1. Methodology 1.1 Data Collection This study employed the quantitative method. 400 questionnaires were distributed to three public universities located in Kelantan namely Universiti Malaysia Kelantan (UMK), Universiti Teknologi MARA (UiTM) and Universiti Sains Malaysia (USM). The data analysis included 357 complete responses out of 400 total respondents. Table 1 shows that most of the samples were female (55.5%). Most of the respondents were from Universiti Malaysia Kelantan representing 54.3%. Furthermore, 44% of the respondents studied in their final year, Year 4. Most of them (31.1%) came from East Coast Region. Table 1 also indicated that most university students started to use cashless financial transactions during Pandemic Covid-19 which is in the Year 2020. Table 1. Demographic Profile.

Respondent Profile	Classification	Frequency	Percentage
Gender	Male	159	44.5
Female	198	55.5
University	UMK	194	54.3
UiTM	129	36.1
USM	34	9.6
Year	Year 1	50	14.0
Year 2	76	21.3
Year 3	74	20.7
Year 4	157	44.0
State	Northern Region	71	19.9
East Coast Region	111	31.1
Central Region	70	19.6
Southern Region	73	20.4
Sabah and Sarawak	32	9.0
Starting using cashless financial transaction	2020 - 2021	194	54.7
2018 - 2019	94	26.3
2016 - 2017	53	14.5
2014 - 2015	16	4.5

1.2 Research Questionnaire Design The questionnaire designed for the present study was designed in two languages, namely Malay and English. A Likert scale with five possible responses"strongly disagree" to "strongly agree"was employed. Three sections make up the questionnaires. Questions about demographics are in Section A. Section B measured the intention to use cashless financial transactions, representing the dependent variable. While Section C measured convenience, security, social influence and speed which were categorized as independent variables. 2 Result and Discussion 2.1 Descriptive Statistics of Variable The descriptive data shown in Table 2 indicate that speed has the highest mean value, 4.43, while the social impact has the lowest mean value, 3.83. Most respondents agreed with the statements made in each item based on each variable, as shown by the fact that all questions for each construct had a mean score above 3.00. All the variables had standard deviations that were less than 1.00, indicating a small distribution of mean values. It also suggests that respondents' perceptions of this part of the study are consistent. Table 2. Descriptive Statistics on the Variable (N=357)

Observation	Mean	Std. Dev	Min	Max
Convenience	357	4.33	0.58	1	5
Security	357	4.20	0.75	1	5
Social Influence	357	3.83	0.96	1	5
Speed	357	4.43	0.57	1	5
Intention to Use Cashless Financial Transaction	357	4.33	0.61	1	5

2.2 Multiple Linear Regression Analysis In this study, convenience, speed, security, and social impact were employed as independent factors in multiple linear regression to predict the outcome of intentions of cashless financial transactions. Multiple linear regression is the common technique to be employed if the set of independent variables is two or more variables related to one continuous dependent variable (Abdullah et al., 2020). Four constructs which consist of convenience, speed, social influence and security as independent variables were analysed concurrently to examine the behavioral intention to use cashless in the financial transaction as a dependent variable. The results of multiple linear regression analysis are shown in Table 3, where the R-value of 0.695 denotes a strong correlation relationship. Additionally, in statistics, the coefficient of determination known as R Square (R2) in the analysis model describes the proportion of variation in the dependent variable that is predictable from the independent variables. Based on the results in Table 3, the R2 value by the multiple linear regression model is 0.483, which indicates that 48% of the behavioural Intention to Use Cashless in Financial Transaction variance is from Convenience, speed and social influence and the remaining (52%) is from other factors that are not taken into consideration in this study. Table 3. Multiple Linear Regression Analysis

Variable	Beta Value	Std. Error	t-value	Sig	R	R square
Constant	0.655	0.230	2.843	0.005	0.695a	0.473
Convenience	0.557	0.052	10.635	0.000
Social Influence	0.023	0.027	0.835	0.004
Security	0.039	0.044	0.874	0.383
Speed	0.229	0.056	4.072	0.000

As shown in Table 3, convenience obtained the highest eta value () at 0.557, followed by speed ( = 0.229), security ( = 0.039), and social influence ( = 0.023). The eta values depicted that convenience and social influence are the strongest and least factors influencing intention to use cashless in financial transactions among university students respectively. Based on Table 4, convenience, social influence and speed offer a p-value below 0.05. While security depicts the p-value above 0.01. Therefore, convenience, social influence and speed significantly influenced the intention of university students to use cashless in a financial transaction. Whereas security did not significantly influence the intention of university students to use cashless in financial transactions. According to Abdullah et al. (2020), most previous studies highlighted that convenience, speed and social influence were major factors that play a significant role in influencing users to use cashless financial transactions. This study also found the same finding and was supported by Rahadi et al. (2020). However, this study also found that security is not a significant factor in using cashless financial transactions among UMK students. The finding was supported by Jumba and Wepukhulu (2019) and Abdullah et al. (2020). In this study, it might be possible because most of the students stayed in a hostel at the campus. In addition, the crime rate around these universities is not so high. Therefore, they are not exposed to criminal issues like being roped or others. Hence, security is not a significant factor that led university students to use cashless in financial transactions. Question: 1)What kind of research design was used for this article? Justify your answer