are almost 21.7 million people using ride services or various rides on the grab and go-jek applications (Tempo, 2018). Almost 75% of Indonesian internet users already use mobile applications such as grab and go-jek applications. With the development and competition that is getting faster, these two applications are increasingly dominating users because of the shortcomings of conventional types of transportation. In addition, there are disturbances from new competitors because of the small opportunity to enter the work sector in community online transportation.
Competition has developed in online transportation using mobile applications that do not reduce the public's use of grab and go-jek applications. With the transportation development process that continues to run, the grab and go-jek applications provide easy access and convenience (Fauz, Widodo, & Djatmiko, 2018). People in Indonesia, especially in Bandung, the online transportation industry has the opportunity to grow rapidly.
This study using the UTAUT 2 model. This study is based on the UTAUT 2 model that has developed using seven main constructs, namely performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit, and adds two external variable constructs, namely service quality, and customer satisfaction. To find out and test the analysis of the acceptance and use of the grab and go-jek applications on the attitudes of community users towards the entry of online transportation and the benefits of an application for using online transportation.
According to (Venkatesh, Thong, & Xu, 2012), the definition of a unified theory of acceptance and use of technology 2 (UTAUT2) is a model with acceptance of new technology. According to (Bendi & Andayani, 2013), the definition of a unified theory of acceptance and use of technology 2 (UTAUT2) is a model that can explain how user behavior responds to new information technology. Meanwhile, the research opinion according to (Arenas Gaitán, Peral Peral, & Ramón Jerónimo, 2015) defines the UTAUT 2 model as to how to unite several models to be compared into one theory of technology acceptance. The UTAUT 2 model has been developed from the development of new technologies that have been adapted from the previous UTAUT model, where the previous UTAUT model used in the form of an organization or group is reduced to individual use.
According to (Venkatesh et al., 2012) effort expectancy is a construction of the UTAUT model that measures the level of ease of use associated with the use of information technology. Meanwhile, according to (Celik, 2016) effort expectancy is an individual assessment of the level of technology utilization that does not require more effort. From some of these studies, it can be concluded that effort expectancy is the ease with which users can use a system or technology.
Moreover, this study aims to knowing performance expectancy can influence behavioral intention towards grab and go-jek applications the people of the city Bandung, knowing effort expectancy can influence behavioral intention towards grab and go-jek applications the people of the city Bandung, knowing social influence can influence behavioral intention towards grab and go-jek applications the people of the city Bandung. knowing facilitating conditions can influence behavioral intention towards grab and go-jek applications the people of the city Bandung, knowing facilitating conditions can influence user behavior towards grab and go-jek applications the people of the city Bandung, knowing hedonic motivation can influence behavioral intention towards grab and go -jek  applications the people of the city Bandung,  knowing price value can influence behavioral  intention  towards  grab  and  go-jek  applications the people of the city Bandung,  knowing habits can influence behavioral  intention  towards  grab  and go-jek applications the people of the city Bandung, knowing habits can influence user behavior towards grab and go-jek applications the people of the city Bandung, knowing service quality can influence behavioral intention towards grab and go-jek applications the people of the city Bandung, knowing customer satisfaction can influence behavioral intentions towards the people of the city Bandung, and knowing behavioral intention can influence user behavior towards the people of Bandung.

Method
In this methodology, the questionnaire is used as part of a survey-based method (Sugiyono, 2019). The questionnaire used describes questions about the benefit of using online application-based transportation, namely, grab and go-jek using the UTAUT 2 model method which consists of several constructs, and the objects used in this study are the people of Bandung who use online transportation based on the grab and go-jek applications. This study uses SPSS and SEM AMOS to check the answers from this survey that target samples do (Cresswell, 2017). SPSS is a software or program stands for statistical product and service solution, which is a program or software used for statistical data processing purposes (Herlina, 2019). Structural equation modeling (SEM) as a multivariate statistical tool that combines factor analysis and multiple equations (regression) or correlation analysis, models (Santoso, 2015). Not only that, but this research also can control the target sample so that answers from the survey could not sample any.

A. Research Model
This research model was conducted using a modified model of the unified theory of acceptance and use of technology 2 (UTAUT 2) developed by (Venkatesh et al., 2012). By eliminating gender construction because this study is aimed at all people regarding the acceptance and use of information technology in the form of a grab and gojek application for online transportation. While the aim is to find out whether a new technology in the form of online transportation for the grab and go-jek applications can enter the community and be accepted by its use.

B. Research Hypothesis
H1:How does the relationship between performance expectancy affect behavioral intention to grab and go-jek applications for the community. H2:How does the relationship between effort expectancy affect behavioral intention to grab and go-jek applications for the community. H3:How does the relationship between social influence affect behavioral intention to grab and go-jek applications for the community. H4:How does the relationship between facilitating conditions affect behavioral intention to grab and go-jek applications for the community. H5:How does the relationship facilitating condition affect use behavior to grab and go-jek applications for the community. H6:How does the relationship hedonic motivation affect behavioral intention to grab and go-jek applications for the community. H7:How does the relationship price value affect behavioral intentions for the community. H8:How does the relationship habit affect behavioral intention for the community. H9:How does the relationship habit affect user behavior for the community. H10:How does the relationship service quality affect behavioral intention for the community. H11:How does the relationship customer satisfaction affect behavioral intention for the community. H12:How does behavioral intention affect use behavior to grab and go-jek applications for the community.

C. Research Objects 1. GRAB
Grab is an application-based transportation service and service Analysis of Acceptance and Use of Online Transportation on Grab and Go-Jek Application for The Public Using the UTAUT2 Model (Case Study: Bandung) company that was originally located in Singapore. Starting from an online taxi service, the grab has a vision and mission to revolutionize the taxi industry in Southeast Asia but over time, the grab has spread other types of features in the form of online transportation services in the form of motorbikes taxis, and cars (Chan, Maharani, & Tresna, 2017). Grab now has additional feature services such as food delivery and payment which are accessed via the mobile application. In Indonesia, the grab service has been around since 2012 as a rural taxi application and has provided various transportation options such as cars and motorbikes in the form of online motorcycle taxis. Grab is an online transportation service company that transports passengers with an application that moves on the android application to order shuttle passengers to the destination users. The grab application uses GPS to use a mapping tool or a location map to read the point where the customer is located (Widyatama et al., 2020). In addition, the grab service has a ride hilling service as a daily transportation solution. Where users of the grab application can determine the type of vehicle, payment method, and also the desired destination through the application.

GO-JEK
The go-jek journey began in 2010 as an ojek call center in Indonesia. In 2015, Indonesian-made applications launched services namely Goride, GoCar, Godsend, and Gomart. With the development of technology since then, the go-jek application can develop into a super application with a multi-service platform with more than 20 services to date (Pudjarti, Nurchayati, & Putranti, 2019). Now, go-jek has become a leading technology platform group that serves millions of users in Indonesia by developing three super-apps such as for customers, driver-partners, and merchant partners.
With GPS, users can monitor the location of the nearest motorcycle taxi fleet and car the shortest and farthest route to reach their destination. So that the GPS (Global Positioning System) can provide convenience by providing information on whereabouts for pick-up and drop-off purposes to the user's location. The presence of applicationbased online transportation can provide many benefits for the community and also benefits for online motorcycle and car taxi drivers themselves. Starting from saving travel time, making costs more economical, to making travel more practical.

A. The Results of Early-Stage Data Collection
There are several points of analysis points of analysist contained in the discussion of this research. 1. How performance expectancy does the grab and go-jek applications work as online transportation on behavioral intention in public. 2. How effort expectancy does the grab and go-jek applications work as online transportation on behavioral intention in public. 3. How social influence do the grab and go-jek applications work as online transportation on behavioral intention in public. 4. How facilitating condition do the grab and go-jek applications work as online transportation on behavioral intention in public. 5. How facilitating condition do the grab and go-jek applications work as online transportation on use behavior in public. 6. How hedonic motivation do the grab and go-jek applications work as online transportation on behavioral intention in public. 7. How price do the grab and go-jek applications work as online transportation on behavioral intention in public. 8. How habit do the grab and go-jek applications work as online transportation on behavioral intention in public. 9. How habit do the grab and go-jek applications work as online transportation on use behavior in public. 10. How service quality does the grab and go-jek applications work as online transportation on behavioral intention in public. 11. How customer satisfaction does the grab and go-jek applications work as online transportation on behavioral intention in public. 12. How behavioral intentition do the grab and go-jek applications work as online transportation on use behavior in public.
In this data analysis, researchers used gender and age as respondent data in filling out and managing the questionnaire. Using gender and age with the aim that the data can be grouped in the concept that can be seen. The use of gender serves to make it easier for researchers to divide the grouping of how many genders is male and female and how much is the use of an application for gender.
The validity test of data collection was carried out to obtain results from a respondent who was suitable as data sources because researchers did not know the number of respondents in the community as users or customers of the grab and go-jek applications. A reliability test is used to measure two or more times of symptoms and use the same measuring instruments. The size method used in this study to measure the range scale of an indicator can be declared reliable using Cronbach alpha. Cronbach alpha can find out the consistency of the measuring instrument whether the item of a question is included in the testing phase whether the instrument is reliable or using acceptable limits if the value is > 0,6. Overall the reliability test used Cronbach's alpha method. In general, decision-making for reliability testing can use the coronach's alpha method with a limit of 0.6 which is acceptable reliability.  variable have a significance to the variable, it can be seen by the construct *** in column P. With the symbol *** indicates that P (probability value) is less than 0.05 or below 5% (P<0.05)

b) Testing Variable Effort Expectancy
From the results of the table below, it can be seen that the three constructs of the effort expectancy variable have a significant relationship to the measured variable. Three constructs can be significant to the variable, it can be seen by the construct *** in column P. The symbol *** indicates that P (probability value) is less than 0.05 or below 5% (P<0.05).

c) Testing Variable Social Influence
From the results of the table below, it can be seen that the four constructs of the social influence variable have a significant relationship to the measured variables. Four constructs can be significant to the variable, it can be seen by the construct *** in column P. The symbol *** indicates that P (probability value is less than 0.05 or below 5% (P<0.05) From the results of the table below, it can be seen that the four constructs on the facilitating condition variable have a significant relationship to the measured variable. Four constructs can be significant to the variable, it can be seen by the construct *** in column P. The symbol *** indicates that P (probability value) is less than 0.05 or below 5% (P<0.05).

) Testing Variable Hedonic Motivation
From the results of the table below, it can be seen that the three constructs on the hedonic motivation variable have a significant relationship to the measured variables. Three constructs can be significant to the variable, it can be seen by the construct *** in column P. With the symbol **** indicates that P (probability value) is less than 0.05 or below 5% (P<0.05). Three constructs can be significant to the variable, it can be seen by the construct *** in column P. With the symbol *** indicates that P (probability value) is less than 0.05 or below 5% (P<0.05). Three constructs can be significant to the variable, it can be seen by the construct *** in column P. The symbol *** indicates that P (probability value) is less than 0.05 or below 5% (P<0.05). to the variable, it can be seen by the construct *** in column P. With the symbol *** indicates that P (probability value) is less than 0.05 or below 5% (P<0.05).

) Testing Value Behavioral Intention
From the results of the table below, it can e saw that three constructs on the behavioral intention variable have a significant relationship to the measured variable. Three constructs can be significant to the variable, it can be seen by the constructs *** in column P. The symbol *** indicates that P (probability value) is less than 0.05 or below 5% (P<0.05).

k) Testing Value Use Behavior
From the results of the table below, it can be seen that the three constructs in the user behavior variable have a significant relationship to the measured variables. Three constructs can be significant to the variable, it can be seen by the construct *** in column P. The symbol *** indicates that P (probability value) is less than 0.05 or below 5% (P<0.05) the goodness of fit test of the research model is an intermediate level of suitability.  ,046 2,215 *** Significant UB <---H ,110 ,054 2,223 *** Significant UB <---BI ,965 1,34 7,323 *** Significant

Hypothesis Testing
The research hypothesis test is used based on the research model that has been developed. Hypothesis testing aims to analyze the relationship between two interrelated construct variables.
From the parameterization results shown in table 5 below, it is obtained with a probability (P) value of 0.0 ** which means the P-value < 0.05 and it can be interpreted that the hypothesis H) is rejected and if the P-value > 0.05 then HO is accepted. So that the hypothesis with a significant value is found in the variable performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, habit and customer satisfaction with behavioral intention and facilitating conditions, habit and behavioral intention to use behavior. Meanwhile, the hypothesis with an insignificant value is found in the variable price value and service quality on behavioral intention.  The Hypothesis is rejected H7: Price Value - Behavioral Intention The hypothesis is rejected H8: Habit - Behavioral Intention The hypothesis is accepted H9: Habit - Use Behavior The hypothesis is accepted H10: Service Quality - Behavioral Intention The hypothesis is rejected H11: Customer Satisfaction ---> Behavioral Intention The Hypothesis is accepted

H12: Behavioral Intention - Use Behavior
The Hypothesis is accepted

Female Gender Moderator Test
From below the table, it can be seen that the gender variable for data that is not significant is found in hedonic motivation and price value on behavioral intention and also in the relationship between habit variables and behavioral use. It is explained that women more often use online transportation facilities on the grab and go-jek applications because they are easy to use and as daily necessities.

Table 20
Hypothesis Testing

6.Male Gender Moderator Test
From the results of the table below, it can be seen that the gender variable for data that is male which is not significant is found in effort expectancy, price value, and customer satisfaction on behavioral intention and also in the relationship of the facilitating condition, price value and customer satisfaction variables to behavioral intention and also which is not significant is found in the relationship between facilitating conditions and behavioral intention to use behavior.

Trimming
This process is carried out to eliminate the relationship between variables that do not have a significant effect. After eliminating each variable that does not have a significant effect, it will be tested again.
Based on table 23 below, the trimming test process is carried out by eliminating several variables that are not significant, the elimination is in the price value and service quality variables on behavioral intention.

Conclusion
Many studies have been conducted on the acceptance and use of technology to users using the unified theory of acceptance and use of technology 2 (UTAUT 2) model developed by Venkatesh et al (2012). In the study, researchers conducted a study using this model to see and analyze the relationship between variables in the acceptance and use of technology in online transportation on grab and go-jek applications.
There have 12 factors, which affect online transportation on grab and go-jek applications for the public. That is performance expectancy, effort expectancy, social influence, facilitating condition, hedonic motivation, price value, habit, service quality, customer satisfaction, behavioral intention, and use behavior. Base on this research using SPSS and SEM AMOS analysis that has 12 factors, which have to affect to influence customer satisfaction. The 12 factors are performance expectancy, effort expectancy, social influence, facilitating condition, hedonic motivation, price value, habit, service quality, customer satisfaction, behavioral intention, and use behavior.
After the researchers tested all the variables that affect the acceptance and use of online transportation for the grab and gojek application for the people in Bandung using the UTAUT 2 model.
Can be concluded in this research that between performance expectancy and behavioral intention has a significant influence with a probability value with a value of 0,0** which means that the P value < 0,05 hypothesis H 0 is accepted Between effort expectancy and behavioral intention has a significant influence with a probability value with a value of 0,0** which means that the P value < 0,05 hypothesis H 0 is accepted.
Between facilitating condition and use behavior has a significant influence with a value of 0,0** which means that the P value < 0,05 hypothesis H 0 is accepted.
Between hedonic motivation and behavioral intention has a significant influence with a probability value with a value of 0,0** which means that the P value < 0,05 hypothesis H 0 is accepted.
Between price value and behavioral intention does not have a significant effect with a probability (P) value of 0.311 which means that the P value > 0,05 hypothesis H 0 is rejected.
Between hedonic motivation and behavioral intention has a significant influence with a probability value with a value of 0,0** which means that the P value < 0,05 hypothesis H 0 is accepted.
Between habit and use behavioral has a significant influence with a probability value with a value of 0,0** which means that the P value < 0,05 hypothesis H 0 is accepted.
Between service quality and behavioral intention does not have a significant effect with a probability (P) value of ,174 which means that the P value > 0,05 hypothesis H 0 is rejected.
Between customer satisfaction and use behavior has a significant influence with a probability value with a value of 0,0** which means that the P value < 0,05 hypothesis H 0 is accepted.
Between behavioral intention and use behavior has a significant influence with a probability value with a value of 0,0** which means that the P value < 0,05 hypothesis H 0 is accepted.