INTRODUCTION
The production quality planning process is a real action
and can be seen, and if the production planning is carried out properly it will
have an impact on efficient implementation by the company. Thus, a production
plan is needed in a company, this planning is carried out as a first step in
determining production activities (Nkadimeng et al., 2018). In addition, there is also a need for
quality control measures, with the aim of increasing effectiveness to prevent
product defects. The lack of product defects in production will have an impact
on production productivity, because it can minimize the use of unnecessary materials
or the workforce itself (Julaeha et al., 2020). However, even
though the company has planned a good production process, the reality on the ground
may be different. Product defects can increase the risk of failure and reduce
product quality, quality control has been proven to be an effective way to
prevent product damage (Khatab et al., 2019).
One example of the case is what happened to PT Hema
Medhajaya, a furniture manufacturing company, in which products are often
produced that are not of the company's quality standards. So that product
quality control with layered checks is needed by the company in order to
increase its efficiency, and can be used as a tool to prevent damage which is
done by rejecting and accepting all products from suppliers and the production
process, using this method. Then it can also be used as a monitoring tool in
the production process (Darsono, 2013). As a basis for
making decisions regarding product acceptance, measurement of the level of
product damage is carried out through determining the tolerance for product
defects produced, so the company uses the Quality Control Circle quality
control method.
Fadilla & Adji (2020) has conducted research that quality control is to
maintain and direct product quality. The application of quality control using
the SQC method is useful in an effort to minimize product failure rates. The
results of this research analysis indicate that there is a positive change in
the production process, which is proven to have decreased by 3.5% from 7.4% to
3.9%.
Likewise with research by Satyawisudarini et al (2017) has conducted research on how much influence the
production process and quality control have on the quality of the products
produced either partially or simultaneously. The conclusion of the production
process and quality control jointly affect the quality of the resulting product
with a coefficient of determination value of 82.8%.
Previous research concerning
the production process, raw material quality, product quality control, has been
widely carried out, but it is different from this research because the research
was carried out directly, namely a case study of a furniture manufacturing
company at PT Hema Medhajaya the use of which will be associated with quality
planning variables, and previous studies used Statistical Quality Control and
Statistical Process Control methods, these two methods are statistical
techniques in monitoring and improving process performance to produce quality
products. In this study using product quality control with the Quality Control Circle
method can analyze the problem, identify the cause, generate alternative
solutions, and finally apply the most adequate solution.
Based on the explanation of
these problems, this research aims to provide evidence that production quality
planning and quality control with the Quality Control Circle method can affect
the final product quality, good production planning in the Furniture company.
According to Ahyari (2005) which provides an explanation, production planning
is a plan for what and how many products to be produced, which must be decided
appropriately and executed according to the plan. This is also related to the
production process of raw materials so that the final product is of high
quality, besides that it is also necessary for the company to get better
production results at reasonable prices, as well as in a systematic way on research. Wei et al (2018)
shows that quality planning can be minimized using PDCA and the Seven Tool. The
total loss from defects decreased, therefore production planning had a positive
effect on the final product. Further supported by Herawati & Mulyani (2016) states that the production process has a significant
effect on the quality of the product or the final product.
H1: Production quality planning
has a positive and significant effect on the final product
The
quality control carried out by the company has quite an impact on efforts to
reduce product failure rates, so that the company produces quality final
products. If the company has good control then the risk of high costs will be
low. Meanwhile, according to Al Choir (2018) Control is an act of monitoring and ensuring that
performance in the field is in accordance with the plan. On research by Magar & Shinde (2014) that implements 7 Quality control Tools these tools
make quality improvements easier to see, implement, and track. Further
supported by research by
Fadilla & Adji (2020) this study uses the Statistical Quality Control (SQC)
method for quality control, and this shows that there is a positive change in
the production process, therefore quality control has a positive effect on the
final product.
H2: Quality Control has a positive and significant
effect on the final product
Production planning has been well planned but in
reality the field is often not appropriate, so quality control must be carried
out in order to get a quality final product. With good production planning and
quality control inspection costs can be minimized as small as possible, due to
minimal damage because it can be detected early. This will reduce overall
production costs. Moreover, Satyawisudarini et al (2017) in his research concluded that the production
process and quality control together affect the quality of the resulting product
with a coefficient of determination of 82.9%.
H3 : Production quality planning and quality control
simultaneously have a positive effect on the final product
METHOD
The research was carried out at PT Hema Medhajaya,
which is located in Sukapeace Village, RT.02 RW.03, Cikupa District, Tangerang
Regency, Banten 15710, which is a company engaged in the furniture sector. This
research was conducted in November-December 2020. The population of this
research is the defects and product quality of PT Hema Medhajaya. While the
sample used is the production report in 2017 - 2019.
Data
were collected by purposive sampling technique (purposed sample), because
previously certain characteristics such as disability and quality were
determined according to the researcher's objectives (Sugiyono, 2017). With this, it is
hoped that it can provide answers to problems, by taking the subject of the
type and quality of PT Hema Medhajaya's products. While the method used to
collect data is observation, observing directly at PT Hema Medhajaya as an
object in obtaining primary data.
There are several ways that are done in data
collection, namely: Observation whose data is obtained by visiting the location
to observe directly, this method was chosen because researchers can see
directly the condition of the object of research. Documentation is observing
and recording some data on the management department, for example, data and
types of quality control implementation in 2017-2019. Literature Research
(Library Research) is a technique for collecting data with a literature review
in order to make a comparison between theory and real conditions in the field (Creswell, 2017).
Based on
the type of research using descriptive quantitative methods in which the type
of data can be measured, calculated, and can be described using the data. Classical
Assumption Test was conducted to obtain valid results. Multicollinearity test
can be detected by showing a tolerance value > 0.01 or equal to the VIF
value <10. Autocorrelation test is the relationship between data at a time
with data at a previous time. Heteroscedasticity test, a good model is the
absence of heteroscedasticity, in this test it can be said that a regression is
free from heteroscedasticity symptoms if all the independent variables are not
significant to the absolute value of the residual from the regression results
(Whydiantoro, 2016).
Sugiyono (2012)
states multiple Linear Regression
is used by researchers, if it has the intention of predicting how the condition
(up and down) of the dependent variable (criteria), if two or more independent
variables as predictor factors are manipulated (increase in value). So multiple
regression analysis will be carried out if the number of independent variables
is at least two. Hypothesis testing basically shows whether all the independent
variables included in the model have a joint effect on the dependent variable.
So this test consists of Simultaneous Test (F test) is used to test the
feasibility of the resulting model using the model feasibility test at the
level of 5%. Testing T Test (Partial) the level of confidence used is 95% or a
significant level of 5%.
Figure 1. Research Model
RESULTS AND DISCUSSION
A.
Results
Descriptive statistical tests are carried out with
the aim of being able to provide a description or descriptive of a data seen
from the lowest, highest, mean and standard deviation values. In this study,
the total sample used was 36 samples. According to the results of descriptive
statistical tests, it can be concluded that the production quality planning
variable has a minimum value of 18.88 and a maximum value of 53.20 with an
average value of 36.5053 and a standard deviation of 8.74780. The results of
this study show that the standard deviation value is smaller than the value.
the average distribution of good quality planning. While the quality control
variable has a minimum value of 1.10 and a maximum value of 3.90 with an
average value of 2.5094 and a standard deviation of 0, 68659 the results of
this study indicate the standard deviation value is smaller than the average
value of the distribution of good quality control. And for the final product
variable has a minimum value of 4.49 and a maximum value of 8.89 with an
average value of 6.9833 and a standard deviation of 1.29321. The results of
this study show that the standard deviation value is smaller than the average
value of the distribution of the final product. good.
The normality test will use a
probability plot test, the results of this probability plot test are the data
or points spread around the diagonal line and follow the direction of the
diagonal line, the data is said to be normally distributed. To see the
normality of the residual data, the Kolmogorov-Smirnov statistical test will be
used. The results of the one-to-one test of Kolmogorov Smirnov's production
quality planning show that the Asym value. Sig. (2-tailed) is 0.200 > 0.05,
quality control is 0.200 > 0.05, and the final product shows that the value
of Asym.Sig. (2-tailed) 0.200 > 0.05, it can be concluded that the residual
value of production quality planning, quality control and final product is
normally distributed and this research can be continued to the next stage.
Furthermore, a
multicollinearity test will be carried out, to see whether there is a
multicollinearity test by looking at the Tolerance and VIF values. If the
tolerance value is > 0.10 and VIF has a value < 10, then there is an
indication of high multicollinearity between independent variables. Based on the
multicollinearity test results seen from the production quality planning
variable, it has a tolerance value of 0.854 > 0.10 and a VIF value of 1.170
< 10 so it can be concluded that the production quality planning variable
does not occur multicollinearity. Furthermore, the quality control variable has
a tolerance value of 0.854 > 0.10 and a VIF value of 1.170 < 10. So it
can be concluded that the quality control variable does not occur
multicollinearity.
Then the heteroscedasticity test will be carried
out, using the scatterplots method. The results of the heteroscedasticity test
graph can be seen that the data points spread in all directions and do not form
a certain pattern, so that in this case there is no heteroscedasticity problem
and this research can be continued to the next stage.
Furthermore, an autocorrelation test will be carried
out using the Runs Test, which is part of non-parametric statistics which can
also be used to test whether there is a high correlation between residuals.
Based on the results of autocorrelation using Runs Test when viewed from
Asymp.Sig. (2-tailed) obtained 0.237 > 0.05, it can be concluded that there
is no autocorrelation problem in this study, so it can be continued to the next
stage.
Table 1
Test Results of Multiple Linear Regression
Analysis and Partial Test (T Test)
|
Model
|
Unstandardized
Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
|
B
|
Std. Error
|
Beta
|
|
1
|
(Constant)
|
5.324
|
.987
|
|
�5,393
|
,000
|
|
Quality Planning
|
-.012
|
.987
|
-.083
|
-.484
|
.631
|
|
�
|
.839
|
.322
|
.446
|
2,608
|
.014
|
Based
on the results of the table above the data, the regression equation can be
arranged:
Y =
a + b1 x1 + b2x2
Y =
5.324 - 0.012 + 0.839
Where the regression equation is interpreted at a
constant value of 5.324, it means that if the variables of production quality
planning and quality control are assumed to be zero, then the quality variable
of the final product will have a positive value of 5.324. The value of the
regression coefficient of the production quality planning variable is -0.012,
meaning that if the other independent variables are fixed and the X1 variable
has an increase of 1%, then the final product (Y) will decrease -0.012. A
negative coefficient means that there is a negative relationship between the X1
variable and the Y variable. For the regression value of the X2 variable of
0.839, it means that if the other independent variables have a fixed value and
quality control (X2) has increased by 1%, the final product (Y) will increase
by 0.839.
The hypothesis test carried out is the T test, at T
table = (ɑ/2; nk-1) = (0.05/2;36-2-1) then the value of Ttable = 2.035 is
obtained and based on the test results that the Production Quality Planning
variable ( X1) -0.484 < 2.035 and the Tcount value of -0.484 lies between
the negative effect, meaning that it can be concluded that H1 or the first
hypothesis has a negative effect on production quality planning on the final
product, then Tcount for the Quality Control variable (X2) 2.608 > 2.035
with a significant value of 0.000 < probability 0.05 so it can be concluded
that H2 or the second hypothesis is accepted, meaning that there is a positive
effect of Quality Control on the Final Product. So it
can be concluded that the variable of Production Quality Planning partially has
a negative and insignificant effect on the Final Product,
Table
2
F Test Results
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
1
|
Regression
|
10.373
|
2
|
5.187
|
3.554
|
.040b
|
|
Residual
|
48,161
|
33
|
1,459
|
|
|
|
Total
|
58,534
|
35
|
|
|
|
Based on the results of the simultaneous
significance test (Test F) obtained 3,554. The value of Ftable is obtained
through the Ftable method with dfl = 2 and n = 36 when the formula is entered,
Ftable = (k; nk) then produces numbers (2; 36-2) = (2; 34), the distribution of
the table F value is 3.28 so Fcount 3.554 > Ftable 3.28 then Ho is rejected,
thus meaning that there is a significant effect of the independent variable
(Production Quality Planning and Quality Control) on the dependent variable
(Final Product Results).
Table 3
Coefficient of Determination Test Results
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
|
|
1
|
.421a
|
.177
|
.127
|
1.20806
|
|
Furthermore, the Coefficient of Determination Test,
based on the results of the test calculations, it can be seen that the R number
is 0.421. So it shows a very strong relationship
between Production Quality Planning (X1) and Quality Control (Y). The value of
R2 (R Square) of 0.177 or 17% shows the percentage contribution of the
influence of the independent variable on the dependent variable is 17%. And the
remaining 100% - 23.6% = 76.4% is influenced by other variables that are not
included in the model.
Table 4
Hypothesis Test Results
|
Hypothesi
|
Score
|
description
|
|
Beta
|
Sig
|
|
H1
|
-.484
(T Test)
|
0.631
|
REJECTED
|
|
H2
|
2608
(T Test)
|
0.014
|
RECEIVED
|
|
H3
|
3554
(Test F)
|
0.040
|
RECEIVED
|
B. DISCUSSION
1.
The Effect of Production Quality Planning on the Final Product
Based on the testing
that has been done, the production quality planning has a negative and
insignificant effect on the final product, so it can be concluded that the
first hypothesis or (H1) is rejected. This is inconsistent with or contrary to
the research conducted by Herawati & Mulyani (2016) which states that the production process has a
significant effect on the quality of the product or the final product.
Production quality planning at PT Hema medhajaya is not good because the
planning that has been set by the company's management is not in accordance
with the reality of the final product. If the final product decreases from the
production quality plan, it is caused by inappropriate factors because the raw
materials in the warehouse are empty and often the raw material components that
come are not on schedule. And if the final result of the product increases from
the planning of the production quality, it is caused by the factor of customer
demand who wants to be sent quickly
Based
on the testing that has been done, production quality control has a positive
and significant effect on the final product, so any improvement in quality
control will increase the final product. Then the second hypothesis or (H2) can
be accepted. This is in accordance with the research conducted by Fadilla & Adji (2020) stated that there was a positive change in the
production process, therefore quality control had a positive effect on the
final product. The formulation of the hypothesis proposed in this study is
suspected that quality control using the Quality Control Circle (QCC) method
can be minimized by product failure because it can be said that quality control
of the furniture company at PT Hema Medhajaya is said to be successful or
effective because it can reduce the minimum limit of deviations in the number
of products that occur in production process, and the product fails is still
within reasonable limits. The higher the level of quality control, the lower
the failure of the resulting product.
Based on the results of the
simultaneous significance test (Test F) it can be concluded that the variables
of the influence of quality planning and quality control together have a
significant effect on the final production result in the furniture company at
PT Hema Medhajaya. This is because from the outset good production quality
planning always pays attention to the defective components even though there
are some components that pass due to employee negligence, and quality control
using the Quality Control Circle method focuses more on controlling product
quality in making repairs and minimizing damage. Therefore, good production
quality planning and quality control that are carried out properly will produce
a quality final product. In line with the research conducted by Satyawisudarini (2017) which states the conclusion that the production
process and quality control together affect the quality of the resulting
product.
CONCLUSION
The results of research at PT Hema Medhajaya can be
concluded that production quality planning activities must be checked from the
beginning of production in order to get quality results, and the final product
is controlled for defects based on product standards including specifications.
From the test results Partially, the production quality planning has a negative
and significant effect on the final product until the first hypothesis testing
is accepted. And the partial test results of quality control have a positive
and significant effect on the final product. The second hypothesis is accepted.
The concept of Quality Control Circle is applied to quality control which is
responsible for the implementation of production quality planning. Factors that
cause disability are, first is human resources, most employees do not
understand the standards set by the company, mainly new employees, besides that
each employee has different competencies from one another, as a result, the
number of reworks increases. Then the second is equipment, there is no
equipment that can perform accurate detection of product defects, as a result
many defects in products occur in the production process.
Based on the conclusions that have been presented, get the
following suggestions: Balanced Quality Control Circle is the application of
Total Quality Control, where the company's focus is in the management system on
integrated quality control. All things that become elements in production must
set minimum standards for product defects, understand the several factors that
lead to the failure of a product, and the main reason for the product to fail,
remain with an awareness of the importance of improving quality as well as
productivity. Moreover, it is suggested to the company to pay more attention to
the operator's performance, discuss a lot and provide training to improve its
quality.
The study was conducted using only 2 independent variables
namely Production Quality Planning and Quality Control without considering
other factors that affect the Final Product Results, on the other hand the
sample entered was only 3 years from 2017 - 2019, and only 36 sample data were
obtained, so suggestions for researchers Next, you can add other variables.
More than that, it is hoped that it can provide various
benefits to all parties concerned, some suggestions can be given to the
management of PT Hema Medhajaya, the results of this research can be used for
consideration and evaluation in producing a quality final product. Besides
that, it can also be used as a reference in improving or increasing employee
performance in the future, management is also required to be able to provide a
work environment where employees can freely express their opinions, participate
in decision making, increase employee enthusiasm for their duties and
responsibilities, and ensure that employees work carefully, organized,
effectively and efficiently while still upholding the attitude and K3
(Occupational Health and Safety).
REFERENCES
Ahyari, A. (2000). Manajemen Produksi Perencanaan Sistem
Produksi (Edisi 4). Yogyakarta : BPFE , 1986. Google Scholar
Al Choir, F. (2018). Pelaksanaan Quality Control Produksi
Untuk Mencapai Kualitas Produk Yang Meningkat (Studi Kasus PT. Gaya Indah
Kharisma Kota Tangerang). 1(4), 2598�2893. Google Scholar
Creswell, J. W. (2017). Research design: Qualitative,
quantitative, and mixed methods approaches. Sage publications. Google Scholar
Darsono. (2013). Jurnal Ekonomi � Manajemen � Akuntansi
No. 35 / Th.XX / Oktober 2013 ISSN:0853-8778. 35, 1�17.
Fadilla, F. N., & Adji, S. (2020). Dalam Upaya
Meminimalisir Produk Gagal Menggunakan Pendekatan Statistical Quality Control
(SQC). 02, 107�118.
Herawati, H., & Mulyani, D. (2016). Pengaruh Kualitas
Bahan Baku Dan Proses Produksi Terhadap Kualitas Produk Pada Ud. Tahu Rosydi
Puspan Maron Probolinggo. Prosiding Seminar Nasional, ISBN 978-6,
463�482. Google Scholar
Julaeha, S., Kosim, M. E., & Suryatman, T. H. (2020). Pengendalian
Kualitas Produksi Roma Sandwich Menggunakan Metode Statistik Quality Control
(SQC) Dalam Upaya Menurunkan Reject Di Bagian Packing. Jurnal Industrial
Manufacturing, 5(1), 1�12. Google Scholar
Khatab, A., Diallo, C., Aghezzaf, E. H., & Venkatadri, U.
(2019). Integrated production quality and condition-based maintenance
optimisation for a stochastically deteriorating manufacturing system. International
Journal of Production Research, 57(8), 2480�2497.
https://doi.org/10.1080/00207543.2018.1521021 Google Scholar
Magar, V. M., & Shinde, V. B. (2014). Application of 7
Quality Control ( 7 QC ) Tools for Continuous Improvement of Manufacturing
Processes. International Journal of Engineering Research and General Science,
2(4), 364�371. Google Scholar
Nkadimeng, M. W., Yahia, Z., & Pradhan, A. (2018).
Integration between production planning, quality and sales: A proposed
framework. Proceedings of the International Conference on Industrial
Engineering and Operations Management, 2018(NOV), 787�795. Google Scholar
Satyawisudarini, I., Haryadi, D., Studi, P., Manajemen, S.,
Ekonomi, F., & Langlangbuana, U. (2017). Handa Williani Novianty 1 ,.
1(2), 77�88. Google Scholar
Sugiyono. (2014). Metode Penelitian Pendidikan Pendekatan
Kuantitatif, Kualitatif Dan R &D. Alfabeta. Google Scholar
Sugiyono. (2017). Metode Penelitian Kuantitatif,
Kualitatif dan R&D. Bandung: Alfabeta.
Wei, N.-C., Bao, C.-P., Chen, T.-L., Yao, S.-Y., & Chen,
Y.-Y. (2018). Cloud Service Based Quality Control Circle. International
Journal of Organizational Innovation (Online), 11(2), 65�83. Google Scholar
Whydiantoro,� agus
toni. (2016). Program Studi Teknik Industri , Fakultas Teknik , Universitas
Majalengka Abstrak Tujuan penelitian ini yaitu ; Menganalisis pengaruh
input bahan baku industri terhadap produksi Gula PT . PG . Rajawali Jatitujuh
Majalengka ; Menganalisis pengaruh bahan Maj. 301�309
THE EFFECT OF PRODUCTION PLANNING
AND QUALITY CONTROL ON THE FINAL PRODUCT