Influence of Work Motivation and Use of Information Technology on

Sleman Yogyakarta Farmers Performance

Arief Subyantoro

, Rifqi Syarif Nasrulloh

and A. Ayiek Sih Sayekti

Universitas Pembangunan Nasional Veteran Yogyakarta

INSTIPER, Yogyakarta

Keyword: Work Motivation, Information Technology Utilization, Farmers' Performance

Abstract: Food security programs based on food independence and sovereignty supported by integrated food

availability, distribution, and consumption subsystems are one of the government's efforts to strengthen

national food security. Farmers, as the main actors in supplying food supplies, are interesting subjects to study.

This study aims to reconfirm the influence between work motivation and the use of information technology

on individual performance based on previous research with different research objects. The population in this

study were all farmers registered as members of farmer groups in each region. The sampling technique is the

accidental sampling method and obtained 102 farmer respondents who filled out the questionnaire. The results

state that this study supports previous findings, which state that 1) work motivation has a positive influence

on farmers 'performance, 2) the use of information technology has a positive effect on farmers' performance.

By building self-motivation through rewards that are expected to be adjusted to personal goals so that the

performance of individuals will increase due to the motivation for personal goals that they want to obtain.

While the use of technology increases individual performance by looking at the more dominant frequency of

using information technology compared to other technology utilization indicators.

INTRODUCTION

In efforts to strengthen food security, the Ministry of

Agriculture will focus on increasing the production of

strategic staple foods for rice, corn, soybeans, sugar

(sugar cane) and beef buffalo, and other agricultural

commodities, on meeting domestic food needs. The

stabilization of food security must be based on food

independence and sovereignty supported by

integrated food availability, distribution, and

consumption subsystems (Renstra BKP, 2019). The

agricultural sector is the main sector in meeting

human needs, both domestically and abroad. In

Indonesia, the role of agriculture is not only a

fulfillment of consumer needs but also as a

contributor to the country's economic income because

Indonesia is an agricultural country whose main

economic factor in agriculture. Based on data from

the Ministry of Agriculture (Ministry of Agriculture),

in the past three years, rice production has continued

to increase, but in terms of productivity, it has

declined. While corn production rose due to increased

harvested area, while the level of productivity fell.

The decline in rice productivity in the last three years

can be seen in table 1:

Table 1. Decreased rice productivity

The food security program is directed at the

independence of the community/farmers based on

local resources so that they are very concerned about

the level of welfare of farmers (Darwanto, 2005). The

griculture sector is still the mainstay in Sleman

Regency; it can be seen from the high.

The number of people in this region who are still

dependent on agriculture for their livelihoods, besides

the agricultural sector, is also the biggest contributor

to the Gross Regional Domestic Product (PDRB) in

Sleman. However, in its implementation, several

problems exist so that the food security program does

not run optimally. The problem was stated in the BKP

Restra (2019) on the fourth point. Namely, food

Year of Productivity Decrease in

2015 5.34 tons per hectare

2016 5.24 tons per hectare 10 tons per hectare

2018 5.16 tons per hectare 8 tons per hectare

Subyantoro, A., Nasrulloh, R. and Sayekti, A.

Inﬂuence of Work Motivation and Use of Information Technology on Sleman Yogyakarta Farmers Performance.

DOI: 10.5220/0009966103470352

In Proceedings of the International Conference of Business, Economy, Entrepreneurship and Management (ICBEEM 2019), pages 347-352

ISBN: 978-989-758-471-8

347

agribusiness that has not been optimal has greatly

affected the level of welfare of farmers. These

problems are closely related to the quality and

quantity of farmers' yields. Product quality and

quantity is an indicator of individual performance

measurement (Moeheriono, 2009)

Individual performance of certain behaviors is

mainly determined by the intention of someone who

has a certain motivation to perform the behavior,

individual attitudes and the influence of the social

environment on the desired behavior must be positive

in order for changes to occur expected, this is

supported by the theory of hope put forward by Victor

Vroom (Robbins & Judge, 2008). Behavior change is

very influential on the extent of individual

performance so that each individual is required to be

able to implement a culture of high- performance

behavior (Armstrong, 2006). Changes in behavior

because technology has resulted in higher quality

individual performance in an organization. These

findings have been highlighted by (Abusharbeh &

Nazzal, 2018; Bao & Nizam, 2015; Andriana, 2015;

Wahyudi et al., 2018) which states that work

motivation has an influence on individual

performance, other findings put forward by (Igbaria

& Tan, 1997; Hasiholan, 2005, Lindawati & Salamah,

2012) also stated that the use of information

technology has a positive influence on individual

performance.

Therefore, this study aims to reconfirm the

influence between work motivation and the use of

information technology on individual performance

based on previous research with different research

objects, namely farmers in Sleman, Yogyakarta. This

is because changes in farmer's behavior are one of the

factors that cause problems that hamper the pace of

food security programs.

LITERATURE REVIEW

2.1 Individual Performance

According to Miner (1990), performance is how a

person is expected to function and behave in

accordance with the tasks assigned to him. Every

expectation of how one must behave in carrying out

the task means showing a role in the organization. An

organization, both government and private

organizations in achieving the goals set, must be

through means in the form of an organization that is

driven by a group of people who play an active role

(actors) to achieve the goals of the institution or

organization concerned (Prawirosentono, 1999).

Performance (performance) is an achievement of

certain job requirements that ultimately can be

reflected in the output produced. Performance is one

of the measurement tools for achieving organizational

goals. Performance can be seen as 'thing is done.'

Hasibuan (2002) also defines performance (work

performance) as a result of work in quality and

quantity achieved by an employee in carrying out

their duties in accordance with the responsibilities

given to him (Moeheriono, 2009).

2.2 Work

Motivation, according to Robbins & Judge (2008), is

a process that explains the intensity, direction, and

perseverance of an individual to achieve his goals.

Motivation, according to Hasibuan (2009), is the

provision of driving data that creates the excitement

of one's work, so that they want to cooperate, work

effectively and be integrated with all their efforts to

achieve satisfaction. Meanwhile, according to Mathis

& Jackson (2002) revealed that motivation is a desire

in someone who causes the person to act. Robbins &

Judge (2008) said that the theory of the process of

motivation tries to answer how to strengthen, direct,

maintain, and stop individual behavior. One theory of

the process is the theory of hope. The theory of hope

was put forward by Victor Vroom, who bases his

theory on three important concepts, namely: 1) Hope

(expectancy) is an opportunity given to occur due to

behavior. 2) Value (valence) is the result of certain

behaviors that have a certain value or dignity (power

or value motivating) for each particular individual. 3)

Linkage (instrumentality) is the perception of the

individual that the results of the first level will be

related to the results of the second level.

H1: Work motivation has a positive influence on the

performance of farmers.

2.3 Utilization of Information

Technology

The rapid development of information systems and

information technology makes it a competitive

weapon that must be owned by companies in Winning

the competition. The application of information

systems and information technology can be said to be

successful if it can improve employee performance,

which in turn can improve company performance.

With the implementation of information systems and

information technology, companies need to prepare

human resources (HR) (Lindawati & Salamah, 2012).

Thompson et al. (1991) define the use of technology

as the benefits expected by users of information

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systems in carrying out their duties where the

measurement is based on the intensity of utilization,

frequency of utilization, and the number of

applications or software used. Technology is seen as

a tool used by individuals in carrying out their duties.

Technology is a tool, technique, or way that can help

humans in doing work so that work becomes lighter,

faster, better, or more results (Haryani, 2001). In

relation to the utilization of information technology,

there are two basic theories, namely Theory of

Reasoned Action (TRA) developed by Fishbein &

Ajzen (1975) and Theory of Attitudes and Behavior

developed by Triandis (1971). Theory of attitudes and

behavior developed by Triandis (1971) states that

behavior is determined by what people want to do

(attitude), what they think they will do (social rules),

what they are used to do (habits) and with the

consequences of the behavior they expect. According

to Lucas & Spitler in Jin (2003), information systems

and information technology can be used effectively

one of them by contributing to performance.

H2: The use of information technology has a positive

influence on the performance of farmers

RESEARCH METHODS

The object in this study is farmers in Sleman,

Yogyakarta. The population of this research is all

farmers who are members of farmer groups in each

region in one Sleman district. The sampling technique

is the accidental sampling method; this technique is

implemented by inviting farmers from several groups

in Sleman at a Forum Group Discussion, farmers who

come to the event will be used as research samples.

This technique is carried out to facilitate research

activities because this research is still under

development. The total number of farmers who

attended the event was 106 farmers, so the sample in

this study was 102, so that the number met the criteria

for the sample in the SEM study of at least 100 people

(Ghozali, 2006). Data collection techniques using a

Likert scale questionnaire with intervals 1-4, 1,

namely strongly disagree, 2 disagree, 3 agree, and 4

strongly agree (Widiyoko, 2016). The statistical

technique used is Partial Least Squares to show the

results of the validity and reliability test and

hypothesis testing. The questionnaire was sourced

from each variable as follows:

Work motivation, there are 3 indicators of work

motivation measurement, namely the business

relationship with performance, business

relationship with rewards, and relationship of

rewards with personal goals (Lamborn, 1991;

Robbins & Judge, 2008).

Utilization of Technology, there are 3

indicators that have been adopted by

Thompson et al. (1991; 1994), namely

intensity, frequency, and diversity.

Individual performance, there are 2 indicators

of individual measurement, namely the

quantity and quality of products (Moeheriono,

2009).

RESULTS

4.1 Characteristics of Respondents

The following characteristics of respondents by age,

sex, marital status, some dependents, length of time

as farmers and education can be seen in table 2:

Table 2. Respondent

Characteristics Respondents Frequency Percentage

Age

15-30 6 6.12

30-40 24 24.48

> 40 72 73.44

Gender

Men 81 82.62

Women 21 21.42

Marital Status

Married 94 95.88

Not Married 5 5.1

Not Married 3 3.06

Number of

Dependents

0 10 10.2

1 11 11.22

2 20 20.4

> 3 61 62.22

Farming Time

> 10 25 25.5

10 - 20 38 38.76

20-30 19 19.38

> 30 20 20.4

Education

SD 26 26.52

SLTP 21 21.42

SLTA 52 53.04

Others 3 3.06

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From the table above, it can be seen that the

majority of respondents have an age of over 40 years

of 73.44% of the total study respondents. This shows

that the existing farmers are classified as old. In terms

of gender, male respondents dominate 82.62% of the

total respondents; this is natural and has become

common because farming is a profession dominated

by men. Many respondents also already have

families, in the amount of 95.88% of the total

respondents, and the majority have more than 3

children in the amount of 62.22. Experience in

farming can be seen from the length of time he

worked as a farmer, seen from table 4.1. The majority

of respondents became farmers around 10- 20 years

which amounted to 38.76% and the second position

was occupied by respondents with long ten years of

farming <10 years which amounted to 25.5% so that

from this data it can be seen that the respondents were

relatively short-lived as farmers. The level of

education of farmers is dominated by upper

secondary level schools, and its equivalent is 53.04%.

This shows the level of farmers' education is quite

good.

4.2 Test Instrument Research

4.2.1 Validity Test

To conduct the validity test in this study used 2

measurements, namely the Convergent Validity and

Discriminant Validity tests. Based on the instrument

testing that has been done, the convergent validity test

results of each variable can be seen in Table 3, as

follows:

Table 3. Convergent Validity Test Table

Convergent Validity

X11 <- Motivation 0.816

X12 <- Motivation 0.835

X13 <- Motivation 0.768

X21 <- Use of IT 0.933

X22 <- Utilization of IT 0.916

X23 <- Utilization of IT 0.876

Y11 <- performance of Farmers 0.640

Y110 <- performance of Farmers 0.695

Y12 <- performance of Farmers 0.713

Y15 <- performance of Farmers 0.808

Y17 <- performance of Farmers 0.771

Y18 <- Farmer Performance 0.736

Y19 <- Farmer Performance 0.691

Based on table 3, the convergent validity value of

each indicator has fulfilled the requirements that are

above 0.7, 2 items in the farmer performance variable

have values between 5-7 but are still maintained

because they have a value of 0.5- 0.6, this is still

accepted in research that is still under development

(Chin, 1998). The following test results discriminant

validity can be seen in Table 4:

Table 4. Cross Loading

Work

Motivation

Information

Technology

Utilization

Performance

Farmers

X11 0.816 0.109 0.342

X12 0.835 0.245 0.364

X13 0.768 0.376 0.37

X21 0.3 0.933 0.34

X22 0.256 0.916 0.257

X23 0.273 0.876 0.274

Y11 0.219 0.016 0.64

Y11

0.221 0.396 0.695

Y12 0.182 0.173 0.713

Y15 0.492 0.303 0.808

Y17 0.37 0.045 0.771

Y18 0.269 0.173 0.736

Y19 0,339 0.342 0.691

Based on the cross-loading in Table 3.5 shows

that each indicator is higher correlated with each

construct is compared with other constructs, so it is

said to have good discriminant validity.

4.2.2 Reliability Test

The test uses composite reliability values. The Rule

of Tumb that is usually used to assess construct

reliability is that the Composite Reliability value must

be greater than 0.7 (Ghozali & Latan, 2013). The

following results of the reliability testing in table 5:

Table 5. Reliability Test

Cronbach' s Alpha Description

Farmer

Performance

0.853

Reliable /

Reliable

Work Motivation 0.731 Reliable / Reliable

Utilization of

Information

Technology

0.895 Reliable / Reliable

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4.2.3 Variables Research Hypothesis Test

Hypothesis

Testing in this study uses the Partial Least Square

(PLS) statistical test with SMART PLS 3.0 software

to analyze the relationship between the data needed

and the relationship between exogenous variables and

endogenous variables. The following hypotheses test

results can be seen in table 6:

Table 6. Hypothesis Test Results

Original Sample

(O)

T Statistics

( O / STDEV)

P values Information

Work motivation -> Farmer

Performance

0.382 3,894 0,0000 Significant

Use of information Technology

-> Performance Farmers

0.207 2.225 0.027 Significant

From table 6, it can be seen that the relationship

between work motivation and individual performance

shows an estimated coefficient of 0.382, a calculated

t value of 3,894, and a probability value of 0,000.

Probability value indicates less than 0.05, so it can be

concluded that

there is a significant effect between work

motivation (X1) and Individual Performance (Y).

Judging from the estimated coefficient values

indicate that the direction of the relationship between

work motivation and individual performance is

positive; therefore, it can be concluded that

hypothesis 1 that states the work motivation of

farmers has a positive influence on farmer

performance is proven. The relationship between the

use of information technology on individual

performance shows an estimated coefficient value of

0.207, a calculated value of t.225, and a probability

value of 0.027. Probability value indicates less than

0.05, so it can be concluded that there is a significant

influence between the use of information technology

(X2) with Individual Performance (Y). Judging from

the estimated coefficient values indicates that the

direction of the relationship between the use of

information technology with individual performance

is positive; therefore, it can be concluded that

hypothesis 2, which states the use of information

technology, has a positive influence on the

performance of farmers is proven.

DISCUSSION

From the results of hypothesis testing that has been

done shows that the work motivation of farmers has a

positive influence on the performance of farmers so

that hypothesis 1 is accepted. These findings support

the research conducted by (Abusharbeh & Nazzal,

2018; Bao & Nizam, 2015; Andriana, 2015; Wahyudi

et al., 2018). By referring to the theory of hope which

assumes that humans will take action to achieve the

goals they deem valuable and they see that what they

do will help them achieve these goals, therefore with

the expectations held by individuals, each individual

strives to achieve or fulfill These expectations will

later aim to improve individual performance (Suripto,

2015). The results also showed that farmers showed

the highest motivation indicator is by building self-

motivation through rewards that are expected and in

accordance with personal goals so that the

performance of individuals will increase due to the

motivation for personal goals that have been wanted.

From the results of hypothesis testing that has

been done shows that the use of information

technology has a positive influence on the

performance of farmers so that hypothesis 2 is

accepted. These findings support the research

conducted by (Igbaria & Tan, 1997; Hasiholan, 2005;

Lindawati & Salamah, 2012). Basically, utilizing

information technology can increase the speed,

accuracy, and efficiency of exchanging large amounts

of information so that the role of utilizing information

technology is very important for improving

individual performance (Igbaria & Tan, 1997). The

results of this study also indicate that the use of

technology increases individual performance by

looking at the more dominant frequency of using

information technology compared to other

technology utilization indicators. This shows that the

use of information technology means that farmers

already have experiences that have a good impact on

their performance so that farmers will continue to use

information technology repeatedly.

Inﬂuence of Work Motivation and Use of Information Technology on Sleman Yogyakarta Farmers Performance

351

CONCLUSION

Based on the results of the study as described in the

previous chapter, two conclusions can be drawn;

namely, first, work motivation has a positive

influence on farmers' performance. It means that if the

work motivation is high, the farmer's performance

will also increase; on the contrary, if the work

motivation is low, the farmer's performance will also

decrease. The highest motivation indicator is to build

self-motivation through the expected appreciation

and in accordance with personal goals so that the

individual's performance will increase due to the

motivation of personal goals that you want to obtain.

Second, the use of information technology has a

positive influence on the performance of farmers.

This means that if the use of information technology

is high, then the performance of farmers will also

increase; on the contrary, if the information

technology is low, then the performance of farmers

will also decrease. Utilization of technology increases

individual performance by looking at the more

dominant frequency of using information technology

compared to other technology utilization indicators.

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