SINERGI Vol.
No.
October 2025: 677-690 http://publikasi.
id/index.
php/sinergi http://doi.
org/10.
22441/sinergi.
Improving the implementation of Indonesian halal logistics: a statistical approach Dwi Agustina Kurniawati1*.
Dwi Kristanto2.
Suhaiza Zailani3.
Muhammad Arief Rochman1.
Cindy Caroline1 Optimization.
Operation Research, and Industrial System Research Group .
ORIS-RG).
Department of Industrial Engineering.
Universitas Islam Negeri Sunan Kalijaga.
Indonesia Department of Industrial Engineering.
Universitas Gadjah Mada.
Indonesia Faculty of Business and Economics.
University of Malaya.
Malaysia Abstract In Indonesia, only a limited number of logistics providers have obtained halal certification, despite halal logistics playing a crucial role in preserving product integrity and preventing crosscontamination.
This study analyzes the implementation of halal logistics by identifying key variables that influence the availability of halal products in the Indonesian market.
Using a quantitative research approach, data were collected through surveys of 108 companies, including 35 logistics service providers and 73 halalcertified MSMEs, as well as semi-structured interviews with logistics service providers and MSME business actors in the food sector.
The data were analyzed using multiple regression analysis to identify the most significant factors influencing the availability of halal products.
The findings suggest that the availability of halal product information, consistent worker training, and corporate environmental responsibility are the primary variables influencing the availability of halal products.
These insights provide a foundation for policymakers to develop regulations that strengthen halal logistics, enabling logistics providers and MSMEs to allocate resources more effectively and maintain halal product availability in the market.
As one of the few studies examining halal logistics in Indonesia's food sector, this research contributes to the broader discourse on halal supply chain management and policy development.
This study highlights the importance of stronger stakeholder collaboration in enhancing halal logistics sustainability in Indonesia.
Keywords:
Halal Logistics.
Multi Regression.
Availability.
Logistics Service Companies.
MSME
Article History:
Received: December 16.
Revised: February 19, 2024 Accepted: March 20, 2024 Published: September 2, 2025 Corresponding Author:
Dwi Agustina Kurniawati Optimization.
Operation Research, and Industrial System Research Group .
ORIS-RG).
Department of Industrial Engineering.
Universitas Islam Negeri Sunan Kalijaga.
Indonesia Email: dwi.
kurniawati@uinsuka.
This is an open access article under the CC BY-SA license INTRODUCTION The halal industry, rooted in Islamic dietary laws, gained significant economic importance in the late 20th century due to globalization, increased consumer awareness, and government regulations that support halal certification .
Beyond food, halal certification now extends to cosmetics, pharmaceuticals, and logistics, shaping the contemporary halal economy .
This expansion has driven the industry's growth beyond Muslim-majority nations, creating a substantial global market .
Figure 1 illustrates the growth of the global halal economy from 2020 to 2024, showing a significant upward trend.
The market value increased from $2.
2 trillion in 2020 to a projected $3.
2 trillion in 2024, highlighting the rising demand for halal products and services worldwide .
According to the Halal Guidebook's second edition, experts predict the global halal economy will reach $3.
2 trillion by 2024, with the food and beverage sector leading the way .
Kurniawati et al.
Improving the implementation of Indonesian halal logistics: A SINERGI Vol.
No.
October 2025: 677-690 Figure 1.
Global Halal Economy Growth Chart For Muslims, food must adhere not only to halal standards prescribed by Islamic law but also meet the criterion of tayyib, ensuring it is wholesome and fit for consumption .
Cross-contamination poses a significant risk, potentially transforming halal products into non-halal ones, highlighting a unique challenge in the industry .
Nugroho et al.
refer to this characteristic of halal products as cross-contamination with nonhalal products.
Cross-contamination occurs due to the discovery of pig DNA, pork, and other ingredients in halal products.
Similarly, in 2014.
Malaysian authorities discovered non-halal ingredients in Cadbury Malaysia's halal chocolate products .
Research on the distribution of halal products is essential to consider the risk of crosscontamination between halal and non-halal The risk is the possibility of crosscontamination, where halal products may become non-halal .
Consequently, research into the distribution of halal products becomes crucial to mitigate the risk between halal and non-halal items, aiming to prevent halal products from inadvertently becoming non-halal .
discovered that Muslim consumers exhibit a high awareness of halal products.
Consequently, inadequate management of halal product distribution can result in issues such as scarcity, overstocking, and product damage due to contamination with non-halal items .
Damaged products contribute significantly to waste within the supply chain, underscoring the need for strategies to manage the impact of waste resulting from product damage .
The implementation of a halal supply chain and effective logistics is crucial to ensure the efficiency and effectiveness of halal product distribution.
The halal supply chain represents a relatively new area in supply chain research, warranting further investigation .
Given this context, there is a pressing need for a study that examines the adoption of halal standards by logistics providers in Indonesia.
Currently, only a small number of logistics providers in Indonesia have obtained halal certification .
However, given the critical role of halal logistics in maintaining the integrity of halal products, it is imperative to conduct comprehensive research and analysis to assess the extent to which logistics providers in Indonesia adhere to halal standards .
This study aims to shed light on the implementation challenges and successes of integrating halal requirements into logistics practices within the Indonesian context.
As noted earlier, there has been an increasing demand for implementing halal supply chains (HSC) and halal logistics to ensure the integrity of halal products .
have proposed frameworks and models for maintaining HSC Several key determinants are crucial for the success of HSC, including government support, transportation planning, information technology, human resources, collaborative relationships, halal certification, and halal traceability .
The need for a supply chain approach to guaranteeing halal integrity, while investigating barriers to managing HSC Therefore, halal logistics plays a crucial role in ensuring the halal status of food products .
Halal logistics encompasses all activities involved in product distribution, contamination prevention processes, and adherence to Shariah principles .
According to Saidah et al.
transportation, warehousing, material handling, and procurement activities must comply strictly with halal requirements.
Implementing halal storage and transportation practices has a significant impact on a company's financial performance .
The necessity of segregating halal and non-halal products during warehousing and transportation to prevent contamination .
Key Halal Compliance Points for processed products emphasize the importance of closely monitoring critical aspects, such as storage, handling, to maintain adherence to halal standards .
Manufacturers are responsible for ensuring products are produced in accordance with halal standards and that there is no crosscontamination with non-halal materials .
implementation of halal supply chains and verification methods is crucial for ensuring the authenticity of these products.
These measures ensure that products meet halal requirements throughout the entire production, distribution, and consumption process.
Kurniawati et al.
Improving the implementation of Indonesian halal logistics: A p-ISSN: 1410-2331 e-ISSN: 2460-1217 Several barriers hinder the widespread adoption of halal logistics certification in Indonesia.
Regulatory challenges, including the complexity of obtaining halal certification and the lack of standardized enforcement mechanisms, have contributed to slow adoption rates .
Additionally, logistical costs associated with maintaining halal compliance, such as dedicated certification fees, create financial burdens for logistics providers, particularly small and medium enterprises .
Furthermore, awareness among logistics companies regarding the importance of halal compliance remains relatively low, resulting in inconsistent implementation of halal logistics practices .
Furthermore, all logistics companies need to use materials derived from halal sources when packaging halal products.
Talib et al.
conducted a study focusing on halal practices within the poultry processing industry, revealing that the use of halal animal feed, adherence to proper sharia-compliant slaughter methods, and appropriate post-slaughter processes .
ncluding handling, packaging, transportation, and storage of poultry product.
are crucial factors determining halal integrity in this sector .
The capabilities of halal logistics play a critical role in maintaining halal integrity throughout the supply chain, from farm to consumer .
Therefore, ensuring the complete separation of halal and non-halal products during logistics operations is necessary to guarantee the halal status of a product .
This practice shields halal products from contamination with non-halal items or substances until they are delivered to the consumer .
In conclusion, the implementation of halal logistics is pivotal in assuring the integrity of halal products.
This involves rigorous adherence to halal standards and practices throughout the logistics process to uphold the sanctity of halal products from production through distribution and consumption.
Conducting a study to analyze the implementation level of logistics providers will enable an assessment of how well logistics providers in Indonesia implement halal standards.
This study aims to derive valuable insights and lessons learned that can inform the formulation of policy proposals for halal logistics in the country.
The research will contribute by examining and analyzing the current state of halal logistics implementation in Indonesia, thereby providing a basis for developing policy recommendations to enhance adherence to halal standards within the logistics sector.
Despite the growing importance of halal logistics, there is a lack of comprehensive studies analyzing the actual implementation level of halal standards among logistics providers in Indonesia.
Previous studies have primarily focused on conceptual frameworks or case studies with limited scope, leaving a research gap in assessing the practical adherence and challenges faced by logistics providers.
METHOD
This study employs a quantitative approach to examine logistics service providers and MSMEs in Indonesia.
The research utilizes a random sampling method to ensure representativeness in data collection.
The selected samples include business operators from the logistics sector and MSME-level business actors from the food sector in Indonesia.
The sample data are collected through randomization.
To provide an overview of the research stages, a summary of each step in the research methodology is provided, offering a comprehensive explanation of each stage described in Figure 2.
Refer to the figure.
The questionnaires are used to collect data from respondents.
The first step in collecting data is a pilot study to determine the validity and reliability of the data, ensuring the validity and reliability of the questionnaires.
Then, the questionnaires are used to collect data until the number of required samples .
is After that, data processing, analysis, and interpretation are conducted to draw conclusions and provide recommendations.
Figure 2.
Research flow diagram Kurniawati et al.
Improving the implementation of Indonesian halal logistics: A SINERGI Vol.
No.
October 2025: 677-690 In this study, the population consists of logistics service providers in Indonesia.
At the same time, the selected samples comprise business operators in the logistics service sector and MSME-level business actors in the food sector in Indonesia.
The sample was drawn using a random sampling method to ensure that each entity had an equal chance of being selected, thereby ensuring the study's results are representative of the broader population.
This research sampled a total of 108 companies, consisting of 35 logistics service companies and 73 MSME-level companies that have obtained halal certification.
This study relies on primary data obtained directly through questionnaire-based assessments by the researchers and secondary data, including R-table information, halal logistics elements, and questionnaires related to halal Data collection in this study used observation, interviews, and questionnaires.
The observation was conducted by directly examining the company's production flow and overall This approach allowed the researchers to understand the flow of the company's supply The research process consisted of three main phases.
The data collection phase, conducted from January to March 2024, involved questionnaires to logistics service providers and MSMEs.
This was followed by the data analysis phase, which took place from April to June 2024, during which responses were processed, statistical tests were performed, and a multiple regression analysis was conducted to identify key Finally, interpretation and report writing phase, conducted from July to August 2024, focused on analyzing findings, drawing conclusions, and preparing the final research documentation.
Interviews were conducted with five company owners from the logistics sector and seven MSME representatives who had obtained halal certification.
Each interview lasted 30Ae45 minutes and focused on four key topics:
distribution methods, and product return The interview questions covered procurement, production, distribution, and product The insights gained from these interviews were later used to design the questionnaires.
The questionnaire method involved distributing a list of questions for respondents to The questionnaires used a Likert scale ranging from 1 to 5, where 1 represents "strongly disagree," 2 represents "disagree," 3 represents "neutral," 4 represents "agree," and 5 represents "strongly agree.
Validity Test Validity refers to the extent to which a measuring instrument accurately measures what it is intended to measure.
A valid instrument effectively demonstrates this by reliably assessing the desired constructs or variables.
In conducting a validity test, researchers typically perform a data sufficiency test at a 5% significance level () and a 95% confidence level, resulting in a critical Zvalue of 1.
The error rate .
is set at 10%.
The assumption is that the population probability of being sampled is 0.
This test determines whether the collected data is adequate for further analysis and interpretation, utilizing formulas such as those described, particularly relevant in contexts where the number of small and medium enterprises is dynamic.
Moreover.
Pearson's product-moment correlation analysis is commonly employed to assess the relationship between individual item scores and the total score.
This analysis helps determine whether the questions effectively measure the underlying constructs.
Firdaus .
suggests using the Pearson product-moment formula to evaluate validity, where if the calculated correlation coefficient .
is greater than the critical value .
, the variable is deemed valid.
otherwise, it is considered invalid.
In summary, validity testing ensures that the instrument used accurately measures the intended variables or constructs .
, employing statistical methods to validate the instrument's effectiveness and reliability in research studies.
Reliability Test A reliability test assesses how consistent the measurement results are when repeated on the exact symptoms multiple times .
Use a measuring tool with the Cronbach Alpha technique in this reliability test.
If a variable is worth measuring, r => 0.
60, it is said to be reliable.
Meanwhile, if a variable is worth a count <0.
60, it is said to be unreliable.
The normality test determines whether the data distribution follows or approaches a normal The Kolmogorov-Smirnov test is one of several tools used to test for normality .
The Likert scale is a tool used to measure the attitudes, opinions, and perceptions of individuals or groups regarding social phenomena .
Multiple regression analysis examines the relationship between a dependent variable (Y) and multiple independent variables (X1.
X2, .
, making it suitable for assessing the factors that influence halal-certified logistics services.
This method helps identify key determinants of logistics efficiency and service availability.
The process begins with data collection that meets classical Kurniawati et al.
Improving the implementation of Indonesian halal logistics: A p-ISSN: 1410-2331 e-ISSN: 2460-1217 regression assumptions, followed by model formulation Y = 0 1X1 2X2 .
nXn e.
Hypothesis testing evaluates the significance of coefficients, and residual analysis ensures compliance with the assumptions.
The results are interpreted through regression coefficients and RA, which measures the model's explanatory power.
higher RA value indicates that the independent variables better explain variations in the dependent variable.
This approach provides a structured analysis for policymakers and logistics providers to enhance the implementation of halal This study aims to address the following research questions: .
What are the key factors influencing the successful implementation of halal logistics in Indonesia? .
What are the main challenges logistics providers face in obtaining halal certification? .
How does the implementation of halal logistics impact the efficiency and integrity of halal product distribution? However, this study has some First, although the sample size is representative, it may not fully capture regional variations in logistics operations.
The remainder of this paper is structured as follows: Section 2 provides a review of the existing literature on halal logistics and supply chain management.
Section 3 discusses the research methodology used in this Section 4 presents the findings and analysis of halal logistics implementation in Indonesia.
Finally.
Section 5 concludes the study with key insights, implications, and recommendations for policymakers and industry stakeholders.
RESULT AND DISCUSSION
Researchers conducted a pilot study before distributing the questionnaire to all respondents, during which they distributed questionnaires to 108 respondents to assess the validity and reliability of the questions provided.
The process of evaluating the research instrument will be carried out with consideration of the answers obtained after filling out the questionnaire, as well as their relevance.
The survey was divided into two sections.
The first section includes respondent biodata, consisting of three questions.
The second section presents research questions that involve 32 variables related to respondents' perceptions of implementing Halal Logistics in Indonesia.
Thirtytwo variables were obtained from distributing By filling in the data, respondents were asked to rate on a scale of 0 - 5, where 0 means "Disagree" and 5 means "Strongly agree".
The total number of respondents in this study was An explanation of the 32 variables is provided in Table 1.
Table 1.
Variables of Halal Logistics Implementation Dimensions Implementation of halal logistics Organization Finance Sub Dimension Variables Availability of Halal Halal products are always available according to Products market demand Information about halal products is always available and transparent The image of the halal product delivery company greatly influences consumer confidence in the Social Workers who handle halal products are highly competent and trustworthy Workers who handle halal products receive training in a planned and consistent manner.
Workers have sufficient knowledge of Islamic law when handling halal products.
Informed data on halal products is harmonized between producers, logistics service providers, and consumers.
Manufacturers and logistics service providers excel at planning and evaluating halal product business strategies.
Stakeholders Halal product business performance indicators are aligned between producers and logistics service The objectives and focus between producers, logistics service providers, and consumers of halal products are aligned to avoid conflicts.
Good management of halal products affects the company's revenue There is growing investment in the halal product Financing Halal product consumers experience significant Description Reference .
X10
X11
X12
Kurniawati et al.
Improving the implementation of Indonesian halal logistics: A SINERGI Vol.
No.
October 2025: 677-690 Dimensions Transporta-tion Sustaina-bility Sub Dimension Variables There are developments in the marketing strategy of halal products Special treatment of halal products affects corporate financing Halal product transportation costs are determined by the quality of service provided The number of products delivered is in accordance with consumer orders Products are distributed with good quality and follow the description provided Reliability During distribution, halal products remain hygienic and are not mixed with non-halal goods.
The temperature of halal products is always well maintained during the shipping process.
Shipping companies can adapt well to halal Electability Shipping companies can cope with fluctuations in demand for halal products.
Halal product deliveries can always be made at a Predetermined time Halal product delivery can be done with the Asset expected frequency Halal product delivery mileage varies widely.
During the distribution process, there is an excessive stock of halal products.
There are many significant threats during the halal product delivery process.
Security Shipping halal products uses separate containers or vehicles from those used for non-halal products.
The company has a target to reduce CO2 Carbon Emissions emissions from year to year Average mileage per shipment of halal products by the company planning Route Optimization Average travel time for shipping halal products according to the company's planning Regulatory The company complies with environmental Compliance regulations when shipping halal products.
The company is responsible for monitoring and Impacts to Air and reducing air and water pollution generated during Water Quality the production and delivery of halal products.
Table 1 outlines the key dimensions of halal logistics implementation, including availability, organization, finance, transportation, asset Availability ensures halal products meet market transparency, consumer trust, and stakeholder Finance examines revenue impact, investment growth, and marketing strategies.
Transportation focuses on reliability, adaptability, and maintaining product integrity.
Asset management ensures timely delivery and stock control, whereas security emphasizes threat Lastly, sustainability addresses carbon emissions, route optimization, and regulatory compliance, forming a structured framework for evaluating halal logistics operations.
Researchers conducted the pilot study to evaluate and improve the developed survey The sampling technique used in the pilot study was convenience sampling, as preferred by the researcher.
It is commonly used for explanatory research or questionnaire testing.
Description Reference X13
X14
X15
X16
X17
X18
X19
X20
X21
X22
X23
X24
X25
X26
X27
X28
X29
X30
X31
X32
but its limitations are notable.
The pilot study was conducted in two stages: qualitative and The qualitative pilot study was used to validate the content and format of the research The first stage, or qualitative pilot study results, was then used as a table of questions for 10 pilot study questions or assessment tools.
The second stage involved the quantitative pilot study.
The quantitative pilot study data are used to test the validity and reliability of the research instrument.
Questionnaire validation is not only based on journal literacy, but also on the validity of experts, ensuring the population is accurately targeted .
The research questionnaire was validated by four individuals, comprising three directors of logistics service providers and one The qualitative pilot study was conducted over four iterations, and no comments were received from the fourth respondent.
therefore, the researchers can use the instrument to collect data.
The results of the first stage, or qualitative pilot study, are then used to improve a questionnaire or research instrument, which is Kurniawati et al.
Improving the implementation of Indonesian halal logistics: A p-ISSN: 1410-2331 e-ISSN: 2460-1217 subsequently used for the second, or quantitative, pilot study.
At this stage, the research instrument underwent evaluation to determine any necessary questionnaire developed in the previous phase.
This evaluation involved testing the validity and reliability of data collected from an initial sample of 30 respondents.
A questionnaire is considered valid if its statements or questions effectively measure the intended variables.
Meanwhile, reliability refers to the consistency or stability of a measuring instrument over time .
The results of the validity and reliability tests ensure that the data obtained are both valid and Should improvements be identified, the researcher adjusts the instrument based on feedback gathered during this evaluation phase.
Conversely, if the survey instrument proves suitable with no further modifications required, it proceeds to the data collection phase.
In this study, the validity test utilized the Spearman correlation test due to the abnormality of the data.
The validity was assessed by comparing the correlation coefficient .
of each statement with the critical correlation coefficient value .
at = 0.
05, set at 0.
Statements were deemed valid if their correlation coefficient .
361, meeting the requirements outlined in Table 2.
Reliability was tested using Cronbach's alpha (), where a higher coefficient indicates greater reliability.
A questionnaire achieves reliability if it achieves a Cronbach's alpha value 6 .
Overall, the reliability test results indicated that all dimensions were reliable.
Table 2 presents detailed outcomes of the validity and reliability tests for each dimension.
This research sampled a total of 108 companies, consisting of 35 logistics service companies and 73 MSME-level business actors from the food sector in Indonesia.
Based on the processing of the analyzed data, it shows that the amount of valid data on all variables is .
= .
, while the amount of missing data on these variables is 0, which means that this data is valid and there is no missing data.
H0: Significance value p > 0.
05, then the data is not normally H1: If the significance value p < 0.
then the data is usually distributed.
Analysis of data normality measured using the Shapiro-Wilk test indicates that all variables analyzed follow a normal distribution characterized by a p-value < 050, which means that there is a rejection of Ho in this hypothesis test.
Table 2 presents the validity and reliability test results for halal logistics dimensions.
Spearman test values .
871Ae0.
and Cronbach's Alpha .
87Ae0.
confirm strong validity and reliability.
All dimensions meet the required thresholds, ensuring consistency in implementation of halal logistics.
At this stage, an assumption test is used for the variables involved in multiple regression to determine whether the data meet the data homoscedasticity, and independence of error.
Assumption testing utilizes histograms to determine data normality, residual graphs with predicted values to assess the independence of error and residuals, and graphs of residuals homoscedasticity and linearity.
Based on Figure 3, the graph indicates that the data is normally distributed because the peaked curve is centered in the middle of the data distribution, and the skewness of the data is also Correlation Analysis From the correlation value, it is found that there is a positive correlation between the dependent variable and other independent Table 2.
Validity and reliability test Variables Organization Finance Transportation Dimensions Social Stakehol Financing Reliability Flexibility Asset Manage Secu-rity Sustainability Carbon Emissio Route Optimiza Regulat Complia Impacts to Air Water Quality Interpretation Validity Relia-bility Spearman Cronbach' s Alpha Valid and Reliable Valid and Reliable Valid and Reliable Valid and Reliable Valid and Reliable Valid and Reliable Kurniawati et al.
Improving the implementation of Indonesian halal logistics: A Valid and Reliable Valid and Reliable Valid and Reliable Valid and Reliable Valid and Reliable SINERGI Vol.
No.
October 2025: 677-690 The most significant correlation is between the dependent variable and variable X1, r.
= .
p < .
001, as well as with other dependent Multicollinearity necessary when multiple predictors are involved, as seen between the dependent variable X12 and X13 .
= 0.
675, p < 0.
and the dependent variable X12 and X14 .
= 0.
450, p < 0.
, which require further analysis using a multicollinearity Linearity testing can be done by analyzing the residuals of the regression model formed.
Figure 3 above shows that the data distribution is evenly distributed, indicating that the data has a linear relationship.
Testing for unequal variance is called the heteroscedasticity test.
Alternatively, testing for the same data variance is referred to as Figure 4 shows the data variance, which does not form a funnel/triangle and/or diamond pattern, indicating that the data falls into the homoscedasticity category.
Regression assumes that each predicted value is independent, meaning that it does not depend on the values of other variables.
If the residuals are independent, the data distribution pattern appears random and similar to the null plot, as shown in Figure 5, which indicates that the data is independent of error.
Figure 3.
Normality Test Density vs.
Residual Figure 4.
Linearity Test Residuals vs.
Dependent Figure 5.
Independence of Error Test Residuals vs.
Predicted The coefficient table obtained for the beta coefficients above shows that the highest Beta value is for X1, which is 0.
513, indicating that variable X1 can cause changes in variable Y by 3%, followed by variable X17 at 25.
So, in this regression equation, the X1 value dominates the dependent variable (Y).
In addition, from the beta coefficient value, it is also known which independent variable has the most dominant The Standardized Coefficient Beta Test compares the Standardized Coefficient Beta values of each variable.
For example, in the case above, the Coefficient Beta value for X1 > X17 means that Information Regarding Halal Products is Always Available and Transparent (X.
contributes dominantly to the implementation of halal logistics compared to other variables.
So it can be concluded, in this regression model, the most dominant variables affecting the dependent variable in order are X1 (Information about halal products is always available and transparen.
X17 (Products are distributed with good quality and following the description give.
X13 (There are developments in the marketing strategy of halal product.
X4 (The workforce handling halal products receives planned and consistent trainin.
X32 (The company is responsible for monitoring and reducing air and water pollution generated during the production and delivery of halal product.
and X12 (Consumers of halal products have experienced significant growt.
When viewed in the coefficient table above, it can be concluded that each independent variable does not exhibit symptoms of multicollinearity in the regression model because all the variables' Tolerance values are > 0.
1 and VIF values < 10.
Multicollinearity checking by building an MLR model on one dependent variable and six independent variables to be predicted.
Next, conduct a collinearity diagnostic analysis by examining the tolerance value and partial Multicollinearity is indicated if the Kurniawati et al.
Improving the implementation of Indonesian halal logistics: A p-ISSN: 1410-2331 e-ISSN: 2460-1217 tolerance value is low (< 1 - RA).
In this case, the value of R2 = 0.
411, so that .
- R2 = 0.
shows that the tolerance value is low on X12 and X13, with tolerances <0.
Furthermore, to see multicollinearity, it is done by looking at the collinearity diagnostics table, where if there are two variables with the maximum value in the same dimension, it is considered to have high in this case, it occurs in variables X12 and X13, where this assumption is reinforced by the substantial correlation value of the two Therefore, the elimination of variable X13 still yields the appropriate analysis.
Variable selection employs the Backward Method, where all predictors are initially included in the model and their respective contributions are Predictors contribution rates .
<0.
were removed from the model/equation.
This process was repeated until all predictors were statistically significant.
After 27 iterations, the following is the best result: the variable with the most influence on the dependent The following is a summary table of the backward method with JASP.
The order of variables using the backward value is determined gradually by the JASP application, which examines the correlation value between variables.
The greater the Pearson's r value of the independent variable on the dependent variable, the greater the level of As for the independent variables, the smaller the R-squared value, the smaller the level of correlation between the independent variables.
This is the basis for decision-making in variable The process of selecting variables ensures the best model fit by minimizing redundancy and improving predictive accuracy.
The Backward Method systematically refines the regression model by eliminating variables with insignificant contributions, ensuring that only the most impactful predictors remain.
This iterative approach enhances the model's explanatory power while reducing potential biases caused by As a result, the refined model provides a more reliable basis for assessing the relationship between independent variables and the implementation of halal logistics.
In general, the above model's R-value is the best, with an R-value of 0.
639 after deducting variables that are considered not to have affected the dependent variable.
The variables selected after 27 iterations, along with an explanation of each, are presented in Table 3.
Table 3.
Key Variables and Descriptions in Halal Product Management Variables Halal products are always available according to market demand Information about halal products is always available and transparent Workers who handle halal products receive training in a planned and consistent manner.
Halal product consumers experience significant growth
There are developments in the marketing strategy of halal products Products are distributed with good
quality and follow the description The company is responsible for monitoring and reducing air and water pollution generated during the production and delivery of halal
Description X12
X13
X17
X32
H0: Significance value p> 0.
05, then there is no effect of the independent variable (X.
on the dependent variable (Y) H1: Significance value p <= 0.
05, then there is an influence of the independent variable (X.
on the dependent variable (Y) In hypothesis testing.
HCA .
ull hypothesi.
states that if the significance value .
is greater 05, the independent variable (X.
does not affect the dependent variable (Y).
Meanwhile.
HCA .
lternative hypothesi.
states that if p is 0.
05 or less, the independent variable (X.
significantly influences the dependent variable (Y).
After examining the regression model with variable selection in Table 4, the model was recalculated using the same regression model, and the Rsquared value for this model is shown in Table 5.
Table 4.
Coefficient Model Unstandar-dized HCA
HCA
(Intercep.
(Intercep.
X12
X17
X32
Standa Stanrd dardiError < .
< .
Table 5.
Model Summary - Y
Model
HCA
HCA
Adjusted RA Kurniawati et al.
Improving the implementation of Indonesian halal logistics: A RMSE SINERGI Vol.
No.
October 2025: 677-690 By using six variables to predict the value of the dependent variable, researchers obtained an R-squared value of 0.
This R-squared value is good enough because the closer it is to 1, the better the model fit by the regression will be.
The value of the latest regression model is presented in the table below.
Based on Table 5, the latest regression model results are as follows: Y = 1,303 0.
534X1 0.
172X4 - 0.
15X12 0.
349X17 0.
201X32.
The results of retesting the regression model using JASP software show the final regression equation or model for the combination of variable Y and 6 X variables (X1.
X4.
X12.
X17.
The equation is Y = 1.
172X4 - 0.
151X12 0.
349X17 - 0.
201X32.
The results of creating this new model are not significantly different from those of the previous one, indicating that the model built is In the model above, this intercept value is only meaningful and predicts logically if X1.
X4.
X12.
X17, and X32 are not equal to 0.
In each regression coefficient, the addition of 1 value of X4 will increase by 0.
This means that the variable of labor handling halal products and receiving training in a planned and consistent manner contributes 0.
175 for an additional value of 1 in predicting that halal products are always available according to market demand.
This is in line with research conducted by .
, .
The exciting thing is that the value of X32 is negative, indicating an opposite effect between variables X32 and Y.
The implication of this finding is the importance of finding a balance between green practices and operational efficiency, as revealed by .
Companies should consider innovations and technologies that can reduce environmental impact without compromising the overall performance of halal logistics.
In this context, if small and medium-scale companies are given more responsibility for sustainability, their performance in providing halal products will be enhanced to meet market needs.
This is relevant to the statement .
that small and medium-scale companies face the main challenge of limited When viewed from the beta coefficient value in regression modelling, the variables that have the most influence on the dependent variable are X1 (Information about halal products is always available and transparen.
X4 (Workers who handle halal products receive training in a planned and consistent manne.
X12 (Consumers of halal products experience significant growt.
X17 (Products are distributed with good quality and following the description provide.
, and X32 (The company is responsible for monitoring and reducing air and water pollution generated during the production and delivery of halal product.
Therefore, the focus of this research on implementing halal logistics should be to increase transparency regarding the halal products and their distribution, ensuring adherence to the rules.
The relationship between increased transparency of information about halal products (X.
not only has a direct impact on consumer confidence but can also strengthen worker performance through practical training (X.
Thus, companies should focus on developing these two implementation of halal logistics.
The synergy between information transparency and worker capability development is crucial in creating a strong and reliable halal supply chain, as stated by .
Additionally, continuing to refine the marketing strategy for halal products and providing training to the workforce on handling halal products is also crucial.
Another factor that affects the dependent variable is the company's responsibility for reducing air and water pollution during the production and delivery of halal As a result, it is expected that consumers of halal products will experience significant growth.
The contribution of the six variables that most significantly affect the performance of halal implementation, in general, is how halal product transparency information is available both from the product handling process during production and during product distribution, where all elements involved are expected to know halal standards, so that training is needed for the relevant workforce in carrying out halal implementation.
In addition, no less important is how the company responds to its role in mitigating adverse environmental impacts associated with the handling and distribution of halal products.
However, the six selected variables, which are indicated to be very significant in influencing the dependent variable, are variables that already demonstrate exemplary performance in improving the implementation of halal logistics.
So, the variables not included in the regression model must be considered.
Researchers/companies must continue to enhance or improve the performance of variables not included in the model to improve the implementation of halal logistics.
One example is variable X10: Effective halal product management has a positive impact on company revenue.
If this performance improves, the implementation of halal logistics will also be better, along with other variables.
Improvements that can be made gradually by the company are to maintain the performance of the fifth variable X1 (Information about halal Kurniawati et al.
Improving the implementation of Indonesian halal logistics: A p-ISSN: 1410-2331 e-ISSN: 2460-1217 products is always available and transparen.
X4 (Workers who handle halal products receive training in a planned and consistent manne.
X12 (Consumers of halal products experience significant growt.
X17 (Products are distributed with good quality and following the description provide.
, and X32 (The company is responsible for monitoring and reducing air and water pollution generated during the production and delivery of halal product.
In addition, improving the performance of variables not included in other models, such as improving the image of a halal product delivery company, significantly affects consumer confidence in these products (X.
The workforce handling halal products is highly competent and trustworthy (X.
The data about halal products is harmonized between producers, logistics service providers, and consumers (X.
This study identifies key factors influencing the availability of halal products, emphasizing the importance of information transparency and employee training.
Unlike previous research, which focuses on theoretical models or specific cases, this study provides a comprehensive empirical assessment.
The findings highlight gaps in halal logistics adherence, which impact consumer trust, policymaking, and operational practices in the logistics and food sectors.
However, potential data collection bias and This study contributes to the implementation of halal logistics in Indonesia and providing actionable policy recommendations.
Future research should investigate the role of technology in enhancing transparency and the external factors that influence policy development.
that the availability of information on halal products is a significant factor affecting consumer In contrast, 85% agreed that consistent training for workers contributes to improved product quality.
Additionally, 70% of respondents noted that a company's responsibility towards environmentally friendly practices also plays a significant role in attracting consumers.
To enhance halal logistics.
SMEs should prioritize product transparency and worker Key strategies include clear halal standards, transparent product tracking, and regular employee training.
These measures can help maintain halal integrity and strengthen consumer trust.
Policymakers can support this by providing incentives and developing infrastructure, such as training centres and integrated distribution systems, to promote broader adoption of halal logistics and strengthen Indonesia's halal industry.
In general, improving the performance of halal logistics implementation is categorized into several aspects, namely enhancing performance during the production and distribution process following Islamic law, employee training to provide a thorough understanding of halal handling standards, transparency of information regarding the process and distribution of halal products so that there is no bias in defining halal products or contamination of halal products, how the logistics distribution performance of halal products in terms of time and distance in delivery and finally focus on how the logistics of halal products can affect the impact on the environment.
Future research could explore a broader sample, including multinational companies, to examine whether the findings hold in different operational scales and CONCLUSION Based on the beta coefficient value in regression modelling, the variables that have the most influence on the dependent variable are X1 (Information about halal products is always available and transparen.
X4 (Workers who handle halal products receive training in a planned and consistent manne.
X12 (Consumers of halal products experience significant growt.
X17 (Products are distributed with good quality and following the description provide.
, and X32 (The company is responsible for monitoring and reducing air and water pollution generated during the production and delivery of halal product.
These findings align with the research objective of effectiveness of halal logistics implementation.
This research has a limited scope, focusing on respondents from SMEs and certain logistics Of the 108 respondents, 75% stated ACKNOWLEDGEMENT The authors acknowledge the full financial support from Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM).
Universitas Islam Negeri Sunan Kalijaga.
Indonesia, for the grant awarded for this research under the Penelitian Kolaborasi Antar Perguruan Tinggi - Research Grant scheme for Year 2023, which made the research and presentation of this paper possible.
REFERENCE