p–ISSN: 2723 - 6609 e-ISSN: 2745-5254
Vol. 5, No. 10, October 2024 http://jist.publikasiindonesia.id/
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4352
The Influence of Iconnet Product Personal Selling on the
Purchase Interest of Housing Residents in Medan City
Maria Bona Putri S
1
, Ratih Hasanah Sudradjat
2*
Universitas Telkom Bandung, Indonesia
Email: [email protected]
1
,
2
*
*Correspondence
ABSTRACT
Keywords: personal
selling; minat beli; ICON+
Technology has influenced humans in their daily lives. The
improvement of technological developments can affect
aspects of life that cannot be separated from the use of the
internet. It is seen in the last 5 years that the use of
technology in Indonesia has grown rapidly, marked by the
emergence of many internet service providers. The increase
in household internet users is one of the phenomena that can
be used by ICON+ to be able to attract new users. This target
market will try to find alternative internet providers that can
meet the needs of the internet in households at affordable
prices. This study aims to measure the influence of personal
selling carried out by ICON+ sales on the buying interest of
people in Medan housing. This study is quantitative research
with a simple linear regression method from a total of 350
respondents. The results of this study stated that personal
selling had an effect on the buying interest of residents in
Medan city housing with the influence of the independent
variable on the bound variable of 52.2% while the remaining
47.8% was influenced by other factors outside this study.
Introduction
As the times continue to evolve and progress, everyone is required to adapt to the
changing circumstances. Especially in terms of obtaining information quickly and
effectively, which is highly needed today. The speed in obtaining such information is
supported by internet access. (Dellamita et al., 2014). The variety of telecommunication
facilities and increasingly sophisticated information technology products are due to the
development of information and telecommunication technology. (Hanim Tafri et al.,
2011). This is one of the impacts of the globalization era, where computers and the
internet, with their dynamic nature, have become coherent facilities dominating various
life activities. In the fields of education, industry, commerce, and offices, these facilities
are necessary. (Patmanthara, 2012).
Technology has influenced humans in their daily lives. If people are "technology
illiterate," they will be slow to obtain information and increasingly find it difficult to
Maria Bona Putri S, Ratih Hasanah Sudradjat
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4353
progress. Today's society is moving towards an information society or knowledge society
where information holds an important and tangible role. In the current era, there is
increasingly intense competition in the telecommunications business.
The improvement of technology development has influenced aspects of life that
cannot be separated from the use of the internet. In the past five years, the use of
technology in Indonesia has developed rapidly. Household internet usage in Indonesia
has sharply increased to 78.18 percent. The increase in internet users in 2020 was
followed by an increase in the number of mobile phone users, reaching 62.84 percent, and
the increase in computer users, which also rose by 18.83 percent. Thus, from 2016 to
2020, the percentage increased from 25.37 percent to 53.73 percent (Central Bureau of
Statistics, 2020).
The increase in household internet users is one phenomenon that ICON+ can utilize
to attract new users. This target market will seek alternative internet providers that can
meet household internet needs at affordable prices. Seeing this, PT Indonesia Comnets
Plus (ICON+) believes that the products offered can be an option for providing the right
internet services. The company, a subsidiary of PT PLN (Persero), focuses on building
"Right of Ways" (RoW), meaning gradually building telecommunication network
connections in remote areas of Indonesia using fiber optic networks spanning 891.00 km
across Sumatra, Java, Bali, Nusa Tenggara, Sulawesi, and Kalimantan.
Figure 1 ICONNET service coverage
On May 31, 2021, PLN launched the rebranding of its latest internet service from
Stroomnet to Iconnet through its subsidiary PT Indonesia Comnets Plus (ICON+)
(ICON+ and PLN Launch Iconnet Brand Change, 2021).
The Influence of Iconnet Product Personal Selling on the Purchase Interest of Housing
Residents in Medan City
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4354
Figure 2 ICONNET Launching
The image above shows that the Iconnet product is a rebranding of Stroomnet, and
the internet service product owned by ICON+ and PLN has been available since 2020.
Some articles mention that Iconnet products are cheaper, allowing them to compete with
other internet service providers (Icon+News, 2021).
According to the Central Bureau of Statistics (BPS), Medan is the city outside Java
Island with the highest Gross Regional Domestic Product (GRDP), reaching up to
241,882 billion Rupiah. The economic growth of the capital of North Sumatra is the
highest outside Java, making Medan one of the best cities to work or open a long-term
business. The growth of housing in Medan is also increasing rapidly. Not only are there
more simple and medium-sized housing areas, but the number of luxury housing
complexes in Medan is also growing significantly.
Therefore, to be more specific and easy to differentiate, the researcher will use one
of the promotional mixes. According to (Kotler et al., 2019), several processes occur in
the personal selling of Iconnet products towards the purchase interest of residents in
Medan's housing areas.
Method
Type of Research
This research is conducted using a quantitative approach, utilizing numerical data
to observe the influence between the variables of Personal Selling and Purchase Intention.
According to (Indrawati, 2015), research methods are scientific processes carried out to
obtain findings, test theories, and develop theories to gather data to identify, solve, and
anticipate problems.
Maria Bona Putri S, Ratih Hasanah Sudradjat
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4355
The method used in this research is descriptive quantitative research. Quantitative
research aims to test whether there are relationships among variables and objectively test
theories. (Ishtiaq, 2019). The variables in this study must be measurable and are usually
found in the instruments, allowing numerical data to be analyzed using statistical
procedures.
Operational Variables and Measurement Scale
1. Operational Variables
Variables are observable and measurable elements that focus on characteristics
inherent in individuals or organizations and vary across individuals or organizations being
studied. (Ishtiaq, 2019). In this research, the independent variable (X) is Personal Selling,
and the dependent variable (Y) is Purchase Intention.
Below is the operational definition of the variables in this study:
Table 1
Operational Variables
Variables
Dimensions
Indicator
Scale
Question No.
Personal
Selling (X) P.
Kotler &
Armstrong
(2012: 62)
Prospecting
and
Qualifying
Consumer Profession
Ordinal
1
Consumer knowledge
Ordinal
2
Consumer background
Ordinal
3
Approach
Direct sales visits
Ordinal
4
Number of Internet users
Ordinal
5
Good looks
Ordinal
6
Introduce yourself
Ordinal
7
Presentation
and
Demonstrati
on
Have good knowledge
Ordinal
8
Explains the product well
Ordinal
9
Explaining the advantages
and benefits
Ordinal
10
Handling
Objections
Taking a positive approach
Ordinal
11
Finding out customer
difficulties
Ordinal
12
Explaining consumer
difficulties
Ordinal
13
Closing
Inquire about consumer
interest
Ordinal
14
Reviewing purchase deal
points
Ordinal
15
Follow Up
Offer enrollment assistance
Ordinal
16
Provide purchase requirement
information.
Ordinal
17
Reconfirm product service
Ordinal
18
Purchase
Interest (Y)
Rehman et al.
(2014:42)
Attention
Offer products as needed
Ordinal
19
Is a reliable product
Ordinal
20
Interest
Attractive offers
Ordinal
21
Interested in buying products
from the offer
Ordinal
22
Desire
A product that meets the
needs
Ordinal
23
Advantages that generate
interest in using the product
Ordinal
24
The Influence of Iconnet Product Personal Selling on the Purchase Interest of Housing
Residents in Medan City
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4356
Action
Interested in buying the
product
Ordinal
25
Satisfied with the service
Ordinal
26
2. Measurement Scale
This study uses a Likert scale for secondary data. The Likert scale aims to measure
attitudes, opinions, and views of individuals or groups regarding social phenomena.
(Sugiyono, 2021). Indicators are set as benchmarks to develop instruments containing
statements or questions.
Table 2
Likert Scale
Options
Score
Strongly Agree
4
Agree
3
Disagree
2
Strongly Disagree
1
Source: (Sugiyono, 2014: 133)
3. Population and Sample
a. Population
Population refers to the wide area encompassing objects or subjects with certain
qualities and characteristics that researchers use to gain further understanding and
draw conclusions. The population in this study comprises individuals who are aware
of Iconnet products and have been offered them through Personal Selling by Iconnet
sales representatives, residing in housing complexes in Medan, totaling 2,825 units.
b. Sample
A sample is a portion of the population that can be considered representative of
the entire population. (Sugiyono, 2013). This research requires predetermined
respondent criteria to achieve appropriate research results. The criteria include
residents of housing complexes in Medan who have been offered Iconnet products
through Personal Selling. Since the population size is known, the sample size is
determined using the Slovin formula, as follows:
Where
n = Minimum sample size
N = Population size
e = Margin of error (0.05)
Source: Gendro Wiyono (2011) in Saputra and Septyarini (2021)
This study uses a 95% confidence level. The margin of error is set at 5%, with a
population size of 2,825 units, resulting in the following minimum sample size:
Maria Bona Putri S, Ratih Hasanah Sudradjat
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4357
Therefore, the sample size for this study is determined to be 350 respondents.
Results and Discussion
Results of the Classical Assumption Test
This test is conducted to ensure no violation of classical assumptions. Before
testing, it is necessary to evaluate all data required for the research. The purpose of the
classical assumption test is to examine and determine whether the regression model used
in this study is appropriate. For data to be considered suitable, it must meet certain criteria:
it should be normally distributed and free from autocorrelation, multicollinearity, and
heteroscedasticity. Therefore, it is essential to conduct a classical assumption test before
performing multiple linear regression analysis, which consists of:
a. Normality Test Results
The normality test is used to analyze whether, in a regression, the independent and
dependent variables or both are normally distributed. This test aims to verify whether the
disturbance or residuals in the regression model are normally distributed. A regression
model is considered good if the data distribution is normal or close to normal. In this
study, the normality test employs the Kolmogorov-Smirnov analysis technique (1-Sample
K-S). The Kolmogorov-Smirnov test is used as the basis for decision-making: if the
Asymp. Sig. (2-tailed) value is greater than 0.05, it indicates that the data is normally
distributed. The results of the normality test are shown in Figure 3 below.
The Influence of Iconnet Product Personal Selling on the Purchase Interest of Housing
Residents in Medan City
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4358
Figure 3 Normality Test Results
Based on Figure 3 above, it is observed that the Asymp. Sig. (2-tailed) value is
greater than 0.05, specifically 0.110, indicating that the regression model in this study
meets the normality assumption and is normally distributed.
b. Heteroscedasticity Test Results
The heteroscedasticity test is conducted to determine whether there are deviations
in the model due to varying types of disturbances between observations. In a scatterplot
diagram, a study is considered free from heteroscedasticity if there are no randomly
scattered points or specific patterns, both below and above zero on the Y-axis. The
scatterplot results are shown in Figure 4 below.
Figure 4 Heteroscedasticity Test Results
(Source: Processed by the researcher, 2024)
Based on Figure 4, it can be concluded that the points are scattered above and below
zero on the Y-axis, and there is no clear pattern. If heteroscedasticity occurs, the graph
will show points forming waves or specific patterns regularly spreading and then
narrowing. Thus, it can be concluded that heteroscedasticity does not occur as the scatter
plot in the regression model shows an unclear or irregular pattern.
Maria Bona Putri S, Ratih Hasanah Sudradjat
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4359
c. Correlation Coefficient Test Results
To statistically test and prove the relationship between (X) and (Y), correlation
analysis is used. Correlation analysis is employed to determine the correlation between
one independent variable and one dependent variable with ordinal data categories. Below
are the correlation test results. The significance level criteria used as the basis for
determining the correlation are: a) p < 0.01 indicates a significant correlation, b) 0.01 ≤ p
< 0.05 indicates a fairly significant correlation, and c) p > 0.05 indicates no significant
correlation.
Figure 5 Correlation Coefficient Test Results
(Source: Processed by the researcher, 2024)
From the figure above, it is known that the correlation (r) between the Personal
Selling variable (X) and Purchase Intention (Y) is 0.723 with a significance of 0.000,
indicating that the correlation coefficient is strong and significant.
Determination Coefficient Test Results
The determination coefficient (R²) test is conducted to assess how well the research
model can explain the dependent variable. In other words, R Square is used to measure
the extent to which the variation in the dependent variable can be collectively explained
by the independent variables.
Figure 6 Determination Coefficient Test Results
(Source: Processed by the researcher, 2024)
Based on the figure above, the R Square value is 0.522, indicating that Personal
Selling influences Purchase Intention by 52.2%, and the remaining 47.8% is influenced
by other factors outside the research model.
The Influence of Iconnet Product Personal Selling on the Purchase Interest of Housing
Residents in Medan City
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4360
Simple Linear Regression Test Results
The simple linear regression analysis aims to determine the influence of one
variable on another.
Figure 7 Simple Linear Regression Test Results
(Source: Processed by the researcher, 2024)
Based on Figure 7 above, the relationship between the personal selling variable (X)
and purchase intention (Y) can be explained. The simple linear regression equation used
is Y = a + bX. From the output, the regression model equation is obtained as follows:
Y= 3.374 + 0.381 X
The coefficients in the simple linear regression equation above can be explained as
follows: the regression coefficient for the constant is 3.374, indicating that if the personal
selling variable is zero or constant, there will be a 337.4% increase in purchase intention.
Meanwhile, the personal selling variable coefficient of 0.381 indicates that each unit
increase in the personal selling variable will increase the effectiveness of social media
usage by 38.1%.
Hypothesis Test Results
The partial hypothesis test aims to determine whether there is an influence of
independent variables on the dependent variable individually. The t-test essentially aims
to show how far each independent variable individually influences the dependent
variable's variation. (Ghozali, 2016). Additionally, the test is conducted using a
significance level of 0.05 (α = 5%), with the criteria that if the significance value is less
than 0.05 and the t-value is greater than the t-table value, then the hypothesis is accepted.
The t-table value for this research is df = 350 - 2 = 348, resulting in a t-table value of
1.649949.
Figure 8 Hypothesis Test Results
(Source: Processed by the researcher, 2024)
Maria Bona Putri S, Ratih Hasanah Sudradjat
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4361
Based on the significance value, the linear regression results show that the
significance value of the Personal Selling variable (X) is 0.000 <0.05, indicating that
Personal Selling (X) has a positive and significant relationship with the Purchase
Intention variable (Y) individually. The t-table value for 5% significance is pdf = 350 - 2
= 348, resulting in a t-table value of 1.649949. Therefore, based on the t-value, the test
results show that the t-value for Personal Selling (X) is 19.509 > 1.649949, meaning that
Personal Selling has a positive and significant relationship with Purchase Intention.
Discussion of Research Results
From the research results obtained, it is known that each variable of Personal Selling
and Purchase Intention has met the criteria for good data, which are valid and reliable.
This is also supported by the normal data distribution and freedom from
heteroscedasticity issues.
Discussion of the Influence of Personal Selling on Purchase Intention
Based on the descriptive analysis of the Personal Selling variable (X), it is known
that the highest to lowest percentage values include Iconnet sales representatives having
good product knowledge and explaining the advantages and benefits of the product to
potential consumers, both valued at 78.4%. The last position is the statement of the sales
representatives' lack of knowledge about the background of potential customers. Based
on the descriptive analysis of the Purchase Intention variable (Y), it is known that the
highest to lowest percentage values include respondents' satisfaction with Iconnet sales
representatives offering Iconnet products with a score of 86.2%, followed by the
statement that the offered product's advantages make respondents interested in buying
Iconnet products at 85.1%, and the last position is respondents' interest in purchasing
Iconnet products at 83%.
From the research results conducted, it can be concluded that Personal Selling
influences Purchase Intention. This research result is determined by the t-test and
significance test conducted related to the personal selling variable on purchase intention,
with a t-value of 19.509 and a significance value of 0.000. This indicates that the t-value
of 19.509 is greater than the t-table value of 1.649949, and the significance value of 0.000
is less than 0.05, indicating that personal selling influences the purchase intention of
housing residents in Medan City.
The determination coefficient (R²) is 0.522, meaning that Personal Selling
influences Purchase Intention by 52.2%, and the remaining 47.8% is influenced by other
factors outside the research model. Overall, the research results state that personal selling
does influence the purchase intention of housing residents in Medan City. Personal selling
involves direct interaction between the seller and the buyer. This allows the seller to
answer questions, provide relevant information, and address objections directly, which
can increase the buyer's trust. Additionally, in the personal selling process, the seller can
quickly identify and address objections or doubts that customers may have, helping them
feel more comfortable making a purchase.
These research findings are also supported by previous studies with similar results,
such as the study by (Aprianto & Candraningrum, 2019), which states that personal
The Influence of Iconnet Product Personal Selling on the Purchase Interest of Housing
Residents in Medan City
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4362
selling influences the purchase intention of housing residents in Medan City.
Additionally, the study by (Siagian et al., 2022) also confirms that personal selling affects
consumer purchase intention, and this is further supported by the research by
(Syarifuddin, 2023), which reports similar findings. The relationship between personal
selling and purchase intention exists because personal selling allows sellers to build closer
relationships with consumers. Good relationships can enhance trust and loyalty, making
consumers more likely to buy. Sellers can provide specific and relevant information about
products or services, including features, benefits, and usage instructions. This information
helps consumers understand the product's value and make better purchasing decisions.
Through direct interaction, sellers can receive feedback from consumers about products
or services. This feedback is not only useful for sellers to improve their offerings but also
shows consumers that their opinions are valued.
Conclusion
Based on the research findings, the coefficient of determination (R Square) is 0.522,
indicating that personal selling has an influence on purchase intention by 52.2%, while
the remaining 47.8% is influenced by other factors outside the research model.
Furthermore, the study results were confirmed through a t-test and significance test,
which demonstrated the relationship between the personal selling variable and purchase
intention. The t-value obtained was 19.509, which is greater than the t-table value of
1.649949, and the significance value was 0.000, which is less than 0.05. These results
suggest that personal selling has a significant influence on the purchase intention of
housing residents in Medan City.
Maria Bona Putri S, Ratih Hasanah Sudradjat
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4363
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