Analysis of Factors Affecting the Income of MSMEs Marketing

Products through Gojek during the Covid Pandemic

Shinta Wahyu Hati and Maulia Anishafitri

Department of Business Management, Politeknik Negeri Batam, Jl Ahmad Yani, Batam, Indonesia

Keywords: Factor Analysis, MSMEs, Gojek

Abstract: The purpose of this study is to test what factors affect the income of MSMEs who market products through

Gojek during the pandemic. Data retrieval and collection techniques using google form. As for data analysis

methods using factor analysis. The results of this study showed that there are 32 statement indicators that are

in rotation into 6 new factors formed including the capital factor (X1) has the highest loading value of

0.763,the wage or salary factor (X2) has the highest loading value of 0.723,the resource factor(X3) has the

highest loading value of 0.827,thefactor Raw materials (X4) have the highest loading value of 0.745,labor

quality factor (X5) has the highest loading value of 0.730 and utilization factor (X6) has the highest loading

value of 0.755. Then the most dominant MSME income factor influences the factor with a percentage of

variance value of 47,797%.

1 INTRODUCTION

The important role of the existence of MSMEs in

Indonesia is increasingly felt in the process of

national economic development in Indonesia. At first,

the existence of MSMEs was considered an important

source in the creation of job opportunities. However,

in the current and future era of globalization, the role

of the existence of MSMEs is increasingly important,

namely as one of the sources of non-oil and gas export

foreign exchange. During this time MSMEs also play

a role in times of crisis. The existence of small and

medium-sized businesses is the main driving factor of

the Indonesian economy. Especially in times of crisis

investment activities and government spending are

very limited, then the role of small and medium

enterprises as one form of the people's economy.

(Tambunan, 2020).

According to data from the Central Statistics

Agency in 2020, the number of MSMEs from Batam

city as many as 81,575 business actors. Currently the

total number of business actors from all districts and

cities in Riau Islands Province is 112,155.

In the business world in the era of globalization,

the sale of products (including goods and services)

can all take advantage of advances in information

technology. Information technology products can

provide the best benefits for business people. Online

marketing and sales done through the internet or

Internet e-commerce has become one of the important

content in business, especially in marketing. Online

marketing through the media is the right step that

must be done by business people (Suswanto &

Setiawati, 2020).

As a leading technology company in Indonesia,

Gojek again shows its commitment to helping

MSMEs expand market share and expand business

scale. The launch of Gojek entrepreneur can reflect

commitment. Gojek entrepreneur is a business

training program that provides a knowledge base in

building a business to promote MSME participants in

Indonesia by entering the digital world. According to

data from the Ministry of Cooperatives and Small and

Medium Enterprises of the Republic of Indonesia in

2018, there are 99% of industries in Indonesia

assisted by MSMEs. MSMEs also have 62 million

units to create employment opportunities.

Efforts to support MSMEs to jump into online

business in the midst of this pandemic are just the first

step. Gojek will present various other innovations to

support MSMEs which are the backbone of the

Indonesian economy. A total of 113 small and

medium enterprises (MSMEs) in Batam City

participated in the Go-Digital IKM program held by

Gojek in collaboration with the Ministry of Industry

and Trade (Disperindag) and the Regional National

Craft Council (Dekranasda) of Batam City. The

Wahyu Hati, S. and Anishaﬁtri, M.

Analysis of Factors Affecting the Income of MSMEs Marketing Products through Gojek during the Covid Pandemic.

DOI: 10.5220/0010935300003255

In Proceedings of the 3rd International Conference on Applied Economics and Social Science (ICAESS 2021), pages 80-91

ISBN: 978-989-758-605-7

program begins with the registration of participants to

become Gofood and Goshopmerchants. Through the

Go-DigitalIKM program, Gojek provides a series of

training to improve the durability of MSMEs from

prolonged pandemic exposure. This effort is a

collaboration that has a positive impact on small and

medium-sized industry players, especially in

increasing the durability of small and medium-sized

industries.

Gofood managed to increase the turnover of

74,000 business partners through various popular

cooking promotions through the HARKULNAS

program held from April 1 to May 5, 2020. Compared

to unplanned merchants, Gofood orders and turnover

were higher (12%). Batam, Jabodetabek and

Surabaya had the highest transaction growth during

the program period. Through the HARKULNAS

program, GoFood has launched many programs to

increase daily sales of MSMEs while reducing

business costs. Gofood supported MSME efforts

during the pandemic. Since the beginning of May,

GoFood's overall transaction volume has increased

10% compared to the previous week in April.

Based on this phenomenon, researchers are

interested in researching more about the influence

caused by MSME income. The title taken is "Analysis

of factors that affect the income of MSMEs who

market products through Gojek during the

pandemic".

2 LITERATURE REVIEW

2.1 Revenue

Income depends on the increase or increase in assets

and the decrease or decrease in the company's

liabilities which are the result of operating activities

or procurement of goods and services to the

community or boarding in particular. (Harnanto,

2019).

2.2 Capital

Capital is a factor of production that has a strong

influence in obtaining productivity or output, macro

capital is a big driver to increase investment both

directly in the production process and in production

infrastructure, so as to encourage increases in

productivity and output. (Meij, 2018).

2.3 Labour

According to the Law on Employment No. 13 of

2003, labour is a person who is able to produce goods

and services that can meet his own needs and meet the

needs of his family. In "Law No. 25 of 1997", workers

are residents aged 15 years and over. According to the

latest employment law, in 2013 there was no age limit

for the definition of labour, but the law prohibited the

employment of children.

2.4 Raw Materials

Raw materials are the main ingredients in the

production process until the finished product. Raw

materials include all commodities owned by the

company and used in the production process (Singgih

Wibowo, 2007: 24). Activities can determine the

level of inventory in raw materials and products so

that the company can effectively protect the smooth

production process and effectively meet the

company's sales and expenditure needs.

2.5 Information Technology

Over time, conditions continued to evolve especially

in the field of computer networks, and information

and communication technology (ICT) also evolved.

Information technology is defined as processing data

in various ways, obtaining, compiling, storing, and

processing data in order to provide quality, relevant,

accurate, and timely information for personal,

corporate, and government purposes in decision

making. (Hasibuan et al., 2020).

2.6 MSMEs

In accordance with Law number 20 of 2008

concerning Micro, Small and Medium Enterprises

(MSMEs), MSMEs are defined as follows: micro-

enterprises are productive businesses owned by

individuals and/or individual business entities that

have met the criteria for Micro-enterprises. Small

Business is a stand-alone business, or a business

entity that is not a subsidiary managed by an

individual or not a branch of a company that is owned,

controlled, or becomes a part either directly or

indirectly of a Medium or Large Business and meets

the criteria of a Small Business as stipulated stated in

the Act.

Medium business is a productive economic

business that stands alone, which is carried out by

individual branch companies that are owned, or

controlled, either directly or indirectly with Small

Analysis of Factors Affecting the Income of MSMEs Marketing Products through Gojek during the Covid Pandemic

Businesses or Large Businesses with a total net worth

or annual sales results (Sudati, 2019).

MSME is a form of productive economic business

carried out by individuals or individual business

entities that have met the criteria of Micro, Small, and

Medium Enterprises (Suryani E, 2021).

The characteristics of MSMEs are using simple or

manual technology so that technology transfer is

easy, raw materials are easy to obtain, have basic

skills that are generally obtained from generation to

generation, market opportunities are wide enough, are

labour intensive or absorb a large number of workers,

most of their products are marketed in Indonesia.

local or domestic market and some other parts have

the potential to be exported (Halim, 2020)

2.7 Gojek

Gojek as a transportation that can be ordered through

a smartphone. Gojek, iOS and Android applications

through www.GoJek.com. In addition, another

interesting thing is that there is one of the functions in

this application that is shopping that can help you

shop anywhere and anywhere. Gojek's presence

provides jobs for some people who lose their jobs, but

own motorcycles. (Kuswanto et al., 2019).

2.8 Covid-19 Pandemic

The Covid-19 pandemic was first reported by

officials in the Chinese city of Wuhan in December

2019. Coronavirus (Covid-19) is an infectious disease

caused by a newly discovered virus. Many residents

are infected with viruses that experience respiratory

diseases without requiring special treatment. At the

age of 40 years and above usually have internal

diseases such as diabetes, asthma, heart, and cancer to

develop more serious diseases. (World Health

Organization, 2020).

2.9 Research Framework

Figure 1: Research Framework.

3 METHODS

3.1 Design, Population, and Research

Samples

The study used quantitative methods using factor

analysis. According to Supranto (2013). The

engineering analysis used is factor analysis which is

a multivariate statistical method designed to explain

the relationship between several independent

variables so that one or more sets of modifiers can be

generated with a number of variables that are less than

the initial number.

The population in this study is MSMEs who

market their products through the Gojek platform.

Sampling technique uses incidental sampling using

the formula Lemeshow, this is because the number of

populations is unknown or infinite, so a sample of 100

people is obtained

3.2 Variable Operations

Operationalization of this research variable adopted

from Endang Purwanti (2018), Joko Jasinar Silalahi

(2018 Pitri Komalasari, Enas Enas, Enjang Nursolih

(2020), Halifa Haqqi, Andika Drajat Murdani (2021).

Table 1: Variable Operationalization.

Variable Indicators

Capital (X1)

Capital as the main condition (X1.1)

Capital Utilization (X1.2)

Capital (X1.3)

Labour (X2)

Qualit

of work

(

X2.2

)

Gender (X2.3)

Labour wa

es or salaries

(

X2.4

)

Raw Materials

(X3)

Estimated use of Raw Materials

(

X3.1

)

Raw material

rice

(

X3.2

)

Real usa

(

X3.3

)

Waiting time (X3.4)

Information

Technology

(X4)

Can improve market

com

etitiveness

(

X4.1

)

Lower o

eratin

costs

(

X4.2

)

Range (X4.3)

Increase customer lo

alt

(

X4.4

)

rove

mana

ement

(

X4.5

)

ICAESS 2021 - The International Conference on Applied Economics and Social Science

3.3 Types and Data Sources

Data is raw material that needs to be processed to

produce factual information or qualitative and

quantitative information. Data from the source of the

collection is divided into two parts, namely:

1. Premier Data

According to Sugiyono (2018) is a data source

that directly provides data for data collection.

Premier data source is a source of data obtained

directly from the original source without

intermediaries. This data requires questionnaires.

2. Secondary Data

According to Sugiyono (2018) is a data source and

does not directly provide data collection, such as

through others or through documents. The

secondary data for this study comes from previous

research.

3.4 Data Analysis Method

The tests used in this study used factor analysis tests.

The factor analysis test is one of the interdependent

analyses between variables. Factor analysis is a

model in which no variable is divided into free

variables and bound variables, but to look for

interdependence between variables to determine the

dimensions or factors that make up them.

Factor analysis is used to reduce data or

summarize, from old variables that have been

changed to a few new variables called factors, and

still contain most of the information contained in the

original variables (Supranto, 2004).

4 RESULTS AND DISCUSSIONS

4.1 Gojek Helps MSMEs during

Pandemic

Throughout 2020, Gojek released a series of digital

solutions to make it easier for small, medium- and

micro businesses to migrate to online businesses.

Through Gojek's joint #Melaju project, thousands of

small, medium and micro businesses are increasingly

aware of the importance of digital technology in

business and successfully survive pandemics.

Learning from this success, Gojek shares recipes and

business trends that are expected to be in high demand

in 2021 to further encourage MSMEs to move

forward.

The COVID-19 pandemic has awakened

everyone, including MSMEs, about the importance of

opening businesses on digital platforms. This is seen

in one day, up to 3,000 MSMEs register to become

Gojek merchants. Nonetheless, there are still many

budding entrepreneurs who need support to continue

to improve their business. Gojek will continue to

work even harder to give birth to technological and

non-technological innovations that help MSMEs

from all fronts and at every stage of the business.

4.2 Gojek Features and Services

To date, Go-Jek has provided 23 services, namely:

1. Go-Ride, Motorcycle transport service.

2. Go-Car, Car transportation service.

3. Go-Buebird, a transportation service that can be

booked without having to book conventionally.

4. Go-Send, Instant Courier Service.

5. Go-Box, Service moves large size goods.

6. Go-Transit, a service to facilitate its multimodal

travel

7. Go-Food, Food delivery service.

8. Go-Shop, a service for shopping for any food that

is not listed on the Go-Food service

9. Go-Mart, a service for shopping for thousands of

types of goods.

10. Go-Pulsa, a service for buying credit or internet.

11. Go-Nearby, a service that makes life easier for the

closest business associates who can use Go-Pay.

12. Go-Bill, Service to pay water bills, BPJS, dl.

13. Go-Give, Services for donating, zakat, infaq san

alms (ZIS) and zakat calculator.

14. Go-Sure, a service that provides a wide range of

insurance products.

15. Go-Investment, Services to invest.

16. Go-Fitness, Services to improve the development

of the sports industry in Indonesia.

17. Go-Service, a service that focuses on vehicle tax

payment services.

18. Go-tickets, Ticket purchase access service

directly into your hands.

19. Go-Play, a Service that serves local content.

20. Go-News, a service that presents a number of up-

to-date news about events that occur.

21. Go-Greener, Indonesian Plastic Bag Diet

Movement (GIDKP) to educate Go-Food

customers.

22. Go-Club, Loyalty program service can be

followed by Gojek users as members who will get

points(rewards)

23. Go-Med, instead connecting users with more than

1000 pharmacies.

Analysis of Factors Affecting the Income of MSMEs Marketing Products through Gojek during the Covid Pandemic

4.3 Statistics Descriptive

4.3.1 Characteristics of Respondents based

on Income Per-month

Figure 2: Income per month.

It can be concluded that the average income per

month of respondents is highest >5,000,000 which is

as much as 46%.

4.3.2 Characteristics of Respondents based

on Length of Business

Figure 3: Length of Business

It can be concluded that the average length of effort

of the highest respondents >4 years is as much as

52%.

4.3.3 Characteristics of Respondents based

on Business Type

Figure 4: Type of Business

It can be concluded that the average type of effort of

the highest respondents of food is as much as 86%.

4.3.4 Characteristics of Respondents based

on Age

Figure 5: Age

It can be concluded that the average age of the highest

respondents >31 years is as much as 48%.

4.3.5 Characteristics of Respondents Based

on Gender

Figure 6: Gender

It can be concluded that the average gender of

respondents is equally male and female which is as

much as 58%.

4.3.6 Characteristics of Respondents based

on Length of Promoting Business

Products in Gojek

Figure 7: Length of Promotion Business Product in Gojek.

It can be concluded that the average length of

promoting business products in Gojek is the highest

respondent 2 years as much as 40%.

ICAESS 2021 - The International Conference on Applied Economics and Social Science

4.3.7 Characteristics of Respondents based

on Duration of Intense Market

Promotion during Pandemic

Figure 8: Duration of Intense market Promotion During

Pandemic.

It can be concluded that on average during the

pandemic you intensely market and make promos on

Gojek the highest respondent YA year which is as

much as 32%.

4.3.8 Characteristics of Respondents based

on Order Frequency from Regions

Figure 9: Order Frequency.

It can be concluded that the average often gets orders

from the highest respondent area of Batu Aji which is

as much as 20%.

4.4 Description of Variables

4.4.1 Description of Capital Variables

Figure 10: Mean Description of Capital Variables.

Based on the bar chart image, it can be seen that the

statement that has the highest mean value is the

statement (X1.2) regarding where this statement has

a mean value of 3.16 so that it can be stated that the

respondent's answer feels very good.

4.4.2 Description of Labour Variables

Figure 11: Mean Description of Labour Variables.

Based on the bar chart image, it can be seen that the

statement that has the highest mean value, namely the

statement (X2.4) regarding the labour pandemic that

I have is able to encourage business productivity

where this statement has a mean value of 3.08 so it

can be stated that the answer respondents feel very

good.

4.4.3 Description of Raw Material Variables

Figure 12: Mean Description of Raw Material Variables.

Based on the bar chart image, it can be seen that the

statement (X3.1) regarding the pandemic period using

raw materials effectively and efficiently can reduce

the supply of raw materials where this statement has

a mean value of 3.37 so it can be stated that the

respondent's answer feels very good. good.

Analysis of Factors Affecting the Income of MSMEs Marketing Products through Gojek during the Covid Pandemic

4.4.4 Description of Information Technology

Variables

Figure 13: Mean Description of Information Technology

Variables.

Based on the bar chart image, it can be seen that the

respondent's answers are in the very good category

and the statement that has the highest mean value is

the statement (X4.7) regarding in the pandemic

period offering products to customers need, so as to

satisfy customers where this statement has a mean

value. of 3.65 so that it can be stated that the

respondent's answer feels very good.

4.5 Factor Analysis

The analysis of factors in this study was conducted in

order to know specifically or specifically what new

factors will be formed in the income data group of

MSMEs who market their products through Gojek so

that it can be a decision which factors are dominantly

influential.

Calculation of factor analysis in this study using

the help of SPSS application program version 25. The

Feasibility Test Stage and the Factor Extraction Stage

are tested as follows:

4.5.1 Kaiser-Meyer-Olkin (KMO) and

Barlett’s Test

KMO Measure of sampling adequacy must be ≥ 0.5

so that factor analysis can be further processed.

Barlett's Test of Sphericity is a test used to test

interdependence between variables that are indicators

of a factor. This analysis intends to state that the

variables in question are not correlated with each

other in the population. Significance in Barlett's test

must also indicate a < of 0.05 for a factor analysis to

be performed. The results of KMO and Bartlett's Test

in this study can be seen in the following table:

Table 2: KMO and Barlett’s Test Results KMO.

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of

Sam

lin

Ade

uac

.791

Bartlett's Test

of Sphericity

Approx. Chi-

uare

1274.189

Df 496

. .000

4.5.2 MSA (Measure Sampling of

Adequacy)

The result of calculating the value of MSA (Measure

of Sampling Adequacy) is a table that is indicated by

a number of numbers that form a diagonal marked "a"

that indicates the number MSA (Measure of Sampling

Adequacy) a variable or indicator. According to

Santoso (2012) If the MSA number is a variable

below 0.5 then the variable must be issued and also

repeat the selection of variables

Table 3: MSA Results (Measure Sampling of Adequacy).

Indicators MSA value

X1.1 0.638

X1.2 0,703

X1.3 0,632

X1.4 0,668

X1.5 0,701

X1.6 0.800

X2.1 0.738

X2.2 0.774

X2.3 0.596

X2.4 0,808

X2.5 0.575

X2.6 0,586

X2.7 0.764

X2.8 0,653

X3.1 0.773

X3.2 0,912

X3.3 0,859

X3.4 0.855

X3.5 0,736

X3.6 0,822

X3.7 0.856

X3.8 0,801

X4.1 0.786

X4.2 0.845

X4.3 0,842

X4.4 0,832

X4.5 0.853

X4.6 0,720

X4.7 0.873

X4.8 0.708

X4.9 0.786

X4.10 0.776

ICAESS 2021 - The International Conference on Applied Economics and Social Science

4.5.3 Communalities

The communalities of each indicator can at least

account for a minimum of 50% or 0.5 diversity of data

from the origin variable. The factor extraction method

used in the study was Principal Components Analysis

(PCA). The following is a table of Communalities

results that show variations of the indicators, namely

as follows:

Table 4: Communalities.

Communalities

Initial Extraction

X1.1 1.000 .605

X1.2 1.000 .815

X1.3 1.000 .875

X1.4 1.000 .758

X1.5 1.000 .778

X1.6 1.000 .649

X2.1 1.000 .554

X2.2 1.000 .717

X2.3 1.000 .579

X2.4 1.000 .794

X2.5 1.000 .542

X2.6 1.000 .734

X2.7 1.000 .781

X2.8 1.000 .810

X3.1 1.000 .690

X3.2 1.000 .704

X3.3 1.000 .713

X3.4 1.000 .807

X3.5 1.000 .791

X3.6 1.000 .634

X3.7 1.000 .669

X3.8 1.000 .758

X4.1 1.000 .657

X4.2 1.000 .653

X4.3 1.000 .672

X4.4 1.000 .723

X4.5 1.000 .704

X4.6 1.000 .708

X4.7 1.000 .733

X4.8 1.000 .715

X4.9 1.000 .572

X4.10 1.000 .766

4.5.4 Total Variance Explained

Total Variance Explained is used to determine how

many factors will be formed with the determination

of the value on the Total Initial Eigenvalues must

have a value of at least 1,000. The total variance

explained calculation results are displayed in the table

as follows:

Table 5: Total Variance Explained.

4.5.5 Scree Plot Graphic

A scree plot graph is a graph that shows the number

of components or factors that can be formed as a

follow-up explanation in previous Total Variances

Explained used to determine the intersection of the X

and Y axes of components or factor 1 with Total

Initial Eigenvalues. The following is an appearance of

the scree plot graph formed from the results of this

study, namely:

Figure 14: Scree Plot Graphics.

4.5.6 Factor Rotation Stage

This stage or step is a way to ensure a variable

indicator enters into which factors can be seen by

determining the largest correlation value between the

variable indicator and the component or factor

formed. The rotation of factors in this stage uses the

varimax method. The following is a table that shows

the results of the analysis of rotation model factors

obtained, namely:

Analysis of Factors Affecting the Income of MSMEs Marketing Products through Gojek during the Covid Pandemic

Table 6: Stage Rotation Factor.

4.5.7 Grouping and Interpretation of Factors

After rotating factors, the next step is to interpret the

factors that have been formed. This is done in order

to represent the member variables formed. According

to Suliyanto (2005), naming factors that have been

formed in factor analysis can be done in the following

ways:

1. Provide the names of factors that can represent

the names of the variables that make up those

factors.

2. Give the name of the factor based on the variable

that has the highest loading factor value. This is

done when it is not possible to name a factor that

can represent all the variables that make up the

factor.

After all stages of factor analysis were carried out,

from 32 indicators, 6 new factors were formed in this

study.

4.6 Discussion

The following are the details and analysis of the

factors which show that there are 6 new factors

formed by 32 original variable indicators, namely as

follows:

4.6.1 The First Factor, the Capital Factor

As for the relationship with capital factors in this

study, capital factors are related to something that can

be used to support the production process or so on.

Capital can be in the form of money, equipment and

so on. Capital has a very important role in economic

activity, especially the production process. If there is

no capital, the production process will be hampered

or cannot be carried out. Capital can be obtained

independently, such as working or saving. However,

it can also be obtained from the assistance of other

parties, such as borrowing from a bank.

Based on the research, capital factor analysis is

included in the factor with the first highest loading

value. Based on the first factor grouping on the

indicator after factor rotation, there are 8 items

including X1.1, X1.2, X1.6, X3.6, X4.1, X4.3, X4.5

and X4. 7 with the statement "My working capital

comes from personal capital". has the highest

contribution. Based on descriptive statistics, the

average capital variable is in the positive or good area

with a value of 3.09.

4.6.2 The Second Factor, Wage, or Salary

Factor

As for the wage or salary factor in this study, namely

the size of the wage or salary in a business, it cannot

be seen and measured only from one or several

aspects. There are several factors that can influence

such as high and low productivity or products

produced, skills at work, responsibilities at work and

so on.

Based on the analysis of wage or salary factors, it

is included in the factor with the second highest

loading value. Based on the results of grouping the

second factor on the indicator after factor rotation,

there are 6 items including X2.1, X2.2, X2.3, X2.5,

X2.6 and X2.7 with the statement "During the

pandemic, there is a difference in wages or full-time

and part-time salary.” Has the highest contribution.

4.6.3 The Third Factor, Resource Factor

As for the relationship with the resource factor in this

study, the resource is also a very important type of

factor. Because it is impossible for raw materials to

become semi-finished materials and then finished

products/goods if there are no humans to process

them. Resources are arguably the most important

point in production. Even though there are some

arguments that performance can be replaced by

robots. But of course, in terms of taste and soul,

humans are much greater. It is undeniable that this

taste and soul also makes the product higher quality.

Based on the research of resource factor analysis,

it is included in the factor with the third highest

loading value. Based on the results of grouping the

third factor on the indicator after factor rotation, there

are 5 items including X4.4, X4.6, X4.8, X4.9 and

X4.10 with the statement "Optimizing the use of

ICAESS 2021 - The International Conference on Applied Economics and Social Science

resources during the pandemic so that it can be

efficient in financing.” Has the highest contribution.

4.6.4 The Fourth Factor, Raw Material

Factor

As for the relationship with the raw material factor in

this study, the raw material is an important factor that

determines the level of cost of goods and the

smoothness of the business production process. Raw

materials are required to be processed, which after

going through several processes are expected to

become finished goods. From the estimated usage, the

price of raw materials, the actual usage is some of the

factors that can affect the raw materials.

Based on the research of factor analysis, raw

materials are included in the factor with the fourth

highest loading value. Based on the results of

grouping the fourth factor on the indicator after factor

rotation, there are 5 items including X3.1, X3.2, X3.3,

X3.4, and X3.5 with the statement "Changes in raw

material prices during the pandemic affect me in

determining budget/budget for business production.”

Has the highest contribution. Based on the results of

descriptive statistics, the mean of the capital variable

is in the positive or good area with a value of 3.03.

4.6.5 The Sixth Factor, Labour Quality

Factor

As for the relationship with the quality of the

workforce in this study, namely the ability of the

workforce to produce products or complete a job with

a certain volume within a certain time limit under

standard conditions. Improve the way of working and

update the way of working to increase profit.

Based on the analysis of labour quality factor

analysis, it is included in the factor with the fifth

highest loading value. Based on the results of

grouping the fifth factor on the indicator after factor

rotation, there are 5 items including X2.4, X2.8, X3.7,

X3.8 and X4.2 with the statement "During the

pandemic, my workforce is able to encourage

business productivity." Has the highest contribution.

4.6.6 The Seventh Factor, Utilization Factor

The relationship with the utilization factor in this

study is that the advantage of using own capital is that

there are no costs such as interest or administrative

costs so that it does not become a business burden and

does not depend on other parties, meaning that it

obtains or is obtained from the deposit of the owner

of capital. While the disadvantage is that the number

is very limited and relatively difficult to obtain.

Use 15-poin Based on the analysis of utilization

factor research, it is included in the factor with the

sixth highest loading value. Based on the results of

grouping the fifth factor on the indicator after factor

rotation, there are 3 items including X1.3, X1.5, and

X1.5 with the statement "During the pandemic I get

additional capital for business production activities."

Has the highest contribution.

5 CONCLUSIONS

Based on the results of research and discussion

conducted, the conclusions obtained are as follows:

Analysis of the factors that affect the income of

MSMEs that market their products through Gojek

during the pandemic by showing that there are 6 new

factors formed from 32 variable indicators, namely:

1. The results of the first factor analysis of capital,

the indicator of its formation is the highest loading

value in the indicator grouping in factor 1 of

0.763.

2. The results of the analysis of the second factor of

wages or salaries, the indicator of its formation is

the highest loading value in the grouping of

indicators in factor 2 of 0.869.

3. The results of the analysis of the three resource

factors, the indicator of its formation is the highest

loading value in the grouping of indicators in

factor 3 of 0.723.

4. The results of the fourth factor analysis of raw

materials, the indicator of its formation is the

highest loading value in the indicator grouping at

factor 4 of 0.745.

5. The results of the analysis of the fifth factor of

labour quality, the indicator of its formation is the

highest loading value in the grouping of indicators

on factor 5 of 0.730.

6. The results of the analysis of the seventh factor of

utilization, the indicator of its formation is the

highest loading value in the grouping of indicators

on factor 6 of 0.755. We hope you find the

information in this template useful in the

preparation of your submission.

REFERENCES

Central Bureau of Statistics. (2020). Indonesia's Economic

Growth Quarter III-2020. Taken from

https://pedoman.co/news/bps-ekonomi-indonesia-

triwulan-iii-2020-tumbuh-505/

BatamEkbis.com (2020). Gojek helps marketing hundreds

of Batam SME products online. Taken from

Analysis of Factors Affecting the Income of MSMEs Marketing Products through Gojek during the Covid Pandemic

https://batamekbiz.com/gojek-bantu-pemasaran-

ratusan-produk-ukm-batam-secara-online/

Bisnis.com. (2020). Gojek claims to help MSMEs survive

during pandemics. Taken from

https://ekonomi.bisnis.com/read/20201223/98/133490

7/gojek-klaim-bantu-umkm-bertahan-saat-pandemi

Chuzairi, A., Sidik, M. A., Kamaruzaman, K., Rahman, A.,

& Susanti, R. (2021). Analysis of the Impact of the

Covid-19 Outbreak on the Economy of Souvenir

MSMEs in Sei Enam, Kijang-Bintan. JPPM Kepri:

Journal of Community Service and Empowerment of

Riau Islands, 1(1), 44-55.

Dangin, I g. a.b. t., & Marhaeni, A. a. i. n. (2019). Factors

of production that affect the income of artisans in the

leather craft industry in badung regency. E-journal of

Economics and Business Udayana University, 681-710.

Febriyantoro, M. T., & Arisandi, D. (2018). Utilization of

digital marketing for micro, small and medium

enterprises in the era of asean economic community.

Dewantara Management and Business Research

Journal (JMD), 1(2), 61-76.

Gojek (2020). Interesting facts harkulnas Gofood 2020.

Taken from

https://www.gojek.com/blog/gofood/harkulnas

Gojek. (2020). 5 mainstay gojek services of the community

during the covid 19 pandemic. Taken from

https://www.gojek.com/blog/gojek/new-normal-gojek/

Hamza, L.M., & Agustien, D. (2019). The Effect of Micro,

Small, and Medium Enterprises Development on

National Income in the MSME Sector in Indonesia.

Journal of Development Economics, 8(2), 127-135.

Halim, A. (2020). Pengaruh Pertumbuhan Usaha mikro,

Kecil dan Menengah Terhadap Pertumbuhan Ekonomi

Kabupatem Mamuju. Growth Jurnal Ilmah Ekonomi

Pembangunan Vol.1 No.2. E-ISSN 2716-2443.

Haqqi, H., & Murdani, a. d. (2021). The Role of Digital

Media in Improving the Global Competitiveness of

cocoa products. research fair unisri, 5(1), 56-63.

Helmalia, H., & Afrinawati, a. (2018). The influence of e-

commerce on the increase in the income of small and

medium-sized micro enterprises in padang cities. Jebi

(islamic economics and business journal), 3(2), 237-

246.

Beautiful, G., Yanti, P. S., & Hajratul, S. (2020). The

Impact of Independence and Ecommerce Business on

the Needs of E-commerce Audit Services. Journal of

Pundi, 4(1).

Katadata. (2020). Internet rescue of MSMEs from the

Covid 19 crisis. Taken from

https://katadata.co.id/ariayudhistira/infografik/5ef41f2

7a4d69/internet-penyelamat-umkm-dari-krisis-covid-

Ministry of Cooperatives and MSMEs. (2018). Business

Scale Profile in Indonesia. Taken from

https://industri.kontan.co.id/news/pelaku-umkm-

terdampak-covid-pertagas-terus-jaga-asa-kelompok-

tuli-sampai-petani

Komalasari, P., Enas, e., & Nursolih, e. (2020). Influence

of the Application of material requirement planning on

the control of raw material supplies (study on pt. albasi

priangan lestari). business management and

entrepreneurship journal, 2(3), 180-190.

Laili, Y. F., & Setiawan, A. H. (2020). Analysis of factors

that affect the income of batik center umkm in

pekalongan city. Diponegoro Journal of Economics,

9(4).

Laura Hardilawati, W. (2020). MSME Survival Strategy in

the Midst of the Covid-19 Pandemic. journals of

accounting and economics, 10(1), 89-98

.Lesmana, s. A. (2021). Analysis of factors that affect the

production of mskm for business success (case study:

umkm batik in sumenep regency). Student scientific

journal feb, 9(2).

Coverage 6. (2020). Gofood strengthens digital security

competencies for partners. Taken from

https://www.liputan6.com/tekno/read/4340989/gofood

-perkuat-kompetensi-keamanan-digital-untuk-para-

mitra

Mbae, I. (2018). Analysis of Soybean Raw Material

Inventory at The Coastal Poso Madani Tofu Plant With

Economical Order Quantity (EOQ) Method. Ecomen,

18(2), 9-19.

Mona, N. (2020). The concept of isolation in social

networks to minimize the contagious effect (cases of

coronavirus spread in Indonesia). Journal of Applied

Social Humanities, 2(2).

ODS Kepri & Data Minister Kab. & city. (2020). MSMEs

in Riau Islands Province. Taken from

https://hmstimes.com/2020/umkm-mati-duluan-baru-

bantuan-datang/

Government regulation of the Republic of Indonesia

number 7 of 2021 concerning micro, small, and

medium enterprises. Taken from

https://jdih.setkab.go.id/PUUdoc/176384/PP_Nomor_

7_Tahun_2021.pdf

Purwanti, E. (2013). Influence of entrepreneurial

characteristics, business capital, marketing strategies on

the development of MSMEs in Dayaan Village and

Kalilondo Salatiga. Among Makarti, 5(1).

Princess, A. L., Susyanti, J., & ABS, M. K. (2020).

Business Capital Factors, Psychological Capital,

Enterpreuner Characteristics, and Innovation To

Business Development in the Creative Economy of The

Fashion Sub-Sector in Malang Raya. Scientific Journal

of Management Research, 9(03).

Republik Indonesia, (2008). Undang-undang Republik

Indonesia Nomor 20 Tahun 2008 Tentang Usaha

Mikro, Kecil, dan Menengah. Jakarta. Kementrian

Koperasi dan Usaha Kecil dan Menengah

Rosmadi, M. L. N. (2021). Implementation of Business

Strategies During the Covid-19 Pandemic. ikra-ith

ekonomika, 4(1), 122-127.

Santoso, F. S. (2020). Family Environment as the

Beginning of The Development of Islamic

Entrepreneurship. Academic Nuances of Journal of

Community Development, 5(1), 13-22.

Siagian, A. O. (2021). The influence of factors on the

Income of Street Vendors in Grogol West Jakarta.

Journal Economy and Currency Study (JECS),3(1), 1-

10.

ICAESS 2021 - The International Conference on Applied Economics and Social Science

Silalahi, J. J. (2018). Analysis of Income and Development

of Agricultural Business in Simanindo District of

Samosir Regency Based on Water Availability.

Taken from

https://smartlegal.id/perizinan/2020/12/08/uu-cipta-

kerja-sah-5-kemudahan-yang-bakal-diperoleh-umkm/

Sudati, Hanung.,. Marlina (2019). UMKM Sebagai pilar

Membangun Ekonomi Bangsa. Jurnal REP (Riset

Ekonomi Pembangunan), Vol 4, No 2, Edisi Oktober.

E-ISSN : 2508-0205

Sudirman, A., Halim, F., & Pinem, R. J. (2020). Trust as a

Mediating of The Impact of Brand Image and Price on

Customer Satisfaction of Gojek. Journal of Competitive

Marketing, 3(3), 66-76.

Suryani, E. (2021) Anaisis Dampak Covid-19 terhadap

UMKM: Study Kasus Home Industri Klepon di Kota

Driyorejo. Jurnal Inovasi Penelitian (JIP) Volume 1

Nomer 8 Edisi Januari, 1591-1596, ISSN 2722-9467

Tahir, F. A., & Inuwa, F. U. (2019). Empirical investigation

of the factors affecting micro, small and medium scale

enterprises performance in Borno State, Nigeria.

International Business Research, 12(4), 30-39.

Tumuwe, R., Damis, M., & Mulianti, T. (2018). Online

motorcycle taxi users among students of Sam Ratulangi

Manado University. HOLISTIC, Journal of Social and

Culture.

Zafar, A., & Mustafa, S. (2018). SMEs and its role in

economic and socio-economic development of

Pakistan. International Journal of Academic Research

in Accounting, Finance and Management Sciences,

6(4).

Analysis of Factors Affecting the Income of MSMEs Marketing Products through Gojek during the Covid Pandemic