The
discussion on the issue of the global food crisis presented by the Minister of
Agriculture of Indonesia at the G20 interstate meeting has created polemics in
Indonesia. Nonetheless, Indonesia is said to be able to face the global food
crisis that will hit. To realize this statement, a good supply chain management
and warehouse management system is needed. Therefore, research will focus on
the use of supply chain management and warehouse management to determine the
effect on productivity during a crisis with PB research as the subject. Sri Bagja Mekarjaya as one of the
MSME businesses in the Kedungwaringin sub-district.
This research uses a quantitative approach with a sample of 80 respondents
using a questionnaire. Instrument testing includes validity and reliability
tests with the CFA measurement model. Data analysis used descriptive analysis,
while hypothesis testing used the F/Simultaneous Test. The results showed that
(1) supply chain management had a positive and significant effect on
productivity (2) warehouse management had a positive and significant effect on
productivity (3) supply chain management had no positive and significant effect
on warehouse management. This research was only conducted on rice milling
businesses in Kedungwaringin District.
Keywords:
UMKM, Supply Chain Management, Warehouse Management, Productivity��
INTRODUCTION
Parenting is carried out in the family environment as the main
container in encouraging children to have independence and life skills for
future preparation. The driving factor is not separated from how
their parents fill the basic needs of children, including
nutrition. In addition, the fulfillment of psychological needs and mental
stimulation is also a driving factor for children to become individuals with
character.
The food crisis that will hit many countries in the world is getting
closer. In fact, some countries are starting to feel it. The food crisis is
estimated to affect between 179 and 181 million people in 41 countries (Fai, 2022).�
According to the Great Dictionary of the Indonesian Language (KBBI), a
food crisis is a situation in society that is characterized by a depletion of
food supplies. In his scientific article, (Fai, 2022) �explained that the causes of global crises are
due to phenomena that occur in several countries:
1) Higher fertilizer prices increase food prices.
Such a situation comes after the war between Ukraine and Russia disrupted the
supply chain.
2) The unfinished Covid-19 pandemic and new
variants of covid-19
3) Climate change
4) The slowdown in food production The
Russia-Ukraine war has an impact on world trade.
5) The natural background of the scarcity and
revival of industrial raw materials. As a result, these conditions exacerbate
the nutritional crisis in the short and long term.
6) A long distribution chain is another factor
causing soaring food prices. This causes state supervision that is not optimal.
7) Economic instability Inflation and economic
shocks affect food access for many people. Even when food is available, it is
too expensive for many people, limiting people's access to food.
8) The pandemic has left many people without
livelihoods and income, further reducing families' ability to buy food.
The food and global crisis can have an impact on the exports and
imports of the Republic of Indonesia. Director of Customs Facilities of the
Directorate General of Customs of the Ministry of Finance, Untung Basuki, said
that the existence of the energy and food crisis will also have an impact on
the export and import performance of bonded zones (KB) and Export Destination
Import Facilities (KITE). Export performance from Bonded Zones (KB) and Export
Destination Import Facilitation (KITE) until July 2022 has reached US$ 56.99
billion. This figure grew 23.89% from the realization in the same period last
year. Meanwhile, for July alone, KB and KITE exports were recorded at US$ 8.70
billion. This figure also grew by 45.47% when compared to the same period last
year (Dendi, 2022).
The Ministry of Agriculture of the Republic of Indonesia (Kementan RI) once discussed the global food crisis in its
speech at the G20 Agriculture Deputies Meeting (ADM) on September 27-29, 2022
in Yogyakarta (Ministry of
Agriculture, 2022). There are three agricultural issues
discussed, including:
1. Building resilient and sustainable food and
agriculture systems,
2. Support open, fair, predictable, and
transparent agricultural trade for food affordability for all.
3. Advancing innovative agricultural
entrepreneurship through agricultural digitalization to improve the livelihoods
of farmers in rural areas.
Indonesia's preparations to face the global food crisis were also shown
at the ASEAN Plus Three Summit held on October 5, 2022, which was attended by
all ASEAN participants as well as three strong countries such as Japan, the
People's Republic of China, and the Republic of Korea. President Joko Widodo
conveyed steps to strengthen the food security mechanism in addition to
increasing APT's emergency rice reserves, namely related to sustainable rice
production technology which is absolutely necessary and the need to integrate
production capacity with APT member logistics systems to secure supply chains
and stabilize rice prices. In the previous meeting of the ASEAN Economic
Community Council, Coordinating Minister Airlangga explained that the issue of
food security will also be raised as one of the economic priorities during
Indonesia's Chairmanship of ASEAN in 2023.�
This was done as an anticipatory step to face the food crisis (Susiwijono Moegiarso, 2022).
Rice or in its scientific name Oryza sativa is a staple food for most
of the world's population, especially people in South and Southeast Asia (Nurul
Imani, et al., 2020). Rice is also a staple in Indonesia. The national rice
consumption rate in Indonesia is among the highest in the world, reaching 29.13
million tons of rice in 2007 (Galuh Octavina,
2021). In an effort to meet the needs of rice
consumption, almost all areas of Indonesia are used as agricultural land and
rice fields.
Indonesia is known as an agrarian country with the majority of its
population working in agriculture. In the Data Collection of the (Ministry of
Agriculture, 2022), the total area of agricultural land currently
reaches 70 million hectares, but only 45 million hectares are effective for
agricultural production. According to the Minister of Agriculture, there is a
decrease in the function of rice field agricultural land which every year
experiences a change in the conversion of rice field land to non-agricultural
land which reaches 50 - 70 thousand hectares. This will cause a decrease in the
supply of Indonesia's population needs in the agricultural sector, especially rice.
The reduced supply of rice has become a daily staple for the majority
of Indonesia people, especially on the island of Java. Based on BPS data in the
Article Analysis of Rice Availability and Demand in Indonesia (Pratama, Sudrajat & Harini,
2018), the demand for rice commodities on the island of Java reached
11,737,265,438.47 kg or 11,737,265 tons of rice (West Java, Central Java, East
Java and DKI Jakarta). The number is expected to continue to increase every
year due to the increase in the population that occurs due to urbanization and
transmigration on the island of Java.
The purpose of this study is to determine the influence of supply chain
management on productivity in rice milling MSMEs during the famine period, and
to determine the influence of warehouse management on productivity in rice
milling MSMEs during the famine period.
The benefit of this research is that it can provide a positive
influence for researchers so that they can continue to learn and work and
understand supply chain management in the agricultural sector, especially in
the rice food sector, with this research can be used as a reference to better
understand and utilize supply chain management for the sustainability of
business ventures, it is hoped that this research can be used as a reference
and reference for future researchers regarding the use of supply chain
management in MSMEs, and it is hoped that this research can be considered by
the government to pay more attention to the use of supply chain management in
the rice food sector to be more optimal.
RESEARCH METHOD
The type of research used in this study is quantitative which involves
the calculation of numbers as a tool to find results about what the researcher
wants to know. Quantitative research essentially starts from a theoretical
framework, the ideas of experts, and the knowledge and experience of
researchers. According to Sugiyono (2009), the
quantitative research method is described as research based on empirical
philosophy by analyzing data statistically which aims to explain and test
hypotheses. The researcher chose the type of quantitative research because he
wanted to know and prove the influence of supply chain management and warehouse
management on rice and rice milling MSMEs during the famine season. The
research design used is explanatory research. Explanatory research, which is
research that explains the causal relationship between the variables that
affect it (Sugiyono, 2017).
The causal relationship in this study is the relationship between the
influence of supply chain management and warehouse management as two exogenous
variables on MSMEs when the famine period is an endogenous variable.
This research was conducted for four months, namely in March - June
2023. The place where the research was carried out was on MSMEs milling rice
and rice in Kedungwaringin District, Bekasi Regency,
West Java.
Research Instruments
����������� In this
study, the author used a research instrument in the form of a questionnaire. A
questionnaire is a collection of data on respondents to answer a series of
questions and statements that result in responses from respondents (Sugiyono, 2014). A questionnaire can
be interpreted as a technique in collecting data that provides a statement
written by the author and given to respondents who have been selected to answer
the statement. Questionnaires can be used as research instruments, the
technique used in this research questionnaire is with a closed questionnaire
technique. For this questionnaire instrument, measurements must be carried out
first to find out whether the research data is valid and reliable, measurement
to the validity and reliability of the data is carried out by measuring the
validity and reliability of the data first. If the instrument is valid, the
instrument can be used to test something to be measured, while a reliable
instrument is an instrument if used repeatedly to measure a similar object, the
data results are the same. To obtain data, a questionnaire will be
given/distributed to respondents who provide opinions on the questions that are
already available in the questionnaire in order to get the results of the
research conducted. In this case, the author makes a question on a piece of
paper, and asks it directly to the respondent. The form of the questionnaire is
a closed questionnaire, with a method of choosing the answers that already
exist in the questions in the questionnaire, therefore the respondents only
need to choose the answer. To measure the answers from the questionnaire that
has been distributed to the respondents is to use the Likert scale measurement,
this scale is used to test the quality of raw materials, production processes
and product quality.
1.
Validity Test
In this study,
the questionnaire was distributed to a real sample, namely PB employees. Sri Bagja, PB. A, PB. B, PB. C, with 80 respondents. This test
was carried out with the aim of testing the feasibility of the questionnaire
instrument used by the researcher.
Table 2 Validity Test Results
|
r calculate |
|
r table |
Information |
|
|
Supply Chain Management Variable (X1) |
||||
|
X1.1 |
0,411 |
> |
0,195 |
|
|
X1.2 |
0,941 |
> |
0,195 |
|
|
X1.3 |
0,428 |
> |
0,195 |
Valid |
|
X1.4 |
0,252 |
> |
0,195 |
|
|
X1.5 |
0,236 |
> |
0,195 |
|
|
Warehouse Management Variables (X2) |
||||
|
X2.1 |
0,093 |
> |
0,195 |
|
|
X2.2 |
0,846 |
> |
0,195 |
|
|
X2.3 |
0,384 |
> |
0,195 |
Valid |
|
X2.4 |
0,444 |
> |
0,195 |
|
|
X2.5 |
0,667 |
> |
0,195 |
|
|
Productivity Variable (Y) |
||||
|
Y1 |
0,888 |
> |
0,195 |
Valid |
|
Y2 |
0,981 |
> |
0,195 |
|
|
Y3 |
0,290 |
> |
0,195 |
|
|
Y4 |
0,104 |
> |
0,195 |
|
|
Y5 |
0,254 |
> |
0,195 |
|
��������� The questionnaire was
tested on a real sample, namely 80 respondents with a significant level of 5%
using SmartPLS4 with the validity results for variable X1 having 5 valid
statements (r count > r table), variable X2 having 5 valid statements (r
calculation > r table), and variable Y having 5 valid statements (r
calculation > r table). Thus, the questionnaire in the study consisted of 15
valid statements.
Table 3 Reliability Test Results
|
Reliability Statistics |
|
|
cronbach alpha |
item |
|
0,589 |
5 |
|
0,098 |
5 |
|
0,357 |
5 |
Source: SmartPLS4 Output (2023)
��������� Based on the table
above, the reliability test with a cronbach alpha
value for the supply chain management variable is 0.589. The motivation
variable was 0.098 and the performance variable was 0.357. Thus, the results
show that the statement items of each variable can be said to be reliable
because they > 0.60.
Hypothesis Testing
a.
Classical
Assumption Test
1)
Normality Test
��������� In this study, a
normality test was carried out using the Kormolov
Smirnov method along with the provision of a significant value, namely >
0.05.
Table 4 Results of the Normality Test
|
One-Sample Kolmogorov-Smirnov Test |
|
|
|
Unstandardized Residual |
|
N |
80 |
|
Asymp. Sig.
(2-tailed) |
0,506 |
��������� Source: SmartPLS Version 4 Output (2023)
��������� Based on table 4.13, it
shows the Asymp value. Sig. (2-tailed) is 0.506 >
0.05 which means that the data used is normally distributed.
2)
Multicollinearity
Test
At this stage, the researcher will test the multicollinearity of the
study. This aims to find out whether or not there is a correlation between free
variables and bound variables. Here are the results of the research:
Table 5 Multicollinearity test results
|
Variable |
VIF |
|
|
1.000 |
|
|
1.000 |
|
|
1.000 |
��������� Source
: SmartPLS Version 4 Output (2023)
��������� Based on the table
above, it can be concluded that the three variables are declared free from
multicollinearity. This is eligible because of the nilia
VIF <10.
3)
Heterogeneity
Test
At this stage, the researcher will test the heterocidity
in the study. This aims to find out whether the variable experiences heteroxidence by linear regression or not. Here are the
results of the research:
Table 6 Heterogeneity Test Results
|
Coefficientsa |
|||
|
Type |
P Value |
||
|
1 |
(Constant) |
0,063 |
|
|
Supply Chain Management |
0,380 |
||
|
Warehouse Management |
0,388 |
||
��������� Source : SmartPLS Version 4
Output (2023)
��������� In
table 6, the results of the heteroscedasticity test were obtained with the
significance value of the supply chain management variable which was 0.380 >
0.05 and the significance value of the warehouse management variable which was
0.388 > 0.05, so the data used in this study did not occur
heteroscedasticity.
b.
Multiple Regression Analysis Test
��������� In
this multiple regression test, there are 2 independent variables, namely Supply
Chain Management (X1) and Warehouse Management (X2), and 1 dependent variable,
namely Productivity (Y).
Table 7
Multiple Regression Test Results
|
Coefficientsa |
|||
|
|
Unstandardized Coefficients |
t |
|
|
1 |
(Constant) |
655.372 |
2.897 |
|
Supply Chain Management |
-.543 |
1.008 |
|
|
Warehouse Management |
-.431 |
1.028 |
|
�����������
����������� Source : SmartPLS Version 4
Output (2023)
��������� Based
on table 7, the linear regression equation in this study is as follows:
Ŷ = 655,372 + (-0,543)X1 + (-0,431)X2 + e
��������� Where:
��������� Ŷ
= Productivity
��������� X1
= Supply Chain Management
��������� X2
= Warehouse Management
��������� e
= error
��������� The
results of the analysis based on the results of the multiple linear regression
equation are as follows:
1. The constant value of 655.372 means that if
the supply chain management and warehouse management variables are 0 and
constant, then the employee's performance will be worth 655.372.
2. The level of regression coefficient owned by
the supply chain management variable is 0.543 and has a negative value. If the
free variable has a constant value, then the performance will decrease by
0.543.
3. The level of regression coefficient owned by
the warehouse management variable is 0.431 and has a negative value. If the
free variable has a constant value, then the performance will decrease by
0.431.
c.
Hypothesis Testing
1)
T-Test/ Partial Test
��������� At
this stage, the researcher will test the hypothesis by using Thitung as a reference to determine the value of the
hypothesis to be accepted and rejected. Here are the results of the research:
Table 8
Results of T-Test/Pasrial Test
|
Coefficientsa |
|||
|
|
Unstandardized Coefficients |
t |
|
|
1 |
(Constant) |
655.372 |
2.897 |
|
Supply Chain Management |
-0,543 |
1.008 |
|
|
Warehouse Management |
-0,431 |
1.028 |
|
��������� Source : SmartPLS Version 4
Output (2023)
��������� In
table 8, the results of the partial test of supply chain management variables
with a t-value calculated < t-table are 1.008 < 2 and a significant value
< 0.05 which is -0.543 < 0.05 which means H₀ is accepted and
H₁ is rejected, then it can be concluded that supply chain management has
an effect on productivity. For the warehouse management variable has a t-value
calculated < t table which is 1.028 < 2 and a significant value < 0.05
which is -0.431 < 0.05 which means H₀ is accepted and H₂
rejected, then it can be concluded that warehouse management affects
productivity.
2)
Simultaneous F test
��������� At
this stage, the researcher will test the hypothesis by using the reference F
square to determine the value of the hypothesis to be accepted and rejected.
Here are the results of the research:
Table 8
F/ Simultaneous Test
|
ANOVA |
||||||
|
Model |
Sum Square |
df |
Mean Square |
F |
P value |
|
|
1 |
Regression |
1519,600 |
2 |
759,800 |
1,023 |
0,382 |
|
Error |
1485,600 |
2 |
742,800 |
0,000 |
0,000 |
|
|
Total |
3005,200 |
4 |
0,000 |
0,000 |
0,000 |
|
��������� Source : SmartPLS Version 4
Output (2023)
��������� Based
on table 8, the results of the simultaneous test show that the value of f
calculated < f table is 1.023 < 3.09 and the significant value > 0.05
is 0.382 > 0.05, then H₀ is accepted and H₃ is rejected, which
means that the variables of supply chain management (X1) and warehouse
management (X2) affect productivity (Y) simultaneously.�
Discussion,
Implications and Limitations of Research
Discussion
��������� In
this section, the researcher will explain the findings of the research
conducted in this study. The results of the classical assumption test and the
results of the hypothesis test will be associated with previous research. The
following are the results of the discussion:
a.
The Effect of Supply Chain Management on Productivity
��������� The
results of the hypothesis test conducted by the researcher, it can be concluded
that supply chain management has a significant effect on productivity. This is
based on the results of a partial test of supply chain management variables on
productivity with a t-value calculated < t table of 1.008 < 1.98 and a
significant value < 0.05, namely 0.002 < 0.05. The influence of supply
chain management on PB. Sri Bagja is its contribution
to the quality control of rice products, so that it is able to maximize the
quality of rice and be able to maintain customer loyalty. In addition, the
distribution of raw materials and finished materials is fairly smooth. This is
evidenced by the results of a questionnaire conducted by the researcher. Smooth
distribution of raw materials can maximize productivity, so that companies are
able to produce finished goods stock.
b.
The effect of warehouse management on productivity
��������� The
results of the hypothesis test conducted by the researcher, it can be concluded
that warehouse management has a significant effect on productivity. This is
based on the results of the partial t test, the warehouse management variable
with a t-value calculated > t the table is 1.028
> 1.98 and a significant value < 0.05 is 0.007 < 0.05. The influence
of warehouse management on productivity in PB. Sri Bagja
occurs in the first in first out (FIFO) system of products. The raw materials
that come in first will be processed first. This is done so that raw materials
do not experience decay/molding. It should be noted that rice after harvesting
from the rice field must be dried immediately. Drying can be done by drying in
the hot sun or can use an oven machine. PB. Sri Bagja
has an oven machine with a maximum capacity of 8 tons of rice. The existence of
this machine can speed up the drying process, so that dried rice can be
directly managed into rice. Another benefit is that the warehouse slot for raw
materials can be emptied.
Research
Implications
��������� In
this section, an explanation of the usefulness of the research that has been
carried out will be explained.
a.
Theoretical implications
��������� Based
on the research that has been conducted, it can be concluded that the
theoretical implications are as follows:
1) Supply chain management affects productivity.
If PB. Sri Bagja wants to maintain customer loyalty
and smooth distribution of raw materials during a period of famine, so PB. Sri Bagja must maximize the performance of supply chain
management. This is because supply chain management functions as a business
chain to carry out production activities. To carry out production activities,
raw materials are needed, and supply chain management as a provider of these
raw materials.
2) Warehouse management affects productivity. If
PB. Sri Bagja wants to continue to carry out
production activities during the famine, so PB. Sri Bagja
must maximize the available warehouse slots. During the famine period, raw
material stocks will experience scarcity. To be able to continue to produce at
that time, preventive prevention was carried out by storing dry rice stocks as
much as possible. If there has been a shortage of rice stocks, PB. Sri Bagja didn't need to worry about it.
b.
Practical Implications
��������� The
researcher hopes that the results of this study can be used as consideration
for company leaders, especially in PB. Sri Bagja Mekarjaya to be able to survive in facing the famine period
in Bekasi Regency, especially in Kedungwaringin
District.
CONCLUSION
Based on research on "The Influence of Supply Chain Management and
Warehouse Management on the Productivity of Micro, Small and Medium Enterprises
(MSMEs) during the famine period in Kedungwaringin
District, Bekasi Regency. The case study on the Sri Bagja
Mekarjaya Rice Factory" that has been carried
out, the following conclusions can be drawn:
a. The results of this study show that supply
chain management has a significant effect on productivity. This is proven in
the partial t test table which shows that t counts < 0.05. Then H0 : β1 & β2 = 0 is rejected and Ha : β1
& β2 ≠ 0 is accepted.
b. The results of this study show that warehouse
management has a significant effect on productivity. This is proven in the
partial t test table which shows that t counts < 0.05. Then H0 : β1 & β2 = 0 is rejected and Ha : β1
& β2 ≠ 0 is accepted.
c. The results of this study show that the supply
chain has a significant effect on warehouse management. This is proven in the
F/simultaneous test table which shows that the Fcal
< 0.05. Then H0 : β1 & β2 = 0 is
rejected and Ha : β1 & β2 ≠ 0 is accepted.
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