International Journal of Engineering Business
and Social Science
Vol. 1 No. 03, January-February 2023, pages: 125-135
e-ISSN: 2980-4108, p-ISSN: 2980-4272
https://ijebss.ph/index.php/ijebss
125
Revenue Analysis of Travel Agent in
Palangka Raya City at the Time of Covid-19 Pandemic
Miar
1
, Muhammad Farras
2
, Sunaryo Neneng
3
, Enjel
4
1,2,3,4
Department of Economics Development, Faculty of Economics and Business,
University of Palangka Raya, Indonesia
Email: miar@feb.upr.ac.id
Submitted: 08-02-2023 Revised: 12-02-2023, Publication: 20-02-2023
Keywords
Abstract
Agency, Revenue,
Services, Covid-19
Pandemic
This purpose of this study is to quantify and evaluate how the Covid-19 Pandemic has
affected the revenue generated by travel-related transportation services in Palangka
Raya City. A qualitative descriptive technique is used in the research procedure. This
study uses the Community as its analytical unit. Observational methods, interviews,
and questionnaires were utilized to collect primary data for this study on travel services
in Palangka Raya City for 30 populations who served as samples. Using the program
SPSS 25, a non-parametric technique was used to examine the data that had been
gathered. The study's findings show that the number of travelers significantly affects
the revenue earned by travel service companies. Tariffs have a negative and negligible
effect on the revenue of travel service providers. The revenue of travel service
providers in Palangka Raya is significantly impacted by operational costs.
1. Introduction
Corona Virus Disease (Covid-19) is an infectious disease caused by SARS-CoV-2. A new type of corona
virus that has been found in humans since an extraordinary incident appeared in Wuhan, China, in December
2019. The presence of Covid-19 has an impact on global health problems, including in Indonesia. As of April
25 2020, Indonesia has reported 8,211 positive cases, 689 deaths, 1,002 recovered cases from 50,563 people
examined with 42,352 negative results (Ministry of Health, 2020b). The impact of the Covid-19 pandemic has
had an impact on the economy in Indonesia. The sectors affected during the Covid-19 pandemic were the
transportation, tourism, trade, health and other sectors, but the economic sector most affected by Covid-19 was
the household sector (Susilawati et al., 2020; Purwanto, 2020; Nalini, 2021; Sulchan et al., 2021; Nayak et al.,
2022). The impact of Covid-19 has also affected the decline in economic activity in various sectors as a result
of regulations issued by the government governing the restriction of community activities during the COVID-
19 pandemic. Establishment of Large-Scale Restrictions (LSR) which prohibits people from traveling long
distances freely, as well as restrictions on the number of passengers on public transportation. so that public
transportation companies experience a decrease in revenue due to reduced passengers. The impact of the Covid-
19 pandemic has also substantially reduced road congestion in major cities in 2020 compared to the previous
year: 36% in Los Angeles, 30% in New York and 25% in Miami (Kelly and Sharafedin, 2021). Several studies
have analyzed mobility patterns during the pandemic. Research in Colombia, (Arellana et al., 2020; Rumondor
et al., 2022; Saputra, 2022) analyzed the short-term impact of the pandemic on air, goods and urban transport.
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They found that government policies, including the ban on airplane passengers, resulted in reduced mobility,
less transit passengers, and less congestion.
In Indonesia, the implementation of the LSR requires the number of public transport passengers to only be
50% of the number of passenger seats. The purpose of limiting the number of passengers is so that passengers
can keep their distance from other passengers. The LSR policy will indeed affect the finances of transportation
services, namely the declining income of this sector and even the threat of experiencing loss/bankruptcy. The
prohibition on traveling or leaving the house during the Covid-19 pandemic has caused travel service
passengers to experience difficulties in daily operations. So that passenger transport experienced a decline in
operations by the owner. The decline in travel operations has caused vehicle owners, drivers and assistants to
experience a decrease in income. The reduced income during the Covid-19 pandemic also affected car loans
that were in arrears, the daily needs of vehicle owners, drivers and assistants were not sufficient for the needs of
their families. From the results of interviews with travel owners as car owners, drivers and assistants complain
that the vehicle operational costs that have been issued are not sufficient to cover operational costs. As a result
of the LSR and people's fear of going out of their homes, travel passengers have become lonely.
Some research that has been done before: Explaining the impact of the Covid-19 pandemic causing low
investor sentiment towards the market which in turn led the market to tend to be negative. Strategic measures
related to fiscal and monetary are urgently needed to provide economic stimulation (Nasution et al., 2020;
Sunarmin & Junaidi, 2021; Akbar et al., 2022). Stated that the condition of MSMEs during the Covid-19
pandemic continued to decline, starting from a decrease in income to production capacity. There needs to be a
policy in order to protect MSMEs so that they can remain competitive even during the Covid-19 pandemic
(Amri, 2020; Palit, 2021).
Covid-19 will greatly impact the income of travel service providers, especially in the city of Palangka
Raya. The existence of PSBB rules makes several restrictions on travel service passengers. So that the reduced
number of passengers and strict regulations have an impact on the income of travel service providers in the city
of Palangka Raya.
Literature review
Service can be defined as "any act or action that can be offered by one party to another party which is
essentially intangible and does not result in ownership of anything". Services in this case can be classified into
various criteria. Judging from the source of income, there are three kinds of classification of services. First,
services whose main source of income comes from customers, such as lodging and rentals. Second, services
whose source of income comes from donations, such as social foundations and orphanages. Third, services with
sources of income from taxes, for example government agencies.
The definition of a travel agency according to R. S. Damardjati (2010: 29; Simanjuntak & Ginting, 2018;
Fidya et al., 2022) is a company that specifically organizes and organizes trips and stopovers for people,
including the completeness of their trips, from one place to another, either within the country, from within the
country, abroad or within the country itself.
According to (Minter, 2017), tariff is the price of transportation services that must be paid by service
users, either through the mechanism of lease agreements, bargaining, or government regulations. The price of
transportation services is determined according to the tariff system, applies in general and there are no other
provisions that bind the transportation company and the owner of the goods or passengers except what has been
regulated in the tariff book.
According to Tobing et al., (2019) Business/Operational costs arise in connection with the sale or
marketing of goods or services and the administration of the general and administrative functions of the
company concerned. Income is the result of a person's livelihood or business in a day or month. According to
Winardi in the Economic Dictionary (1981); that income or income is the same as the results in the form of
money or other materials achieved from the use of wealth or free human services.
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IJEBSS Vol. 1 No.3, January-February 2023, pages: 125-135
According to the FASB (Financial Accounting Standard Board) proposed by Napier & Stadler, (2020);
Aziz & Amanda, (2021), "Revenue is an inflow or increase in asset value from an entity or settlement of
obligations of an entity or a combination of both during a certain period originating from the delivery or
production of goods, giving services for implementing other activities which are the company's ongoing main
activities.
In carrying out its activities, a company incurs expenses for its operational activities. Operating expenses
are economic benefits during an accounting period in the form of outflows or reductions in assets or the
occurrence of liabilities resulting in a decrease in equity that does not involve distribution to investment.
Expenses are outflows of assets or other uses of assets or the incurrence of liabilities of the entity (or a
combination of both) resulting from the delivery or manufacture of goods, rendering of services, or other
activities that constitute the company's main or central operations. Expenses are an increase in the number of
assets caused by the sale of company products. The type of income owned by the company will be largely
determined by the line of business the company is engaged in.
With the presence of the Covid-19 outbreak, the Indonesian government acted through strategic policies to
suppress the spread of Covid-19 in the public. Therefore, the central government implemented a policy of
implementing large-scale social restrictions (LSR) until there was a lock down policy in several regions
including Central Kalimantan Province. This is confirmed by Central Kalimantan Governor Regulation Number
43 of 2020, concerning the Implementation of Discipline and Law Enforcement of Health Protocols in the
Prevention and Control of Covid-19 which limits the public from doing activities outside the home to minimize
the spread of Covid-19 including limiting and even delaying traveling activities. and traveling to reduce the
transmission rate of the Covid 19 virus, which has an impact on the travel agency sector, one of which is travel
agents or travel service providers in the city of Palangka Raya.
Theoretical Thinking Framework
Based on the description and formulation of the problem above, the hypotheses proposed in this study are:
1. It is suspected that the Covid-19 pandemic will affect the number of passengers.
2. It is suspected that the Covid-19 pandemic will affect Tariffs
3. It is suspected that the Covid-19 pandemic will affect Operational Costs
2. Research Method
Data collection with this quantitative descriptive method was carried out by means of a direct survey to
the field by distributing questionnaires to travel owners. The distributed questionnaire contains a number of
questions and answers that must be selected and filled out by respondents.
This research will be carried out at CV (commanditaire Vennotschap) and in several limited companies
providing travel services in the city of Palangka Raya. The sample used in this study is a saturated sample or
total sample, namely sampling by taking the entire population, usually done if the population is considered
Revenue
Travel Bureau
Covid-19
Total passenger
Tariff
Operating costs
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small or less than 100, where the population in this study is 30 people including the travel agent entrepreneur
and several employees in the business. Travel services in the city of Palangka Raya.
The data analysis methods used are: 1) Descriptive Analysis According to Sugiyono, (2012) descriptive
analysis method is a statistic used to analyze data by describing or describing the data that has been collected as
it is without intending to make conclusions that apply to the general public or generalizations. 2) Classical
Assumption Test is carried out so that the processed sample data can truly represent the population as a whole.
Several assumption tests in this research are Normality Test, Multicollinearity Test and Heteroscedasticity Test.
3) Multiple regression analysis is a study of the dependence of the dependent variable with one or more
independent variables, with the aim of estimating the population mean or the average value of the dependent
variable based on the known value of the independent variable. The results of the regression analysis in the
form of coefficients for each independent variable. 4) Individual Parameter Significant Test (t-test) to test how
far the influence of the independent variables used in this study individually in explaining the dependent
variable partially. 5) F-test shows whether all independent variables together have a significant effect on the
dependent variable, and 6) Test R2.
3. Results and Discussions
The economic impact associated with the pandemic generated unemployment rates that exceeded the
Great Recession of 2008 in the first three months of the pandemic (Kochhar, 2020). The Covid-19 pandemic
has claimed a large number of victims in all countries and the devastating impact is unprecedented. Impact of
the Covid-19 pandemic, research has been conducted on who is more likely to be unemployed during the
pandemic and found certain populations including racial/minorities, women, immigrants, and the less educated
are disproportionately affected (Beland et al., 2020; Cowan, 2020; Fairlie et al., 2020; Montenovo et al., 2022).
Research has also shown this impact is associated with work in occupations with an inability to work remotely
(Montenovo et al., 2022; Asfaw, 2022; Aloisi & De Stefano, 2022; Kruse et al., 2022). The pandemic has also
had an important impact on transport activity (Arellana et al., 2020; Vickers, 2017; (Riggs & Appleyard, 2020).
The same research on the impact of Covid-19 on the transportation sector also has an impact in three areas,
namely: mobility trends, use of public transport, and equity in the impact of changes in transportation. Other
studies have also found a decrease in the availability and use of multiple modes of transport, including air, long-
distance rail, road, water, and public transport (Cullinane & Haralambides, 2021; Islam, 2020; Rothengatter et
al., 2021; Sun et al., 2020). Later other studies have also found changes in public transport availability to have a
negative impact on low-income and vulnerable populations (DeWeese et al., 2020; Wilbur et al., 2020). In
addition, previous studies have also revealed that transport-related jobs have low employability, indicating
greater economic and health risks for transport sector jobs (Xia et al., 2016; Meersman & Nazemzadeh, 2017;
(Meersman & Nazemzadeh, 2017; Dingel & Neiman, 2020; 2021; Simcock et al., 2021).
The impact of the Covid-19 pandemic has also occurred in the travel transportation business in the city of
Palangka Raya. Based on information from non-bus (four-wheeled) travel entrepreneur informants, the average
income of passenger transportation before the Covid-19 pandemic generally ranged from Rp. decreased to <
500 thousand in one trip. This is due to the government's policy of implementing Large-Scale Social
Restrictions (LSR) during the Corona Virus pandemic. In the field of transportation, the number of non-bus
travel passengers is also limited with a 50% decrease in passengers and bus transportation is also reduced by
30% in accordance with the bus capacity.
The data analyzed are:
Descriptive analysis
Age of Respondent
Respondents in this study amounted to 30 people who are Owners, Admins, and Drivers in Travel Services
Businesses. Descriptive results based on the following Position / Position in Travel Companies:
Table 1
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IJEBSS Vol. 1 No.3, January-February 2023, pages: 125-135
Characteristics of respondents based on positions in Travel Companies
Position
Amount
Percentage
Owner
14
46,7%
Admin/Operator
12
40,0%
Driver
4
13,3%
Total
30
100%
Sources of data processed by researchers based on the results of the survey
From the results of the descriptive data processed based on the table above, it shows that the more dominant
respondent is the owner of the Travel Service Business which has a percentage of 46,7% and the second dominance
is by Admin/Operator of 40,0% and the lowest is the Driver or Travel Service Driver of around 13,3%.
The average and total number of passengers, fares, operating costs and income of travel businesses in the
city of Palangka Raya based on the results of research conducted on 27 samples, the travel service business in the
city of Palangka Raya obtained data on the amount of income, tariffs, passengers, and Operational Costs are shown
in table 2 below.
Table 2
Passengers, Fares, Operating Costs, and Travel Business Income in one month
No
Passenger
(Per-day)
X1
Tariff
(X2)
Operational
Cost
(Monthly)
X3
Income
(Monthly)
Y
1
7
250.000
3.500.000
7.000.000
2
7
250.000
2.500.000
6.000.000
3
6
110.000
2.000.000
5.500.000
4
6
190.000
1.500.000
3.200.000
5
6
200.000
1.000.000
3.000.000
6
30
250.000
40.000.000
150.000.000
7
30
225.000
50.000.000
250.000.000
8
7
200.000
15.000.000
60.000.000
9
6
200.000
1.500.000
3.000.000
10
7
190.000
3.000.000
6.500.000
11
6
200.000
3.500.000
5.000.000
12
7
100.000
3.100.000
6.800.000
13
6
150.000
2.000.000
4.800.000
14
7
200.000
3.500.000
7.200.000
15
6
150.000
2.000.000
6.500.000
16
7
250.000
1.000.000
3.100.000
17
6
200.000
1.800.000
3.500.000
18
7
190.000
4.000.000
7.000.000
19
7
200.000
2.800.000
5.800.000
20
6
200.000
1.500.000
3.700.000
21
7
200.000
2.000.000
5.000.000
22
7
130.000
6.000.000
15.000.000
23
6
190.000
1.500.000
3.000.000
24
6
200.000
6.500.000
25.000.000
25
30
190.000
50.000.000
280.000.000
26
6
200.000
5.600.000
18.000.000
27
7
190.000
1.000.000
2.800.000
28
5
150.000
1.600.000
3.000.000
29
5
180.000
1.100.000
2.000.000
30
7
150.000
900.000
2.300.000
Total
263
5.685.000
2.214.000
903.700.000
Average
8,76
189.500
738.000
3.123.333
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Sources of data processed by researchers based on the results of the survey.
Based on the table data above, it can be seen that the total income of Travel Service Providers in Palangka
Raya City is Rp. 903.700.000 with an average of Rp. 3.123,333 with 263 passengers with an average of 8,76, for a
total passenger fare of Rp. 5.685,000 with an average of Rp. 189,500 and for a total of Rp. 2.214,000 with an average
of Rp. 738.000.
Classic assumption test
Table 3
Normality test
Normality Test Measurement Results
One-Sample Kolmogorov-Smirnov Test
Unstandardized Residual
N
27
Normal Parameter, b
Mean
,0000000
Std.
Deviation
,10296176
Most Extreme
Differences
Absolute
,116
Positive
,116
Negative
-,102
Test Statistic
,116
Asymp. Sig. (2-tailed)
,200c,d
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.
d. This is a lower bound of the true significance.
Based on the table of normality test above, namely the Plygon image, the probability plots show that they are
normally distributed, because the line (dots) follows a diagonal line. ). Based on these results, it can be concluded
that the results of the regression model have met the assumption of normality.
Table 4.
Multicollinearity Test
Multicollinearity Test Results
Coefficientsa
Model
Unstandardized
Coefficients
Standa
rdized
Coeffi
cients
Collinearity
Statistics
B
Std.
Error
Beta
Toler
ance
VIF
1
(Constant)
,777
1,431
X1
,086
,194
,034
,264
3,785
X2
-,183
,249
-,030
,905
1,105
X3
1,079
,084
,957
,278
3,597
A Dependent Variable: LG10_Y
Based on table of Multicollinearity Test Multicollinearity Test Results Tolerance value result <0,10 and value
Variance Inflation Factor (VIF) >0,10 then it can be said that there is no multicollinearity between independent
variables.
Figure 3
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Heteroscedasticity Test
Based on the results of the SPSS output, it is known (the scatterplot image) above that the points spread below
and above the Y axis, and do not have a regular pattern, so it can be said that the independent variables are the
number of passengers (X1), fares (X2), and operational costs (X3).) there is no heteroscedasticity or
homoscedasticity.
Multiple Linear Analysis
The dependent variable in this study is the purchase decision, while the independent variables are price and
product quality. Multiple regression analysis formula as follows:
Y= a+ b1X1 + b2X2+ b3X3
Table 5
Regression Value
Coefficients
a
Model
Unstandardized
Coefficients
B
Std. Error
1
(Constant)
-1,243
,696
X1
-,181
,094
X2
,180
,121
X3
,082
,041
a. Dependent Variable: ABS_RES
Based on the results of data processing using SPSS IBM 25, a constant coefficient value of -1,243 was
obtained, the coefficient of the number of passengers was -0,181, the fare coefficient was 0.180, and the operational
cost coefficient was 0,082. Then the regression equation can be formulated as follows:
Y= -1,243-0,81X1+0,180X2+0,082X3
Test F
The F-test was conducted to see whether or not the independent variables (Number of Passengers, Fares, and
Operating Costs) were bound together (Amount of Revenue) together.
Table 6
The table below is the result of the F test.
Results Test F
ANOVAa
Model
Sum
of
D
f
Mean
Square
F
Sig.
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Square
s
1
Regr
essio
n
7,539
3
2,513
209,69
8
,000
b
Resi
dual
,276
2
3
,012
Tota
l
7,815
2
6
a. Dependent Variable: LG10_Y
Predictors: (Constant), LG10_X3, LG10_X2, LG10_X1
From the ANOVA test with SPSS IBM 25 based on the table above, there are: Fcount. Is 209,698. Based on
table F with a significance level of 5%, it is known that Ftable with n-k-3= 27 – 3=25 then Ftable = 2.050. Based on
the calculation results obtained that Fcount >Ftable. This shows that Ho is rejected and Ha is accepted. Based on this,
it can be concluded that the number of passengers, fares, and operational costs together are able to predict the impact
of Covid-19 on travel income in Palangka Raya City.
Test T
Partial test is used to determine how much influence the independent variables individually in explaining the
dependent variable. This test is carried out by looking at the significance <0,05 it can be concluded that the
independent variable significantly affects the dependent variable.
4. Conclusion
Based on the results of data analysis obtained with 30 samples and 27 data on the amount of data regarding the
Impact of Covid-19 on Travel Service Business Revenue in the City of Palangka Raya which has been described in
the previous chapter, the following conclusions are The Variable Number of Passengers has a significant and
negative effect on travel service business revenues during the Covid-19 pandemic, Tariff variable has a negative and
insignificant effect on travel service business income during the Covid-19 pandemic and Operational costs have a
significant effect on business income for the Covid-19 Pandemic Travel.
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