https://dinastipub.
org/DIJEFA Vol.
No.
2, 2025
DOI: https://doi.
org/10.
38035/dijefa.
https://creativecommons.
org/licenses/by/4.
The Influence of Digital Marketing and Consumer Behavior on Purchase Decisions at Mega Akbar Regency Housing Naja Jessyka Maulani PutriA.
Ely SiswantoA.
Ita Prihatining WilujengA.
Program Studi Magister Manajemen Fakultas Ekonomi dan Bisnis.
Universitas Negeri Malang.
Malang.
Indonesia, naja.
2404138@students.
Program Studi Manajemen Fakultas Ekonomi dan Bisnis.
Universitas Negeri Malang.
Malang.
Indonesia, ely.
fe@um.
Program Studi Manajemen Fakultas Ekonomi dan Bisnis.
Universitas Negeri Malang.
Malang.
Indonesia, ita.
fe@um.
Corresponding Author: naja.
2404138@students.
Abstract: In today's digital era, marketing strategies in the property industry have undergone significant changes.
Digital marketing has become a primary tool for developers to reach potential buyers more easily and widely.
However, besides digital marketing strategies, consumer behavior also plays a crucial role in determining home purchase decisions.
Buying property is a major decision influenced by various factors, such as psychological, social, economic, and personal experiences.
This study aims to determine the extent of the influence of digital marketing and consumer behavior on home purchase decisions at Mega Akbar Regency Housing.
Using a quantitative method, this research involves 70 respondents who have completed a questionnaire.
The collected data is then analyzed using various statistical tests, including multiple linear regression, correlation, and significance tests with the help of SPSS.
The results indicate that digital marketing and consumer behavior significantly influence purchase decisions.
However, consumer behavior has a more dominant influence compared to digital marketing.
This means that while digital marketing strategies are highly effective in attracting potential buyers' attention, psychological factors, recommendations from others, and how consumers search for and compare information play a more decisive role in their final decision to purchase a home.
Keyword: Digital Marketing.
Consumer Behavior.
Purchase Decision INTRODUCTION The development of digital technology in recent years has transformed the way businesses market their goods and services.
To reach potential buyers more efficiently, digital marketing has become a dominant strategy in the property industry.
Property developers can increase sales conversion rates and attract customer attention by utilizing various online platforms such as social media, websites, email marketing, and paid advertisements.
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According to (Kotler, 2.
digital marketing enables businesses to interact directly with customers, build closer relationships, and enhance customer engagement in the decisionmaking process.
Consumer behavior and marketing strategies are crucial components in purchase decision-making.
Consumer behavior reflects how individuals make purchasing decisions based on various factors, including psychological, social, cultural, and economic (Goldberg & Groenewald, 2.
state that perception, motivation, and personal experiences with a product or service influence consumer behavior.
In the property industry, buyer behavior heavily depends on multiple factors, including location, price, facilities, developer reputation, and previous buyer reviews.
Since property purchases are long-term investments, they are among the most challenging decisions to make.
(Solomon et al.
, 2.
highlights that, in addition to rational factors such as location and price, home purchase decisions are also influenced by emotional factors such as comfort, security, and social status.
As a result, gaining a better understanding of consumer behavior and effective digital marketing techniques can help property developers enhance their competitiveness and attract more buyers.
METHOD
This study employs a quantitative research method with a total population of 70 The sampling technique used is purposive sampling, which involves selecting respondents deemed relevant to the research.
Data analysis is conducted with the assistance of SPSS software, utilizing several statistical tests to ensure the validity and reliability of the The validity test assesses the ability of the research instrument to accurately measure the variables under study.
According to (Sugiyono, 2.
validity refers to the extent to which an instrument measures what it is intended to measure.
This study employs the product-moment correlation test to evaluate the validity of the research instrument.
Additionally, the reliability test ensures that the measurement results are consistent.
(Sekaran & Bougie, 2.
state that an instrument can be considered reliable if repeated measurements yield similar results.
This study applies the CronbachAos Alpha test, where an instrument with a value above 0.
7 is deemed To analyze the relationship between variables, multiple linear regression is used to examine how two or more independent variables influence the dependent variable.
According to (Gujarati, 2.
multiple linear regression helps evaluate the simultaneous impact of independent variables on the dependent variable.
The regression equation applied in this study follows the formula: Y = a b1X1 b2X2 .
bnXn e.
Furthermore, multiple correlation analysis is conducted to examine the relationship among more than two variables.
(Pearson, 1.
explains that correlation measures the degree to which changes in one variable are associated with changes in another variable, with values ranging from -1 to 1, where higher values indicate stronger relationships.
The coefficient of determination (RA) test is also employed to determine the extent to which independent variables explain the dependent variable.
According to (Ghozali, 2.
an RA value close to 1 indicates a highly accurate model.
The coefficient of determination is expressed as a percentage, representing the proportion of variability in the dependent variable explained by the independent variables.
Additionally, the t-test is conducted to assess the partial effect of each independent variable on the dependent variable.
(Santoso, 2.
states that a significant t-test result indicates a strong correlation between an independent variable and the dependent variable.
This test involves comparing the calculated t-value with the table t-value and analyzing the significance of the p-value.
Lastly, the F-test is used to determine the overall significance of the regression model.
According to (Santoso, 2.
the F-test assesses whether all independent variables collectively influence the dependent variable.
A regression model is considered significant if the calculated F-value is greater than the table F-value.
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RESULTS AND DISCUSSION
Results of the Validity Test for the Digital Marketing Variable (X.
No.
Table 1.
Digital Marketing Variable Results Variable X1 R-Calculated R-Table Description Question 1 Valid Question 2 Valid Question 3 Valid Question 4 Valid Question 5 Valid Source: Processed Research Data, 2025 The results of the validity test indicate that all question items for the Digital Marketing variable (X.
have an R-calculated value greater than the R-table value .
This confirms that the research instrument used is valid in measuring Digital Marketing.
In other words, the questionnaire items accurately represent the factors within Digital Marketing that influence purchasing decisions Results of the Validity Test for the Consumer Behavior Variable (X.
No.
Table 2.
Consumer Behavior Variable Results Variable X2 R-Calculated R-Table Description Question 1 Valid Question 2 Valid Question 3 Valid Question 4 Valid Question 5 Valid Source: Processed Research Data, 2025 The validity test for the Consumer Behavior variable (X.
shows that all question items have an R-calculated value greater than the R-table value .
Therefore, all items in this instrument are valid for measuring consumer behavior.
This means that the questionnaire items accurately capture various aspects of consumer behavior, such as purchasing motivation, perception, and information-seeking habits.
Results of the Validity Test for the Purchase Decision Variable (Y) No.
Table 3.
Purchase Decision Variable Results Variable Y R-Calculated R-Table Description Question 1 Valid Question 2 Valid Question 3 Valid Question 4 Valid Question 5 Valid Source: Processed Research Data, 2025 The validity test results for the Purchase Decision variable (Y) indicate that all question items have an R-calculated value higher than the R-table value .
Therefore, the instrument used is valid for measuring purchase decisions.
This means that the questions posed to respondents accurately represent the factors influencing their decision to buy a house.
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Results of the Reliability Test Table 4.
Reliability Test Results Item CronbachAos Alpha Alpha Digital Marketing (X.
Consumer Behavior (X.
Purchase Decision (Y) Source: Processed Research Data, 2025 Description Reliable Reliable Reliable The reliability test results indicate that the CronbachAos Alpha values for Digital Marketing .
Consumer Behavior .
, and Purchase Decision .
exceed the threshold of 0.
This confirms that the research instrument is reliable.
It means that the responses provided by participants are consistent and dependable.
If the study were to be conducted again under the same conditions, the results would remain stable.
Results of Multiple Linear Regression Analysis Table 5.
Multiple Linear Regression Test Results Unstandardized Coefficients Standardized Coefficients Std.
Error (Constan.
Digital Marketing (X.
Consumer Behavior (X.
Source: Processed Research Data, 2025 Model Beta Sig.
Based on the regression analysis results, the regression equation obtained is Y = 0.
149XCA 0.
909XCC.
The coefficient values for Digital Marketing (X.
149 and Consumer Behavior (X.
909 indicate that Consumer Behavior has a more significant influence on Purchase Decision compared to Digital Marketing.
This means that while Digital Marketing strategies do affect purchasing decisions, factors related to consumer behaviorAisuch as information-seeking habits, motivation, and perceptionAiplay a more dominant role in determining home purchase decisions.
Results of Multiple Correlation Test Model R Square Table 6.
Multiple Correlation Test Results Adjusted R Std.
F Change Square Error of Square Change Estimate Source: Processed Research Data, 2025 Sig.
Change The obtained R value of 0.
997 indicates a very strong relationship between the Digital Marketing and Consumer Behavior variables on Purchase Decision.
This means that the more effective the Digital Marketing strategy and the more positive the Consumer Behavior, the higher the likelihood that consumers will decide to purchase a house at Mega Akbar Regency.
Results of the Coefficient of Determination Test Model Square Table 7.
Coefficient of Determination Test Results Adjusted R Std.
Error of R Square F Square the Estimate Change Change Sig.
Change 1229 | Page https://dinastipub.
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Source: Processed Research Data, 2025 The RA value of 0.
993 indicates that 99.
3% of the variation in Purchase Decision can be explained by Digital Marketing and Consumer Behavior, while the remaining 0.
7% is influenced by other factors not examined in this study.
This means that Digital Marketing and Consumer Behavior play a dominant role in shaping purchase decisions, whereas external factors such as economic conditions or government policies have a minimal impact.
t-Test Results Model X1 (Digital Marketin.
X2 (Consumer Behavio.
Table 8.
t-Test Results Unstandardized Coefficients Standardized Coefficients Std.
Error (Constan.
Source: Processed Research Data, 2025 Beta Sig.
Digital Marketing (X.
has a t-value of 2.
309 with a significance value of 0.
024, indicating a significant influence on Purchase Decision.
Consumer Behavior (X.
has a t-value of 13.
531 with a significance value of 0.
000, showing that Consumer Behavior has a greater influence on Purchase Decision compared to Digital Marketing.
This means that while Digital Marketing impacts Purchase Decision.
Consumer Behavior plays a more dominant role in determining whether an individual decides to buy a house.
Therefore, an effective marketing strategy should prioritize a deeper understanding of consumer behavior to enhance its effectiveness.
F-Test Results Model Regression Residual Total Table 9.
F-Test Results Sum of Squares df Mean Square F Source: Processed Research Data, 2025 Sig.
The F-test results show that the calculated F-value = 4898.
464 with a p-value = 0.
indicating that the regression model is statistically significant overall.
This means that Digital Marketing (X.
and Consumer Behavior (X.
collectively have a significant influence on Purchase Decision (Y).
In other words, the success of property marketing is not solely dependent on one factor, but rather a combination of effective digital marketing strategies and an in-depth understanding of consumer behavior.
The influence of Digital Marketing and Consumer Behavior on Purchase Decisions has been a central focus in various studies.
This research indicates that while Digital Marketing has a significant impact.
Consumer Behavior often plays a more dominant role.
These findings align with previous studies.
For instance, (Setiawan et al.
, 2.
found that Digital Marketing had a positive and significant impact on purchase decisions for bread and cakes at Malika Bakery.
However.
Consumer Behavior exerted a stronger influence on purchasing decisions.
This suggests that understanding consumer behavior, including preferences and shopping habits, is more crucial in influencing purchase decisions than digital marketing strategies alone.
Similarly, a study by (Alamsyah & Fikri, 2.
emphasized the mediating role of Consumer Behavior in the relationship between Digital Marketing and Purchase Decisions.
They found 1230 | Page https://dinastipub.
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that Digital Marketing significantly influenced Purchase Decisions through Consumer Behavior as a mediator.
This highlights the importance of considering how consumer behavior can mediate the impact of digital marketing strategies.
Moreover, (Abas, 2.
demonstrated that Digital Marketing positively influenced consumer decisions for certain products.
However, her study also indicated that other factors, including consumer behavior, played a crucial role in purchasing decisions.
This underscores the need for a comprehensive understanding of consumer behavior when designing effective marketing strategies.
Overall, the findings of this research align with prior literature, suggesting that while Digital Marketing plays an essential role, a deeper understanding of Consumer Behavior is key to influencing Purchase Decisions.
Therefore, effective marketing strategies should prioritize consumer behavior insights to achieve optimal results.
CONCLUSION
The findings of this study confirm that Digital Marketing and Consumer Behavior significantly influence the decision to purchase a house at Perumahan Mega Akbar Regency, with Consumer Behavior being the dominant factor.
Although digital marketing strategies are effective in attracting potential buyers, factors such as information-seeking habits, motivation, recommendations from others, and psychological aspects play a more significant role in the final purchasing decision.
Additionally, the analysis shows that 99.
3% of the purchasing decision can be explained by Digital Marketing and Consumer Behavior, while 0.
7% is influenced by other factors not examined in this study.
Therefore, a combination of effective marketing strategies and a deep understanding of consumer behavior can significantly enhance property sales opportunities.
REFERENCE