p–ISSN: 2723 – 6609 e-ISSN: 2745-5254
Vol. 6, No. 1, January 2025 http://jist.publikasiindonesia.id/

Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 121

The Effect of Personal Selling of Iconnet Products on the Buying
Interest of Housing Residents in Medan City

Maria Bona Putri S1*, Ratih Hasanah Sudrajat2

Universitas Telkom, Indonesia
Email: [email protected]*,

ABSTRACT
Keywords: personal selling;
buying interest; 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

The existence of an era that is increasingly developing and moving forward requires
everyone to adapt to their circumstances. Especially in terms of obtaining information
quickly and effectively is something that is needed today. The speed of obtaining this
information is supported by the existence of internet network access (Utomo & Hendrati,
2024).

The variety of telecommunication facilities and information technology products
that are increasingly sophisticated is due to the development of information technology
and telecommunications (Pratama, 2024). This is one of the impacts of the globalization
era, where computers and internet networks with their dynamic nature are the coherence
of facilities that have dominated various life activities. In the world of education, industry,
commercial and office need these facilities (Lestari, 2022).

Technology has influenced humans in their daily lives. If humans "stutter with
technology", they will be slow to obtain information and it will be more difficult to
advance. Today's society is heading towards the era of an information society or a
knowledge society where information holds an important and real task. In today's era,
more competition in the telecommunications business is getting tighter (NOVIA, 2023).

Maria Bona Putri S, Ratih Hasanah Sudrajat

Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 122

The improvement of technological developments can affect aspects of life that
cannot be separated from the use of the internet. It has been seen in the last 5 years that
the use of technology in Indonesia has grown rapidly. Household internet usage in
Indonesia has increased sharply to reach 78.18 percent. The increase in internet users in
2020 was followed by an increase in the number of mobile phone users, which reached
62.84 percent, in addition to the increase in computer users also increased by 18.83
percent. So, from 2016 to 2020, there was an increase in the percentage from 25.37
percent to 53.73 percent (Central Statistics Agency, 2020).

The increase in household internet users is one of the phenomena that ICON+ can
take advantage of 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. Seeing this, PT Indonesia Comnets Plus (ICON+) feels that the
products offered can be an option for providing the right internet service. The company
is a subsidiary of PT PLN (Persero) which focuses on building "Right of Ways" (Row)
which means building a telecommunication network connection gradually in remote areas
in Indonesia using a fiber optic network along 891.00 km, namely Sumatra, Java, Bali,
Nusa Tenggara, Sulawesi and Kalimantan (Wardani et al., 2023).

PT. Indonesia Comnets Plus (ICON+) was established on October 3, 2000. This
company is a subsidiary of PT PLN (Persero) which is on a mission to meet the needs as
a provider of Information and Communication Technology (ICT) solutions. ICON+ is
specifically aimed at serving the needs of PT PLN (Persero) in providing network services
and telecommunication content with transmission media using fiber optics. The fiber
optic network has a length of approximately 891,000 km which has regional coverage,
namely Sumatra, Java, Bali, Nusa Tenggara, and Kalimantan.

Since 2008, ICON+ has consistently and periodically expanded telecommunication
network connectivity to several remote areas in Indonesia that utilize the utilization of PT
PLN (Persero's electricity network rights), namely the "Right of Ways" (RoW) which
covers areas in all areas of Indonesia. In carrying out business activities, ICON+
collaborates with various companies and institutions in Indonesia.

ICON+'s operating locations throughout Indonesia are getting wider. ICON+'s
regional office network is already present in several major cities, such as Medan, Padang,
and Palembang. Jakarta, Bandung. Semarang, Surabaya, Bali, Makassar and Balikpapan.

Based on the background description and identification of the problem above, the
purpose of this study is to determine the influence of Personal Selling of ICONNET
products on the buying interest of housing residents in the city of Medan.

Method

This research was carried out with a quantitative approach, of course, using
numbers to see the influence between Personal Selling variables and Buying Interest. The
research method is a scientific process carried out in research to obtain findings, prove a
theory, and develop a theory to obtain data with the aim of identifying, solving, and
anticipating problems (Alfansyur & Mariyani, 2020).

The Effect of Personal Selling of Iconnet Products on the Buying Interest of Housing Residents
in Medan City

Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 123

The type of method used is descriptive quantitative research. Quantitative research
is an approach that aims to test whether there is a relationship in each variable and test
the theory objectively (Priyatno, 2013). The variables in this study must be measurable
and usually exist on the instrument so that the numerical data can be analyzed with
statistical procedures.
Population and Sample
1. Population

Population is a wide area that includes objects and subjects with certain qualities
and characteristics that are used by researchers in conducting further understanding
and drawing conclusions (Alfansyur & Mariyani, 2020). The population in this study
is people who have known Iconnet products and have been offered Personal Selling
by Iconnet sales where they live in housing in the city of Medan totaling 2,825 units.

2. Sample
Samples are some parts of the population that can be considered to represent

the entire population. The research of course requires predetermined respondent
criteria to achieve appropriate research results. The respondents' criteria are housing
people who live in Medan and have been offered Iconnet products through Personal
Selling. Since the population is known for sure, the sample size will be used through
the Slovin formula, as below:

�� =
��

1 + ��(��2)

Information:
n = Minimum number of samples

N = Number of population

e = Error tolerance limit (0.05),

Source = Gendro Wiyono (2011) in Saputra and Septyarini (2021)

This study used a 95% confidence level. The error tolerance limit is set at 5%, and
the population is 2,825 units, so that the minimum number of samples is obtained as
below.

�� =
��

1 + ��(��2)

�� =
2825

1 + 2825(0,052)

�� =
2825

1 + 2825(0,0025)

�� =
2825

1 + 7,0625

�� =
2825
8,0625

Maria Bona Putri S, Ratih Hasanah Sudrajat

Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 124

�� = 350,3875

So, from the above results, it is known that the number of samples studied in this
study is 350.3875 respondents (350 people).
Data Collection Techniques

To conduct research, it is necessary to determine techniques and tools aimed at
collecting data related to research. In obtaining these data, it is necessary to use collection
techniques and tools to prove the hypotheses that have been designed by the researcher.
This study collects data using primary and secondary data.
a. Primary Data

Primary data is data obtained from primary sources obtained directly by
providing data to researchers based on observations and by distributing questionnaires
to respondents. In this study, the researcher will obtain a primary data source, namely
by disseminating a questionnaire in the form of a google form and disseminated
through social media to the community in housing in the city of Medan.

b. Secondary Data
Secondary data is additional data that can be used to support primary data.

Secondary data is obtained from indirect sources, such as the results of documentation,
books, the internet, and sources from previous research that are related to research
conducted by researchers.

Results and Discussion
Respondent Characteristics Analysis

This study uses primary data in the form of questionnaires distributed to samples in
the form of Google Forms. The respondents have been adjusted based on the calculation
of the slovin formula, which is a total of 350 people. The questionnaire is considered valid
if the respondent meets the criteria for the formula that has been set.
Characteristics of Respondents Based on Screening Questions

Figure 1

Characteristics of Respondents Living in Housing (Complex) in Medan City

(Source: Data processed by researchers, 2024)

The Effect of Personal Selling of Iconnet Products on the Buying Interest of Housing Residents
in Medan City

Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 125

Figure 1 above shows that there are 356 respondents who answered yes to screening
questions from 382 people. This shows that there are 356 respondents who live in housing
(complex) in the city of Medan.

Figure 2

Characteristics of Respondents who have been offered Iconnet products
(Source: Data processed by researchers, 2024)

Based on figure 2 above, it shows that there are 350 respondents who answered yes,
which means that 350 people have been offered Iconnet products by Iconnet sales.
Respondent Characteristics by Gender

Figure 3

Characteristics of Respondents Based on Gender
(Source: Data processed by researchers, 2024)

Based on gender, female respondents amounted to 71.7%, namely 251 people,

while male respondents amounted to 28.3%, namely 99 people. This indicates that the
majority of respondents living in Medan housing complexes who fill out the questionnaire
are dominated by women.
Respondent Characteristics Based on Occupation

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Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 126

Figure 4

Characteristics of Respondents Based on Occupation
(Source: Data processed by researchers, 2024)

In accordance with the results of the characteristics of the respondents above, of
the 350 respondents who met the criteria, 52% of the respondents worked as private/state
employees. Furthermore, as many as 22% work as self-employed. Then as many as 18.3%
work as students/students and finally 7.7% choose to answer and others. From this
information, it can be concluded that respondents who work as private/state employees
are the ones who fill out the questionnaire the most.
Characteristics of Respondents Based on Education Level

Figure 5

Characteristics of Respondents Based on Education Level
(Source: Data processed by researchers, 2024)

From the results of the characteristics of the respondents above, it can be seen that
out of 350 respondents, as many as 52.6% of the respondents have a final education of
strata 1. Followed by strata 2 as much as 28%. Furthermore, 16.3% of respondents who
have a high school/equivalent education and the remaining 2.6% choose strata 3. From
this data, it can be seen that the majority of respondents have the most final education
level, namely strata 1 and none of the respondents answered elementary school/equivalent
and junior high school/equivalent.
Results of the Classic Assumption Test

This test is carried out with good results so as not to violate the classical
assumptions, so all the data needed in the research must be tested first. The purpose of
the classical assumption test is to test and find out whether the regression model to be
used in this study is feasible or not. In order for a data to be said to be suitable for use,

The Effect of Personal Selling of Iconnet Products on the Buying Interest of Housing Residents
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Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 127

there are conditions that must be met, namely that the data must be distributed normally
and does not contain autocorrelation, multicoloniality and heteroscedasticity (Ghozali,
2013). For this reason, it is necessary to first perform a classical assumption test before
performing a multiple linear regression test consisting of:
Normality Test Results

Normality testing is used to analyze in a regression, independent variables and
dependent variables or both are normally distributed. This test aims to test whether in the
regression model, the perturbating or residual variables have a normal distribution. A
regression model is considered good if the data distribution is normal or close to normal.
In this study, normality testing uses the Kolmogorov Smirnov analysis technique (1-
Sample K-S). With the use of the Kolmogorov test as the basis for decision-making is
when the Asymp value. Sig. (2-tailed) > 0.05 which means that the data is distributed
normally. The results of the normality test can be seen in Figure 4.9 below.

Figure 6 Results of the Normality Test

(Source: Data processed by researchers, 2024)

Based on Figure 6 above, it can be seen that the value of Asymp. Sig. (2-tailed) is
greater than 0.05, which is 0.110, which means that the regression model data has met the
assumption of normality and is normally distributed.
Heteroscedasticity Test Results

Heterokedasticity testing is carried out to find out whether model deviations occur
because between one observation to another there are different types of disturbances. In
the scatterplot diagram, a study is stated to be non-heteroscenistic if there are no random
scattering points and a specific pattern, either below the number 0 or above the number 0
on the Y axis.

Maria Bona Putri S, Ratih Hasanah Sudrajat

Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 128

Figure 7 Heteroscedasticity Test Results

(Source: Data processed by researchers, 2024)

Based on Figure 7, it can be concluded that the dots spread up and below 0 on the
Y axis, and there is no clear pattern. If heteroscedasticity occurs, then the graph that will
be shown are the points that form a certain wave or pattern regularly spreading and then
narrowing. Therefore, it can be concluded that there is no heteroscedasticity because the
scatter plot graph in the regression model shows an unclear or irregular pattern.
Determination Coefficient Test Results

The determination coefficient (R2) test was carried out to assess the extent to which
the research model was able to explain its dependent variables. In other words, R Square
is used to measure the extent to which variations in dependent variables can be
collectively explained by independent variables.

Figure 8 Determination Coefficient Test Results

(Source: Data processed by researchers, 2024)

Based on the figure above, it can be seen that the R Square value is 0.522 which
means that Personal Selling affects Buying Interest by 52.2% and the remaining 47.8% is
influenced by other factors outside the research model.
Simple Linear Regression Test Results

Simple regression analysis aims to determine the influence of one variable on other
variables.

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Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 129

Figure 9 Simple Linear Regression Test Results

(Source: Data processed by researchers, 2024)

Based on figure 9 above, it can be explained about the relationship between the
variables of personal selling (x) and buying interest (y). The simple linear regression
equation used is Y= a+bX.
From the output, a regression equation model is obtained:

Y= 3.374 + 0.381 X

The coefficient in the simple linear regression equation above can be explained that
the regression coefficient for the constant of 3.374 indicates that if the personal selling
variable has a value of zero or fixed, then there will be an increase of 337.4% in buying
interest. Meanwhile, the personal selling variable coefficient of 0.381 indicates that every
1 unit increase in the social media use variable will increase the effectiveness of social
media use by 38.1%.
Hypothesis Test Results

Partial hypothesis testing aims to determine whether there is an influence of
independent variables on individual bound variables. The t-test basically aims to show
how far the influence of each independent variable individually in explaining the variation
of dependent variables (Ghozali, 2018). In addition, the test was also carried out using a
significant level of 0.05 (α=5%), with the criterion if the significant value < 0.05 and if
the value of Tcount > Ttable, the hypothesis was accepted. The value of the Ttable of this
study is df = 350 – 2 = 348, so the value of the Ttable is 1.649949.

Figure 10 Hypothesis Test Results

(Source: Data processed by researchers, 2024)

Maria Bona Putri S, Ratih Hasanah Sudrajat

Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 130

Based on the significance value, the result of linear regression, it is partially stated
that the significance value of the Personal Selling variable (X) is 0.000 < 0.05, meaning
that Personal Selling (X) partially has a positive and significant relationship with the
Buying Interest variable (Y). There is also a t-table value for 5% significance is df = 350
– 2 = 348, Ttable is 1.649949, so based on the t-calculation value, the test results state
that the value on the t-calculation of Personal Selling (X) is 19.509 > 1.649949 meaning
that Personal Selling has a positive and significant relationship with Buying Interest.

From the results of the research that has been obtained, it is known that each of the
variables of Personal Selling and Buying Interest has met the criteria of good data, namely
valid and reliable. This is also supported by the results of normal data distribution and
free from heterokedasticity problems.
Based on the results of descriptive analysis on the Personal Selling (X) variable,
it is known that the percentage value from the highest to the lowest percentage value is
that Sales Iconnet has good product knowledge and Sales Iconnet explains the advantages
and benefits of the product to potential consumers, both are equally valuable, while the
last position is the statement of Iconnet sales' ignorance of the background of its potential
customers by 78.4%. Based on descriptive analysis on the Buying Interest variable (Y),
it is known that the percentage value from the highest to the lowest percentage value
includes, among others, a statement of respondent's satisfaction with Iconnes sales in
offering Iconnet products with a score of 86.2%, followed by a statement with the
advantages of the product offered, you are interested in buying Iconnet products by
85.1%, while in the last position, the respondent's interest in buying Iconnet products is
83%.
From the results of the research that has been carried out, it can be concluded that
Personal Selling has an effect on Buying Interest. The results of this study were
determined from the results of the t-test and the significance test that had been carried out
related to the variable of personal interchange on buying interest, namely with a t-count
value of 19.509 and a significance of 0.000. This indicates that the t-count value of 19.509
> from the t-table value of 1.649949 and also the significance value of 0.000 < 0.05 which
indicates that it is true that personal selling has an effect on buying interest residential
residents in the city of Medan.
The coefficient of determination (R Square) is 0.522 which means that Personal
Selling affects Buying Interest by 52.2% and the remaining 47.8% is influenced by other
factors outside the research model. Overall, the results of the study stated that it is true
that personal selling affects buying interest residential residents in the city of Medan.
Personal selling involves direct interaction between sellers and buyers. It allows sellers
to answer questions, provide relevant information, and handle objections directly, which
can increase buyer confidence. In addition, in the process of personal selling, sellers can
quickly identify and address any objections or doubts that customers may have, thus
helping them feel more comfortable making purchases.

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Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 131

The results of this study are also supported by previous studies that have similar
results such as research from (Aprianto & Candraningrum, 2019) which states that
personal selling affects the buying interest of housing residents in the city of Medan. In
addition, research from (Sudradjat, 2024) also states a similar thing, namely personal
selling affects consumer buying interest, and is also supported by research from
(Syarifuddin, 2023) which states a similar thing. The relationship between personal
selling and buying interest is because personal selling allows sellers to build closer
relationships with consumers. A good relationship can increase trust and loyalty, so
consumers are more likely to buy. Sellers may provide specific and relevant information
about the product or service, including features, benefits, and how to use it. This
information helps consumers understand the value of the product and make better
purchasing decisions. Through direct interaction, sellers can receive feedback from
consumers regarding products or services. This feedback is not only beneficial for sellers
to improve their offerings, but it also shows consumers that their opinions are valued.

Conclusion

Based on the results of the study entitled "The Effect of Personal Selling of Iconnet
Products on the Buying Interest of Housing Residents in Medan City" which has been
tested using a simple regression model with a total sample of 350 respondents, the
conclusions that can be drawn include:
1. The result of the determination coefficient (R Square) is 0.522 which means that

Personal Selling affects Buying Interest by 52.2% and the remaining 47.8% is
influenced by other factors outside the research model.

2. The results of this study were determined from the results of the t-test and the
significance test that had been carried out related to the variable of personal
interchange on buying interest, namely with a t-count value of 19.509 and a
significance of 0.000. This indicates that the t-count value of 19.509 > from the t-table
value of 1.649949 and also the significance value of 0.000 < 0.05 which indicates that
it is true that personal selling has an effect on the buying interest of housing residents
in the city of Medan.

Maria Bona Putri S, Ratih Hasanah Sudrajat

Indonesian Journal of Social Technology, Vol. 6, No. 1, January 2025 132

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