SCHOLARS: Jurnal Sosial Humaniora dan Pendidikan ISSN: 3047-8618 (Onlin.
| DOI: https://doi.
org/10.
31959/js.
Volume 03 .
No.
Desember 2025 .
Homepage: https://ejournal-polnam.
id/index.
php/JS/index The Influence of Generation ZAos Social Media Activity in Jambi City on Stock Market Trends: A Statistical Analysis Fatan Heti Anggraini1.
Sri Wahyu Ningsih2.
Muetia Apriliani3.
Akmalun Nisa4.
Feby Lestari5.
Herry Mulyono6.
Yossinomita Yossinomita7* Faculty of Management and Business.
Universitas Dinamika Bangsa *Corresponding author email: yossinomita.
saputra@gmail.
Abstract: Generation Z plays a significant role in shaping contemporary stock market trends, particularly through intensive use of social media.
In the digital era, social media functions as a key source of investment information and informal financial education for young investors.
This study analyzes the influence of Generation Z in Jambi City on stock market investment interest through social media engagement.
A quantitative approach was employed using data collected from 62 Generation Z respondents .
= .
through an online questionnaire distributed to university students using purposive sampling.
Data were analyzed using multiple linear regression with SPSS, supported by classical assumption tests.
The results show that Generation Z characteristics ( = 0.
p = 0.
, the role of social media in investment education ( = 0.
p = 0.
, and viral stock trends on social media ( = 0.
p = 0.
each have a positive and statistically significant effect on investment Among these factors, the educational role of social media has the strongest These findings indicate that Generation ZAos digital literacy and exposure to social media-based investment content substantially shape their investment behavior.
This study contributes to behavioral finance literature by highlighting the growing importance of social media in influencing young investors and offers practical implications for policymakers, financial educators, and market practitioners in developing effective digital-based financial literacy strategies.
Keywords: Generation Z.
Social Media.
Stock Market Trends.
Digital Investment Behavior.
Behavioral Finance.
INTRODUCTION
Generation Z, defined as individuals born between 1997 and 2012, has emerged as a dominant demographic in contemporary social media usage.
According to the final report of OPBEI .
, approximately 75.
10% of the combined Millennial and Generation Z population in Indonesia actively use social media, with Generation Z accounting for the highest proportion of usage (B.
Maharani & Hidayah, 2.
Social media platforms have become primary channels for influencers to disseminate information and encourage public engagement in various activities, including The proliferation of mobile applications has further facilitated investment companies in recommending stock buying and selling activities to users (Kusnandar et , 2.
Notably, a considerable number of retail investors are members of Generation Z, a cohort characterized by high internet dependency and susceptibility to the Lisensi Lisensi Internasional Creative Commons Attribution-ShareAlike 4.
Anggraini1.
Ningsih2.
Apriliani3.
Nisa4.
Lestari5.
Mulyono6.
Yossinomita7.
AuThe Influence of Generation ZAos Ay 49 phenomenon known as the Aufear of missing outAy (FOMO).
This aligns with KadellAos .
findings, as cited in Saputra & Aulia .
, which highlight that individuals aged 18Ae25 are particularly prone to internet addiction.
In this context.
FOMO becomes closely intertwined with Generation ZAos decision-making processes, including their investment behaviors.
This high level of digital engagement is further confirmed by data from the Indonesian Internet Service Providers Association (APJII), which reports that Generation Z holds a 51.
9% share of the national social media presence, with Instagram being the most frequently accessed platform (Nisa & Hidayati, 2.
The APJII survey, conducted from December 2023 to January 2024 with 8,720 randomly selected respondents across 38 provinces, underscores the widespread reach of Key Opinion Leaders (KOL.
in shaping online discourse.
Coupled with the increasing ease of accessing capital market information due to technological advancements, these factors have significantly influenced the investment behaviors of young investors.
In Jambi Province, this trend is particularly pronounced: between late 2020 and August 2021, individuals aged 18Ae25 became the majority of stock market investors, representing 47% of total Single Investor Identification (SID) accounts (Qotrunada & Hascaryani, 2.
These patterns suggest a potentially strong linkage between Generation ZAos social media engagement and their active participation in the stock market.
The importance of understanding this linkage is reinforced by prior research in investment decision-making and behavioral finance.
MuAoafi et al.
describe investment decisions as a complex process requiring comprehensive knowledge of multiple influencing factors.
While contemporary investment theories emphasize the role of information in guiding decisions, they also acknowledge that investment fundamentally entails deferring present consumption for future returns.
The ability to accurately assess risk plays a critical role in investment success.
however, investors often face difficulties in obtaining relevant and reliable information.
Such informational limitations provide fertile ground for the application of behavioral finance, which explores how psychological factors can lead investors to deviate from rational decision-making.
Fatmawati & Parulian .
emphasize two critical concepts within this framework: cognitive illusions and limits to arbitrage.
Cognitive illusions describe systematic biases in the way individuals process and interpret information, whereas limits to arbitrage refer to constraints that hinder the exploitation of market inefficiencies.
These tendencies, as also highlighted by Yustati & Harpepen .
, can significantly influence investment outcomes, often leading to market behaviors that diverge from classical economic predictions.
Although existing studies have contributed to a broader understanding of investment behavior, particularly through the lens of behavioral finance, they have yet to fully examine the specific role of Generation Z within localized contexts such as Jambi City.
Moreover, previous research has rarely incorporated measurable indicators of digital interaction, such as the volume and nature of social media activity, into analyses of investment behavior and market trends.
This gap highlights the need for an integrated approach that combines behavioral finance theory with empirical social media data.
Such an approach can offer deeper, more context-specific insights into how digitally connected young investors influence stock market dynamics.
SCHOLARS: Jurnal Sosial Humaniora dan Pendidikan.
Vol.
No.
Desember 2025 Figure 1 presents a conceptual flowchart illustrating the proposed relationship between Generation ZAos social media usage, exposure to investment-related content, behavioral finance factors, and their subsequent influence on stock market participation and broader market trends.
Source: AuthorAos preparation .
Figure1.
Flowchart: Influence of Generation Z in Jambi City on Stock Market Trends via Social Media Statistics METHOD This study employed a quantitative research approach to examine the influence of Generation Z on stock market investment interest through social media engagement.
Data were collected through an online questionnaire survey distributed to university students in Jambi City who belong to the Generation Z cohort.
The selection of university students as respondents was conducted using purposive sampling, with the main criteria being active social media use and basic exposure to investment-related The focus on university students is theoretically justified for several reasons.
First, university students represent one of the most digitally active subgroups of Generation Z, with high intensity of social media usage and frequent exposure to stock market discussions on platforms such as Instagram.
TikTok, and Twitter/X.
Previous studies have shown that students dominate online investment communities and are early adopters of digital investment platforms.
Second, students are at a critical stage of financial decision-making, where investment interest and financial literacy begin to develop, making them an appropriate population for analyzing emerging investor Third, using a relatively homogeneous group helps reduce variability caused by differences in income level and employment status, thereby allowing a clearer Anggraini1.
Ningsih2.
Apriliani3.
Nisa4.
Lestari5.
Mulyono6.
Yossinomita7.
AuThe Influence of Generation ZAos Ay 51 examination of behavioral and perceptual factors related to social media and investment The dataset was obtained from questionnaire responses administered in 2025.
Data analysis was conducted using the Statistical Package for the Social Sciences (SPSS), following procedures outlined in Wartabone et al.
The analysis using multiple linear regression, supported by classical assumption tests, namely validity, reliability, normality, multicollinearity, and heteroscedasticity tests, to ensure the robustness of the regression model.
The final sample consisted of 62 respondents .
= .
Although the sample size is relatively small, it is methodologically acceptable for exploratory quantitative research employing multiple linear regression, particularly when the population under study is specific and well-defined.
With three independent variables, the sample meets the minimum requirement suggested in regression analysis, which recommends at least 15Ae20 observations per independent variable.
Nevertheless, the authors acknowledge that the limited sample size may constrain the generalizability of the findings beyond Generation Z students in Jambi City.
Therefore, the results should be interpreted as context-specific empirical evidence, and future studies are encouraged to use larger and more diverse samples to enhance external validity.
The characteristics of the respondents were derived from the completed questionnaires and are summarized as follows.
Gender Table 1.
Gender Distribution of Respondents No.
Gender Number of Respondents Female Male Total Percentage (%) As shown in Table 1, the total number of respondents was 62, with the majority being female .
individuals or 69.
4% of the total sampl.
Male respondents comprised 19 individuals or 30.
These figures indicate that female participation in this study was substantially higher than that of males.
Age No.
Table 2.
Age Distribution of Respondents Age Group Number of Respondents Percentage (%) 18 years 18Ae25 years 26Ae30 years >30 years Total Table 2 presents the age distribution of respondents.
The largest proportion belongs to the 18Ae25 age group, with 41 respondents .
1%), followed by those under 18 years of age, with 13 respondents .
0%).
Respondents over 30 years old accounted for 8 individuals .
9%), while there were no respondents in the 26Ae30 age group.
SCHOLARS: Jurnal Sosial Humaniora dan Pendidikan.
Vol.
No.
Desember 2025 This distribution confirms that the stock market trend in Jambi is primarily driven by Generation Z, particularly those aged 18Ae25 years (Nasution et al.
, 2.
To enhance methodological clarity and transparency, the operational definitions of variables used in this study are explicitly presented in Table 3.
Variable Generation Z Characteristics Role of Social Media in Investment Education Viral Stock Trends on Social Media Investment Interest Table 3.
Operational Definition of Variables Code Operational Indicators Definition Digital Intensity of XCA behavior and social media responsiveness use, interaction of Generation Z toward stock information on responsiveness social media to market The extent to Exposure to XCC which social media serves as a source of of investment knowledge and Influence of Exposure to XCE trending or viral stock viral stockdiscussions, related content influence of on investment motivation to Individual Desire to intention and willingness to intention to invest in the stock market readiness to Measurement Scale Likert Scale .
Ae.
Likert Scale .
Ae.
Likert Scale .
Ae.
Likert Scale .
Ae.
RESULTS Validity Test Results This type of test is part of statistical techniques aimed at assessing the extent to which an instrument can measure the aspects it is intended to measure.
Validity is a crucial Anggraini1.
Ningsih2.
Apriliani3.
Nisa4.
Lestari5.
Mulyono6.
Yossinomita7.
AuThe Influence of Generation ZAos Ay 53 element in the measurement process because a valid instrument can produce accurate and reliable data.
In a study, validity is typically tested on measurement instruments such as questionnaires or scales.
The primary purpose of this test is to ensure that the instrument truly measures the variable or concept of interest with a high degree of accuracy (Qotrunada & Hascaryani, 2.
This process is essential for ensuring the quality and credibility of the research The measurement criteria are:
If the calculated r value > r table, then the item is valid.
If the calculated r value < r table, then the item is not valid.
The results of the validity test for each variable used in this research are as follows:
Table 4.
Validity Test Results Variable Influence of Generation Z on the Stock Market through Social Media (X.
Role of Social Media in Investment Education and Understanding (X.
Trends of Viral Stocks on Social Media (X.
Preference for Investment Information and Content (Y.
Ethics and Regulation of Stock Content on Social Media (Y.
Indicator X1.
X1.
X1.
X2.
X2.
X2.
X3.
X3.
Y1.
Y1.
Y2.
Y2.
Y2.
Calculated 0,4555556 0,5534722 0,5423611 0,4784722 0,5166667 0,4479167 0,5444444 0,5513889 0,5791667 0,5090278 0,4326389 0,4500000 0,5194444 Table 1,7361111 1,7361111 1,7361111 1,7361111 1,7361111 1,7361111 1,7361111 1,7361111 1,7361111 1,7361111 1,7361111 1,7361111 1,7361111 Significance Remarks Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid The results in Table 4.
from the validity test indicate that all questionnaire items are This implies that all indicators (X1.
X2.
X3, and Y) effectively measure the intended variables.
The calculated r-values for each item exceed the r-table value at 01 significance level.
These findings confirm that the data used in this study are of high quality (Abdullah et al.
, 2.
Reliability Test Results The reliability test aims to ensure that the research instrument .
demonstrates an adequate level of internal consistency in measuring the intended In this study, reliability was assessed using the CronbachAos Alpha method.
A variable is considered reliable if its CronbachAos Alpha value exceeds 0.
Variable Table 5.
Reliability Test Results CroncbachAos Alpha
0,8153
0,8319
0,7722
0,7729
0,7785
Results Reliable Reliable Reliable Reliable Reliable SCHOLARS: Jurnal Sosial Humaniora dan Pendidikan.
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Desember 2025 As presented in Table 5.
, all variables obtained CronbachAos Alpha values greater This indicates that the questionnaire used in this study possesses good internal consistency and is therefore suitable for data collection.
Normality Test Results The normality test aims to determine whether the data for the two variables are normally distributed.
This test serves as one of the prerequisites or assumptions before performing simple linear regression analysis.
Table 6.
Normality Test Results: One-Sample Kolmogorov-Smirnov Test Unstandardized Residual Mean Normal Parametersa,b Std.
Deviation Absolut Most Extreme Positive Differences Negative Test Statistic Asymp.
Sig.
-taile.
c Sig.
Monte Carlo Sig.
-taile.
e Confidence Interval Lower Bound Upper Bound According to Table 6.
, if the Asymptotic Significance .
-taile.
value is greater than 05, the data are considered normally distributed.
if it is less than 0.
05, the data are considered non-normal.
The result shows 0.
200 > 0.
05, indicating that the data are normally distributed.
Therefore, the normality assumption for regression analysis has been met.
Multicollinearity Test Results The multicollinearity test is conducted to evaluate whether there is a strong relationship or high correlation among the independent variables in the regression An ideal regression model should not exhibit multicollinearity, meaning that the independent variables are not highly correlated.
Variable 1 X2 Table 7.
Multicollinearity Test Results Collinearity Statistics Tolerance VIF Anggraini1.
Ningsih2.
Apriliani3.
Nisa4.
Lestari5.
Mulyono6.
Yossinomita7.
AuThe Influence of Generation ZAos Ay 55 Multicollinearity can be assessed using two indicators:
Tolerance value Ae a Tolerance value O 0.
10 indicates multicollinearity.
Variance Inflation Factor (VIF) Ae a VIF value Ou 10 indicates multicollinearity.
The results in Table 7.
show that all Tolerance values are greater than 0.
10 and all VIF values are less than 10.
Therefore, it can be concluded that no symptoms of multicollinearity are present in the model.
Heteroskedasticity Test Results The heteroskedasticity test aims to determine whether the regression model has unequal variance of residuals across observations.
Heteroskedasticity occurs when the variance of the residuals differs from one observation to another.
Table 8.
Heteroskedasticity Test Results Unstandardized Standardized Coefficients Coefficients Variable Std.
Error Beta (Constan.
Dependent Variable: ABS_RES Sig.
The results indicate that no heteroskedasticity is detected, as all variables have significance values greater than 0.
This confirms that the regression model meets the homoscedasticity assumption.
DISSCUSIONS
The multiple linear regression analysis produced the following equation:
ycU = 0.
271 XCA 0.
350 XCC 0.
298 XCE
where Y represents investment interest.
XCA denotes Generation ZAos characteristics.
XCC refers to the role of social media in investment education, and XCE indicates viral stock trends on social media.
All coefficients are statistically significant at the 5% level, demonstrating that each factor contributes positively and meaningfully to Generation ZAos interest in stock market investment.
The first factor.
Generation ZAos characteristics (XCA), has a regression coefficient of 271, a t-statistic of 2.
659, and a Sig.
value of 0.
This indicates a significant and positive influence on investment interest.
The results suggest that Generation ZAos active engagement with social media facilitates the rapid dissemination of stock market Their digital proficiency enables them to access, share, and respond to market-related news more efficiently, thereby fostering greater participation in stock These findings align with Pelawi & Suliati .
, who highlighted that the SCHOLARS: Jurnal Sosial Humaniora dan Pendidikan.
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No.
Desember 2025 increasing investment interest among Generation Z brings positive prospects for stock market participation.
Furthermore, the role of social media in investment education and awareness (XCC) emerges as the most influential variable, with a regression coefficient of 0.
350, a tstatistic of 3.
176, and a significance value of 0.
This result highlights the critical role of social media as an informal financial education platform, particularly given that Generation Z constitutes its largest user segment.
Educational investment contentAisuch as tutorials, market insights, and experiential sharingAican be presented in interactive and engaging formats, thereby improving financial literacy and supporting informed investment decision-making.
This finding supports Maharani & Hidayah .
, who found that social media significantly influences investment interest by offering accessible and appealing learning resources.
Viral stock trends on social media (XCE) also exhibit a significant positive effect on investment interest, with a regression coefficient of 0.
298, a t-statistic of 2.
421, and a significance value of 0.
Viral investment narratives can rapidly shape market perceptions, stimulate enthusiasm, and encourage young investors to participate in the stock market, often within a short period.
This result aligns with Maharani et al.
who observed that the integration of stock market activities and social media platforms intensified during the COVID-19 pandemic.
The emergence of online investment communities during lockdown periods reinforced the role of viral content in driving engagement, and this influence continues even in the post-pandemic period.
However, despite its positive impact, viral stock trends also present potential negative implications that warrant critical consideration.
The rapid spread of investment-related content on social media may encourage speculative behavior, herd mentality, and impulsive decision-making among Generation Z investors, particularly those with limited financial experience (Fitri & Hariyanto, 2.
Viral stock recommendations are often driven by popularity rather than fundamental analysis, increasing the risk of misinformation, market volatility, and short-term price distortions.
In extreme cases, this phenomenon may expose young investors to financial losses and undermine long-term investment sustainability.
Therefore, while viral trends can stimulate initial investment interest, they also highlight the importance of strengthening financial literacy, critical evaluation skills, and regulatory oversight to ensure that social media-driven investment activities contribute positively to market stability and investor Overall, these findings demonstrate an interconnected relationship between Generation ZAos digital characteristics, the educational role of social media, and the influence of viral stock trends.
Together, these factors form a dynamic ecosystem in which information dissemination, learning processes, and social influence interact to shape investment interest.
Nonetheless, the results also suggest that maximizing the benefits of social media in investment contexts requires balancing its educational potential with adequate risk awareness and responsible investment behavior among young investors.
CONCLUSION
The findings of this study demonstrate that Generation Z in Jambi City plays a pivotal role in shaping stock market trends, primarily through their active use of social Anggraini1.
Ningsih2.
Apriliani3.
Nisa4.
Lestari5.
Mulyono6.
Yossinomita7.
AuThe Influence of Generation ZAos Ay 57 media platforms such as Instagram.
TikTok, and Twitter/X.
The regression results confirm that Generation ZAos characteristics (XCA), the educational role of social media (XCC), and viral stock trends (XCE) each have a significant and positive influence on investment interest, with the educational role of social media emerging as the most influential factor.
Generation ZAos digital proficiency enables rapid access to and dissemination of stock market information, while educational content on social media platforms enhances their financial literacy and awareness of investment opportunities.
Furthermore, viral stock trends act as powerful catalysts that can quickly influence market sentiment and investment behavior among young investors.
These findings are consistent with previous studies indicating that social media not only facilitates information sharing but also amplifies investment enthusiasm among Generation Z.
In the context of Jambi City, the interaction between digital engagement, financial education, and trend-driven behavior positions Generation Z as an important driving force in contemporary stock market To strengthen the positive influence of Generation Z on stock market development, local government institutions and educational organizations in Jambi City should focus on improving financial literacy among young people through structured and engaging Programs such as investment workshops, seminars, and training sessions focused on smart investing and fundamental stock market principles are essential to ensure that investment decisions are not based solely on viral trends or influencer recommendations, but are supported by sound financial analysis and risk awareness.
In addition, securities companies, financial institutions, and market research organizations are encouraged to actively monitor social media trends to better understand the investment preferences and behavior of young investors.
By integrating traditional market data with real-time social media analytics, these institutions can design targeted educational campaigns, develop relevant investment products, and foster a more informed, rational, and resilient Generation Z investor community.
Despite the meaningful findings, this study has several limitations.
First, the research sample is limited to Generation Z investors in Jambi City, which may restrict the generalizability of the results to other regions with different socioeconomic and cultural Second, this study focuses only on three independent variablesAi Generation Z characteristics, the educational role of social media, and viral stock trendsAiwhile other potential factors such as income level, risk tolerance, psychological biases, and peer influence were not examined.
Third, the use of a cross-sectional research design captures investor behavior at a single point in time, which may not fully reflect changes in investment behavior over longer periods or during different market Future studies are recommended to expand the scope of research by including a broader geographic area and a larger, more diverse sample to improve the generalizability of the findings.
Additionally, future research may incorporate other relevant variables such as behavioral finance factors, financial risk perception, influencer credibility, and technological adoption in investment platforms.
Longitudinal studies are also suggested to better capture changes in Generation ZAos investment behavior over time, particularly in response to market volatility and evolving social media dynamics.
Qualitative approaches, such as interviews or focus group discussions, may further SCHOLARS: Jurnal Sosial Humaniora dan Pendidikan.
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Desember 2025 enrich understanding of the motivations and decision-making processes behind Generation ZAos investment activities.
REFERENCES