make purchases of their products. In this context, a business needs to gain trust to attract customers in the

transaction process. This research aims to examine the relationship between the influences of Security and

Privacy on the Trust of Gen Z in Indonesian E-commerce. The research method employed is quantitative. This

study involves 400 respondents who are Gen Z consumers (born between 1997-2012) frequently engaging in

transactions through e-commerce platforms. The data processing utilized the Partial Least Square - Structural

Equation Model (PLS-SEM). The results indicate that Security and Privacy each have a positive and significant

influence on Trust.

Development and growth in E-Commerce have

been remarkable and rapid since Internet access

became more widely available in the mid-1990s. In

2019, in the United States, the market share for E-

Commerce reached 11.1%, experiencing a 5.8%

increase from 2013, [1]. This percentage figure is

estimated to rise to 13.7% in 2021. Conversely, the

market share for E-Commerce in Indonesia stands

at only 3% of total retail, [2]. Considering the

196.47 million by 2023. In the current digital era,

the online realm has become a mandatory aspect

for organizations and businesses. This is evident in

companies' endeavors to influence especially

teenagers to buy their products, with a

consumer confidence and loyalty due to the

positive behavior of the seller, [5]. The function of

trust in E-Commerce transactions is to facilitate

business transactions between two parties with no

prior experience in mutually beneficial dealings.

Confidence not only reduces perceived risks but

also enhances the perceived value or gain for

consumer intent to transact, [7], and is crucial in

achieving outcomes as expected and satisfying in

online transactions, [8]. Various studies have

shown that trust positively influences online

purchase intentions, with higher levels of consumer

trust correlating with higher levels of consumer

purchase intent, [8]. Furthermore, trust in e-reviews

positively impacts choices, [9]. Trust also

influences customer loyalty and creates an intent to

repurchase. Customers will only make repurchases

from sellers they know and trust, [10].

business, the level of customer trust remains low.

IDC and Microsoft, in Microsoft Indonesia 2019,

conducted a study titled "Understanding Consumer

digital services.

consumer distrust. There are five factors

influencing Consumer Trust in the use of e-

commerce. First is the issue of Security voiced by

59% of respondents. This is followed by concerns

about Privacy (57%). After that, customers are also

worried about reliability (53%), ethics (42%), and

compliance (29%). This study will focus on

confirming the influence of two factors, Security

privacy depend on how familiar they are with a

evolve as global online sales are estimated to reach

21.8% by 2024, [19]. E-commerce, according to

[20], can be defined as the place where the

exchange of commodities occurs online between

individuals using the internet, along with the

transmission of data between electronic devices

using the internet. The growth of E-Commerce can

be seen in how modern economies are increasingly

[15].

trust can lower the perceived risk of the transaction.

It holds higher importance in e-commerce.

Therefore trust should be built. A study from [25],

showed how trust is influenced by security,

privacy, guarantees, customer service, website

information, and laws regulating consumer

protection in e-commerce. The role of security in

impacts trust. The study involved 403 respondents

from groups with knowledge of technology and

coding and groups with little technology

knowledge. The results showed that privacy has a

positive impact on the level of trust. Another study

influence of privacy practices to trust is further

second hypothesis of this study is:

H2: Privacy has a positive and significant effect on

Gen Z's trust in Indonesian E-commerce.

The method employed in this research is a survey

formulated questions designed to record

respondents' answers in the closest alternative form

and collect a large amount of quantitative data,

[28].

distribution technique focused on gathering

information from members of the population

willing to provide their responses, [28]. The

distribution of the questionnaire questions uses

Google Forms, consisting of sections that include:

Validity serves the purpose of assessing how well

or good a technique, instrument, or measurement

process captures a specific concept, [28]. The

Average Variance Extracted (AVE) can be utilized

to evaluate the validity of convergence for each

measure, and its metric aims to assess the

construction of the validity of such convergence.

construct and the indicator variable considered

outside the formative construct. The general rule is

that outer loadings should be 0.708 or higher. In

research, values below 0.708 are often encountered,

especially when using newly developed scales.

When removing indicators with outer loadings

below 0.708, caution must be exercised in

examining the effects of removal, particularly on

composite reliability, such as construct content

validity, [30].

proofs of discriminant validity. According to the

Fornell-Larcker criterion, the square root of the

AVE for each construct must be greater than the

correlation with other constructs. The evaluation

Reliability, with a threshold of greater than 0.7 for

confirmatory research and 0.6-0.7 for explanatory

research [30].

Collinearity, a condition of strong linear

relationships between independent variables, can

disrupt PLS analysis. Commonly used methods

such as Variance Inflation Factor (VIF), Tolerance,

and Condition Number are employed. A VIF value

employed in this study, provides a nuanced view,

with values around 0.75, 0.50, or 0.25 indicating

category. Thus, it can be concluded that this

research falls under the moderate fit.

Based on Table 3, the results for Security towards

Trust are 0.425, and Privacy towards Trust is 0.452.

These values have positive figures and are close to

+1. Therefore, the conclusion is that Security

H1, Security - Trust, is supported as it has a T-

Statistics value greater than 1.66, specifically

8.109, and a p-value less than 0.05, specifically

consumer privacy systems as a strategic step to

build consumer trust in their e-commerce

platforms.

impact of security and privacy on trust, companies

can direct their efforts to optimize the user

researchers consider additional factors that may

influence consumer trust levels in the e-commerce

understanding the complexity of consumer trust

and can provide valuable insights for the

development of future business strategies.

of research to variables that have been less

investigated regarding their impact on trust levels.

By delving into these factors, researchers can

provide a more comprehensive understanding of

the dynamics of trust in the e-commerce context.

articulated among varied consumer segments.

[9] K. L. Sidali, S. Holger, and A. Spiller, “The

[10] S. Bhattacharya, R. P. Sharma, and A.

[12] M. S. Alzaidi and G. Agag, “The role of

[14] G. A. Putri, A. K. Widagdo, and D.

[16] N. Shanmugavel and M. Micheal,