https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 DOI: https://doi.
org/10.
38035/dijefa.
https://creativecommons.
org/licenses/by/4.
Environmental Awareness.
Knowledge.
Product Quality and Green Product Purchase Decisions Achmad Tarmizi1*.
Muhamad Al Faruq Abdullah2.
Wenny Desty Febrian3.
Didin Hikmah Perkasa4 Universitas Dian Nusantara.
Jakarta.
Indonesia.
Universitas Paramadina.
Jakarta.
Indonesia.
Universitas Paramadina.
Jakarta.
Indonesia.
Universitas Paramadina.
Jakarta.
Indonesia.
Corresponding author: achmad.
tarmizi@undira.
Abstract: This research aims to determine the positive influence of environmental awareness, knowledge and product quality on decisions to purchase green products: Case Study of Consumers in the West Jakarta Region.
Data collection in this research was carried out using a survey method by distributing 150 questionnaires using the sampling technique used.
In this research, accidental sampling technique was used.
The accidental sampling technique is the withdrawal of a sample size if the exact population size is not known.
This research uses multiple regression analysis with the SPSS version 26 program as a tool for processing and analyzing research results.
The results of the hypothesis test show that the Environmental Awareness variable has a significant effect on Green Product Purchasing Decisions.
The knowledge variable has a significant effect on Green Product Purchasing Decisions.
The product quality variable has a significant effect on green product purchasing decisions.
And the variables environmental awareness, knowledge and product quality together .
have a significant effect on green product purchasing decisions.
Keywords: Environmental Awareness.
Knowledge.
Product Quality.
Green Product Purchasing Decisions INTRODUCTION The natural environment and social environment cannot be separated from human life as social creatures.
Natural resources are used by humans to meet their needs, such as getting clothing, food and shelter.
However, sometimes when utilizing natural resources, humans do not use them wisely, which can cause various problems, one of which is environmental damage.
Environmental damage is a problem for all countries.
This is because environmental damage will have an impact on the ecosystem within it.
For example, deforestation carried out by humans in an effort to meet their needs, such as obtaining raw materials for paper and chairs, has reduced the number of trees, this of course has an impact on reducing oxygen production and carbon dioxide filters.
In addition, according to the Indonesian Ministry of Environment Auforest and land damage also causes water systems to be disrupted.
abundant in the rainy season 4871 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 and dry in the dry seasonAy1.
According to data from Greenpeace, around 1.
8 million105 ha of forest loss occurred on land within one or more concessions.
The forest damage that occurs is mainly caused by forest fires, illegal logging, forest mining and the function of forests being converted into industrial forest plantations and large-scale plantations as well as illegal logging by irresponsible parties, causing unsustainable forests.
This environmental damage causes global warming.
Global warming is an event where the earth's temperature increases, erratic weather, storms and drought occur.
This event is a real impact that occurs as a result of global warming on earth.
AuGlobal warming is also changing the landscape of life on earth and killing off many speciesAy3.
Global warming is caused by several factors, namely carbon dioxide emissions from motorized vehicles and factories, forest destruction and methane emissions from the agricultural and livestock sectors and also human lifestyle.
Apart from that, waste that is not processed properly will also pollute water and soil which will produce methane gas which will have an impact on climate change and an increase in temperature.
This climate turmoil will affect all aspects of human life if it is not addressed.
Figure 1 and Figure 2 explain that amidst the challenges and evolution of understanding regarding Environmental.
Social and Governance (ESG) in 2023, a maturity phase will occur where ESG is no longer just a trend, but has become an essential element in business strategy.
The decline in interest in ESG seems more a healthy market adjustment than a marker of the end of ESG itself.
More and more countries are creating new regulations that support ESG transparency and accountability.
For example, the development of regulations from the US (Securities and Exchange Commissio.
SEC and EU (Corporate Sustainability Reporting Directiv.
CSRD underscores the importance of stricter and more standardized ESG reporting.
Corporate responses to these changes signal a transition towards ESG practices that are more integrated and have a direct impact on business operations.
Figure 1.
Trends in Environmental Issues (ESG) in 2023 and Predictions for 2024 in the Indonesian Business Context Source: https://id.
com/pulse/tren-isu-lingungan-esg-tahun-2023-dan-preksi-2024-dalam-feryanto-keekc Figure 2 Green Marketing: Goals.
Challenges.
Strategies and Examples Source: https://pasla.
id/green-marketing-besar-tantangan-strategi-dan-example/ 4872 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 The existence of issues regarding the environment causes awareness among the 105 and government to care more about the environment by carrying out efforts that can reduce environmental damage.
For example, several months ago the Indonesian government established a policy to charge a fee for every plastic bag used by consumers when consumers shop at minimarkets.
The government did this because the government saw the high use of plastic bags in Indonesia which would have an impact on environmental damage.
In fact.
Indonesia is ranked 2nd as the country that produces the most plastic bag waste in the world6.
Not only the government, society is now starting to promote communities that focus on improving the quality of the environment, such as Green Peace and Earth Hour.
In Indonesia there are also many social communities that focus on environmental issues such as the Indonesian Plastic Bag Diet.
Hilo Green Community and the Indonesian Green Youth Coalition (KOPHI).
These environmental issues are increasingly changing people's consumption patterns in consuming products.
which is environmentally friendly.
"Today's consumers show their concern for environmental and social issues so they also expect the same from corporations, therefore brands that are committed to sustainability will have a place in the hearts of Environmental awareness is owned by someone who thinks about environmental consequences and someone who thinks about environmental consequences is influenced by their social awareness, as according to Webster (Junaedi, 2.
, consumer social awareness is a consumer who remembers the general consequences of personal consumption or efforts to utilize purchasing power in social problems in decisions.
purchases by evaluating the impact of their consumption on social issues.
So it can be said that if environmental consequences are deemed important to consumers, consumers will buy environmentally friendly products.
Motorized vehicles that can be said to be environmentally friendly vehicles are electric Electric vehicles seem to have become a hot topic of conversation in the automotive and energy world.
The fact that this vehicle no longer uses fuel oil (BBM) makes people see it as a solution to air pollution which has become a problem from year to year (ITSMediaCenter.
According to Kumara .
, electric vehicles are an important solution to overcome problems related to environmental pollution, limited and decreasing supplies of conventional fuel, and global warming due to the high use of fossil-based fuels in transportation equipment.
Currently, the phenomenon of global warming It is increasingly understood that human efforts are required to significantly reduce carbon emissions into the earth's atmosphere.
Electric vehicles are a very important solution in efforts to save the environment and sustainably manage natural resources.
This is possible because the technology supporting electric vehicles has developed to such an extent that electric vehicles have been successfully created that are reliable, economical and have the same level of comfort as conventional motorized vehicles and even electric vehicle technology has better operating specifications compared to conventional motorized vehicles (Kumara, 2.
Electric vehicles currently being developed, such as Gesits.
Uwinfly.
Volta.
Tesla, and Hyundai, are battery-based electric motorized vehicles (KBLBB) which will use electricity from charging in various places.
Without using a combustion engine, of course KBLBB will not produce Carbon Monoxide emissions like the motorized vehicles we use today.
With electric vehicles, of course emission levels will be reduced.
Pollution will only come from power plants and not from vehicles directly.
This will certainly have a positive effect on air pollution levels in densely populated areas.
So that the level of public health will increase.
(ITSMediaCenter, 2.
Based on the results of the Katadata Insight Center (KIC) survey "Katadata Consumer Survey on Sustainability" conducted on 3,631 consumers in 2021 in the databox, it shows that environmentally friendly vehicles are the least purchased environmentally friendly products, 4873 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 namely of 3,631 people, only 301 people who purchased an environmentally friendly vehicle in the last 1 year.
This shows that public interest in buying environmentally friendly vehicles is still small .
ataboks, 2.
According to the Indonesian Electric Motorcycle Association .
n theconversation.
, sales of electric motorbikes from 2019-2022 only reached 30,837 units, while fuel-based vehicles in the same period sold 29 million units.
This figure shows there is little interest in buying electric motorbikes in Indonesia.
It could be that this is closely related to the perception of the Indonesian people who are still reluctant to switch to electric motorbikes .
com, 2.
Based on the explanation and study presented above, the researcher obtained an illustration that environmental awareness, knowledge and product quality influence decisions to purchase green products or environmentally friendly products, amidst competition in environmentally friendly industries, so the researcher chose these variables.
Apart from that, this variable is very interesting to research so that it will be seen whether the independent variables in this research will influence purchasing behavior for green products or environmentally friendly products.
That's why the author chose the title.
AuEnvironmental Awareness.
Knowledge.
Product Quality.
Green Product Purchasing Decisions.
Based on the explanation above, in this research the author examines the positive influence of environmental awareness, knowledge and product quality on the decision to purchase green products, in this case electric vehicles.
In Figure 2.
1, it can be seen that the influence of environmental awareness (X.
, knowledge (X.
and product quality (X.
variables influence the decision to purchase green products (Electric Vehicle.
(Y).
(X.
Green Product Purchase Decisions (Y) product quality (X.
Figure 3 Conceptual Framework (Researc.
Source: Data processed by Practitioner .
Review of Previous Research Muhammad Rizwanet.
, .
An Empirical Study about Green Purchase Intention.
Vol.
No.
Macrothink Institute.
Pages 290-305.
The aim of this research is to see the influence of green perceived risk, green perceived trust, value, brand image, green advertisement and green awareness on green purchase intention.
This research was conducted by distributing questionnaires to 150 respondents who visited different The questionnaire was processed and analyzed with SPSS statistical software, using different techniques such as descriptive, correlation and factor analysis.
The results of this research are that consumers have great attention to environmental protection and they are very concerned about the state of the environment, which influences their intentions and behavior in purchasing green products.
So it can be concluded that green perceived risk, green 4874 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 perceived trust, value, brand image, green advertisement and green awareness have a positive influence on green purchase intention.
Wenny Pebrianti .
Analysis of the Influence of Environmental Awareness and Premium Prices on Intention to Purchase Green Products in Pontianak.
Vol.
No.
1 Journal of Business Economics and Entrepreneurship.
Page 69-84.
The aim of this research is to determine whether there is an influence of environmental awareness and premium prices on green product purchase intentions for organic vegetables and fruit products in Pontianak.
The total sample was 93 people who lived in Pontianak.
Data collection methods use interviews and survey studies.
The data analysis method uses descriptive statistical analysis and multiple linear regression analysis.
The results of this study indicate that the independent variables, namely environmental awareness and premium prices, simultaneously influence purchasing intentions for green products.
The partial results are also the same in that the two variables such as environmental awareness and premium prices have a significant effect on the dependent variable of intention to purchase green products.
The total coefficient of determination (R.
0414 or 41.
4% means that there is an influence of environmental awareness and premium prices on the intention to buy green products, while the rest is influenced by other factors not examined in this research.
METHODOLOGY
Data source The data sources used are:
Primary data Data was obtained from research subjects, namely West Jakarta Region Consumers.
According to Sugiyono .
Primary data is a data source that directly provides data to data collectors.
Data is collected by the researcher himself directly from the first source or place where the research object is carried out.
Secondary Data Secondary data is data that researchers obtain through literature, previous research journals, other sources related to the problem to be researched and literature studies that researchers obtain from several research supporting books so as to obtain a theoretical picture of the problem being researched, according to Sugiyono .
Secondary data is a data source that does not directly provide data to data collectors, for example through other people or through documents.
Population and Sample Population:
The population is the totality of objects that have certain qualities and characteristics that are determined by the researcher to be studied and then drawn conclusions.
The population that the researchers took was West Jakarta Region Consumers, whose number was limited to only 150 people for this research.
Sugiyono .
stated that the population as a region in general consists of objects/subjects that have certain qualities and characteristics determined by researchers to researched and then drawn conclusions.
In population research, it is divided into two, namely the general population and the target population.
Population is the totality of all elements, consisting of certain characteristics determined by the researcher to be studied for the purpose of marketing research problems.
Sugiyono said that population is a generalized area consisting of: objects/subjects that have certain qualities and characteristics that are determined by researchers to be studied and then conclusions drawn.
Meanwhile, according to Sekaran, population refers to the entire group of people, events, or things of interest that 4875 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 researchers want to investigate.
According to Ridwan in Buchari Alma .
Population 105 is the totality of characteristics or units of measurement results that are the object of research.
Based on this, it can be concluded that the population is an object or subject that resides in an area and meets certain requirements related to the research problem.
Therefore, the population used in this research is all consumers who shop in the West Jakarta area.
The sampling technique used in this research uses accidental sampling technique.
The accidental sampling technique is the withdrawal of a sample size if the exact population size is not known.
Because the population is not known with certainty, sampling used the theoretical method from Naresh Malhotra.
According to Malhotra .
, sampling is mentioned in his book Marketing Research at least four of the number of question items.
In this study there were 20 questions.
So, the number of samples taken in this study was 160 samples .
questions x .
, because there were several samples that were invalid, it became 150 samples.
Sample:
The sample is part of the population which is expected to be able to represent the population in the research.
According to Sugiyono, .
the sample is part of the number and characteristics of the population.
According to Sugiyono, .
the sample is part of the population which is the source of data in research, where the population is part of the number of characteristics possessed by the population.
The sampling technique according to Sugiyono, .
is a sampling technique, to determine the sample to be used.
According to Malhotra .
a sample is a subgroup of elements from a population selected to participate in a study.
Or in other words or part of the number and characteristics of respondents who participated from that population.
This is because it is impossible for researchers to study all elements of a population if the population is large.
Therefore, samples are selected from each element of the population.
The sampling technique used in this research used accidental sampling technique.
The accidental sampling technique is the withdrawal of a sample size if the exact population size is not known.
In this research, quantitative research methods are used by formulating problems by raising the problems described above, then collecting data in the field through research questions to respondents, then researchers will analyze the data, and formulate study results to develop recommendations for decision making, to answer research The data collection technique is carried out by field observation to see the phenomenon by conducting a pre-survey to limit problems, then the researcher will collect relevant data through library literature via the internet/library, then will collect feedback through questions by distributing questionnaires via GForm so that it can be analyzed.
RESULTS AND DISCUSSION
Table 1.
Results of Descriptive Statistical Tests Kesadaran_Lingkungan Pengetahuan_1 Kualitas_Produk Keputusan_Pembelian_Prod uk_Hijau Valid N .
Statistic Descriptive Statistics Minimum Maximum Statistic Statistic Mean Statistic Std.
Error Std.
Deviation Statistic (Source: Data Processed In 2.
Based on the Descriptive Test Results above, we can describe the distribution of data obtained by researchers as follows: 1.
Environmental_Awareness Variable, from this data it can be described that the minimum value is 18, while the maximum value is 25, the average 4876 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 value of the Environmental_Awareness Variable is 22.
48 and the standard deviation 105 of the Environmental_Awareness Variable data is 1.
Knowledge, from this data it can be described that the minimum value is 16, while the maximum value is 27, the average value of the Knowledge Variable is 21.
31 and the standard deviation of the Knowledge Variable data is Product Quality from this data can be described as the minimum value is 17, while the maximum value is 25, the average value of the Product Quality Variable is 20.
97 and the standard deviation of the Product Quality Variable data is 2.
Green Product Purchasing Decisions from this data can be described as having a minimum value of 16, while the maximum value is 25, the average value of the Green Product Purchasing Decision Variable is 04 and the standard deviation of the Green Product Purchasing Decision Variable data is Validity test To obtain primary data, researchers distributed questionnaires to consumers in the West Jakarta area with 20 questions obtained based on indicators from the variables Environmental Awareness.
Knowledge.
Product Quality and Green Product Purchase Decisions.
The following is a validity test table:
Table 2.
Validity Test Variabel Kesadaran_Lingkungan_1 Corrected Item Total Correlation Keterangan Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Kesadaran_Lingkungan_2 Kesadaran_Lingkungan_3 Kesadaran_Lingkungan_4 Kesadaran_Lingkungan_5 Pengetahuan_1 Pengetahuan_2 Pengetahuan_3 Pengetahuan_4 Pengetahuan_5 Kualitas_Produk_1 Kualitas_Produk_2 Kualitas_Produk_3 Kualitas_Produk_4 Kualitas_Produk_5 Keputusan_Pembelian_Produk_Hijau_1 Keputusan_Pembelian_Produk_Hijau_2 4877 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 Valid Valid Valid Keputusan_Pembelian_Produk_Hijau_3 Keputusan_Pembelian_Produk_Hijau_4 Keputusan_Pembelian_Produk_Hijau_5 (Source: Researcher's Primary Data, 2.
Based on the findings in the table above, it can be seen that the r-count/Corrected Item Total Correlation is greater than the r-table so it can be concluded as valid data.
The r-table is obtained from the statistical r table with the criterion = 0.
05 in a two-way test and df = n-2 .
= number of sample.
Reliability Test Reliability is a tool for measuring a questionnaire which is an indicator of a variable.
construct or variable is said to be reliable if it provides a Cronbach Alpha value > 0.
(Mudrajad, 2009:.
Table 3.
Reliability Test Table CronbachAos Cronbach Alpha Alpha Kesadaran_Lingkungan 0,60 Pengetahuan 0,60 0,60 Kualitas_Produk 0,60 Keputusan Pembelian Produk Hijau Variabel N of Items (Source: Researcher's Primary Data, 2.
From the table 4.
8 above, it is known that all statements from the variables Environmental Awareness (X.
Knowledge (X.
, and Product Quality (X.
on the Decision to Purchase Green Products (Y) have a Cronbach Alpha value greater than 0.
So it can be concluded that all statements used for the variables in this research are reliable.
Classic assumption test Normality Test The normality test aims to test whether in the regression model, the confounding or residual variables have a normal distribution (Ghozali, 2012: .
Draw the Normal Curve P-P Plot 4878 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 Based on the image above, it can be concluded that in a normal p-plot graph, the 105 can be seen spreading around the diagonal line, and the spread is not too far or wide.
In this case, the graph shows that the regression model meets the normality assumption and is suitable for use.
Histogram Normal Curve Image (Source: Data processed 2.
Based on the image above, it can be concluded that in the Histogram graph you can see a line resembling a bell, which means the data is normally distributed.
Kolmogorov-Semirnov Normality Test Table 4.
Kolmogorov-Semirnov Normality Test Table One-Sample Kolmogorov-Smirnov Test Unstandardized Residual Normal Parametersa,b Mean Std.
Deviation Most Extreme Differences Absolute Positive Negative Test Statistic Asymp.
Sig.
-taile.
(Source: Data processed 2.
From the picture above, it is known that the results of the Kolmogrov-Smirnov test are 061 at a significance of 0.
200 (Asymp.
Sig.
-taile.
), meaning that it can be concluded that the residuals are normally distributed, because the p value is > 0.
Multicollinearity Test The multicollinearity test aims to test whether the regression model finds a correlation between independent variables.
To detect whether there is multicollinearity, you can look at the VIF (Variance Inflation Facto.
value and the Tolerance value.
The regression model is said to be free from multicollinearity if the VIF value is O 10, and the tolerance value is Ou0.
(Ghozali, 2012: .
The VIF and Tolerance test results from the regression model can be seen in the following table:
4879 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 Table 5.
Multicollinearity Test Results Coefficientsa Unstandardized Standardized Coefficients Coefficients Std.
Error Beta Model (Constan.
Kesadaran_Lingku Kualitas_Produk Pengetahuan_1 Dependent Variable: Keputusan_Pembelian_Produk_Hijau (Source: Data processed 2.
Collinearity Statistics Sig.
Tolerance VIF The results of the table above calculating the Variance Inflation Factor (VIF) value show that the VIF value for Environmental Awareness is 2,035, the VIF value for Product Quality is 2,167, the VIF value for Knowledge is 2,351.
This shows that there is not a single independent variable that has a VIF value of no more than So it can be concluded that there is no multicollinearity between the independent variables in the regression model.
The calculation results also show the Tolerance value for each variable, namely Environmental Awareness of 491.
Product Quality of 0.
Knowledge 1 of 0.
This means that there are no independent variables that have a Tolerance value of less than 0.
So according to the Tolerance value, multicollinearity does not occur in the regression model.
This is in accordance with Imam Ghozali's statement .
2: .
, that the cut off value commonly used to assess the presence of multicollinearity is if the VIF value O 10 or the Tolerance value Ou 0.
Heteroscedasticity Test Heteroscedasticity aims to test whether in the regression model there is inequality of variance from the residuals of one observation to another.
If the residual variance from one observation to another is constant then it is called homoscedasticity and if it is different it is called heteroscedasticity (Ghozali, 2012: .
Scatterplot graphic image of heteroscedasticity test results (Source: Data processed 2.
4880 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 From the scatterplot graph, it can be seen that the points are spread randomly and 105 do not form a clear pattern spread either above or below the number 0 on the Y axis.
It can be concluded that there is no heteroscedasticity in the regression model, so the regression model is suitable for use to predict Green Product Purchasing Decisions based on enter the independent .
In accordance with Imam Ghozali's statement .
2: .
, that if there is a certain pattern, such as the dots forming a certain regular pattern .
avy, widening, then narrowin.
, and if there is no clear pattern and the dots are spread out above and below zero on the Y axis, then heteroscedasticity does not occur.
Tests with plot images can be misleading if the amount of data is small.
For this reason, more accurate testing is needed, namely the Spearman method.
If the independent variable statistically significantly influences the dependent variable, then there is an indication of The results of the SPSS output display clearly show that none of the independent variables have a statistically significant effect on the dependent variable value (Ghozali, 2011: .
Table 6.
Spearman Heteroscedasticity Test Correlations Spearman's Kesadaran_Ling Kualita Kesadaran_ s_Prod Pengetahuan Unstandardize Lingkungan d Residual 707** .
Correlation Coefficient Sig.
-taile.
Kualitas_Produk Correlation Coefficient Sig.
-taile.
Pengetahuan_1 Correlation Coefficient Sig.
-taile.
Unstandardized Correlation Coefficient Residual Sig.
-taile.
**.
Correlation is significant at the 0.
01 level .
-taile.
(Source: Data processed 2.
From the table it can be seen that the probability of significance is above 0.
It can be seen that the sig value.
Environmental Awareness is 0.
861, sig value.
Product Quality is 0.
and Knowledge 1 value is 0.
So it can be concluded that the regression model does not contain heteroscedasticity.
Autocorrelation Test The autocorrelation test aims to test whether in a linear regression model there is a correlation between confounding errors in period t and period t-1 .
Autocorrelation arises because successive observations over time are related to each other.
This is often found in time series data because "disorders" in individuals or groups tend to influence "disruptions" in the same individual or group in the following period.
In this research, researchers used the Durbin Waston (DW tes.
approach, because the sample used was 150 samples.
The Durbin Waston test is only used for level one autocorrelation and requires the presence of a constant in the regression model and no other variables between the variables.
4881 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 Hipotesis Nol Keputusan Jika Tidak ada autokorelasi positif Tolak 0 < d < dL Tidak ada autokorelasi positif No decision dL O d O dU Tidak ada korelasi negatif Tolak 4 Ae dL < d < 4 Tidak ada korelasi negatif No decision 4 Ae dU < d < 4 Ae dL Terima dU < d < 4 Ae Du Tidak ada autokorelasi positif atau negative The results of calculating the Durbin Watson value resulting from the regression model are shown in the table below:
Autocorrelation Test Results Table Model Table 7.
Autocorrelation Test Results Table Model Summaryb Adjusted R Std.
Error of the R Square Square Estimate Durbin-Watson Predictors: (Constan.
Pengetahuan_1.
Kesadaran_Lingkungan.
Kualitas_Produk Dependent Variable: Keputusan_Pembelian_Produk_Hijau (Source: Data processed 2.
Based on the results of the table above, the Watson Durbin test result is 1,906.
The dL and dU values are searched for N=150, then we get dL = 1,692 and dU= 1,774, while 4-1,774 = 4 Ae 1,774 = 2,226, the result is 1,774 <1,906<2,226, the conclusion is that there are no symptoms of positive or negative autocorrelation.
Multiple Regression Analysis Multiple regression analysis is a development of simple regression analysis.
Its use is to predict the value of the dependent variable (Y) if there are at least two or more independent Multiple regression analysis is an analytical tool for forecasting the influence value of two or more independent variables on the dependent variable to prove whether or not there is a functional relationship or causal relationship between two or more independent variables on variables (X.
, (X.
and (X.
with one variable bound:
The results of multiple regression analysis in this study are as follows:
Table 8.
Multiple Regression Test Results Coefficientsa Unstandardized Standardized Coefficients Coefficients Model Std.
Error Beta (Constan.
Kesadaran_Lingkungan Kualitas_Produk Pengetahuan_1 Sig.
(Source: Data processed 2.
4882 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 Based on the table above, it is known that the coefficient values of the regression equation obtained by the regression equation model are as follows:
Y = 0.
308 X1 0.
748 X2 - 0.
259 X3
Where:
Y = Turnover Intention X1 = Environmental_Awareness X2 = Knowledge X3 = Product_Quality Hypothesis test The t test is used to show how far the influence of individual independent variables is in explaining variations in the dependent variable of the test criteria, namely Significance t < 0.
05 and ycEaiycycycug > ycycycaycaeyco, then the null hypothesis .
is rejected and the alternative hypothesis .
is accepted.
This means that there is an influence between the independent variable (X) on the variable (Y).
Significance t > 0.
05 and ycEaiycycycug < ycycycaycaeyco, then the null hypothesis .
is accepted and the alternative hypothesis .
is rejected.
This means that there is no significant influence between the independent variable (X) on the dependent variable (Y).
The results of statistical testing on the t test can be seen in table 9 as follows:
Table 9.
t Test Results Coefficients Unstandardized Standardized Coefficients Coefficients Model Std.
Error Beta (Constan.
Kesadaran_Lingkungan Kualitas_Produk Pengetahuan_1 Sig.
(Source: Data processed 2.
The f test is used to show how far the independent variables influence simultaneously in explaining variations in the dependent variable of the test criteria, namely:
ANOVAa Model Regression Residual Total Sum of Squares Mean Square Sig.
(Source: Researcher's Primary Data, 2.
Coefficient of Determination .
The coefficient of determination ycI2 essentially measures how far the model is able to explain variations in the dependent variable.
The coefficient of determination value is determined by the Adjusted R Square value as follows:
Model Table 10.
Coefficient of Determination Test Model Summaryb Adjusted R Std.
Error of R Square Square the Estimate DurbinWatson 4883 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 Predictors: (Constan.
Pengetahuan_1.
Kesadaran_Lingkungan.
Kualitas_Produk Dependent Variable: Keputusan_Pembelian_Produk_Hijau (Source: Researcher's Primary Data, 2.
CONCLUSION Conclusion: After analyzing primary data regarding environmental awareness, knowledge and price on Green Product Purchasing Decisions .
urvey of consumer members in the West Jakarta are.
, the following conclusions can be drawn: 1.
The environmental awareness variable influences the decision to purchase green products.
So it can be concluded that the Environmental Awareness variable has no significant effect on Green Product Purchasing Decisions.
Therefore the first hypothesis statement (H.
is rejected.
The knowledge variable influences the decision to purchase green products.
So it can be concluded that the knowledge variable has a significant effect on Green Product Purchasing Decisions.
Therefore the second hypothesis statement (H.
is accepted.
Product Quality Variables influence green product purchasing decisions.
So it can be concluded that the price variable has a significant influence on Green Product Purchasing Decisions.
Therefore the third hypothesis statement (H.
is accepted.
In the F-test, the F-count value is greater than the ftable, so that the regression model can be used to predict the Green Product Purchase Decision variable or it could be said that the environmental awareness, knowledge and product quality variables together .
has a significant effect on Green Product Purchasing Decisions.
Looking at the results of this research, it can be concluded that consumers pay attention to environmental awareness, knowledge and product quality in deciding to purchase green Especially in knowledge, although it has a significant effect, the results are negative, that means if in the regression analysis you have carried out it is found that the variable X2X_2X2 (Knowledg.
has a significant but negative influence on the decision to purchase green products, so the meaning is as follows: Significant Influence: Knowledge (X.
has a real relationship with the decision to purchase green products.
This means changes in the level of knowledge have a measurable effect and do not occur by chance.
Negative Influence: A negative relationship means that as the level of knowledge increases, the decision to purchase green products tends to decrease.
In other words, the more knowledge someone has about green products or about environmental issues, the less likely they are to buy green products.
Therefore, there needs to be a massive effort to raise environmental awareness among the public about the importance of green products.
This research can be carried out again by taking a wider scope and number of respondents so that it will get different responses.
In future research, additional research variables can be carried out that influence green product purchasing decisions with more diverse combinations.
For example, adding the variables green companies, green organization image, green perceived value, green trust and green perceived risk can enrich variations in research.
ACKNOWLEDGMENTS
The author would like to express his deepest gratitude to Dian Nusantara University, especially the Research and Community Service Division (LRPM), for their continuous financial support and assistance during this research.
Funding provided by the LRPM played an important role in the successful completion of the study on Environmental Awareness.
Knowledge.
Product Quality and Green Product Purchase Decisions We also acknowledge the invaluable support and resources provided by LRPM, which have made significant contributions to the progress of our research.
The drive and commitment of the LRPM team is 4884 | P a g e https://dinastipub.
org/DIJEFA Vol.
No.
November 2024 critical, and we greatly appreciate their dedication to fostering research excellence community engagement.
REFERENCES