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INDONESIA
Jurnal Inkofar
Published by Politeknik Meta Industri
ISSN : 26153645     EISSN : 25812920     DOI : https://doi.org/10.46846/jurnalinkofar.v9i1
Core Subject :
INKOFAR Journal is an international peer-reviewed journal published by Politeknik META Industri Cikarang. The journal provides a scientific platform for academics, researchers, practitioners, and professionals to publish original research articles, review papers, case studies, and applied research findings. The journal focuses on multidisciplinary studies in the following fields: 1. Industrial Engineering Production and Operations Management Supply Chain and Logistics Management Ergonomics and Human Factors Quality Engineering and Quality Control Systems Engineering and Optimization Sustainable Manufacturing Decision Support Systems Industrial Management and Productivity 2. Computer Engineering and Informatics Artificial Intelligence and Machine Learning Software Engineering Data Science and Big Data Analytics Internet of Things (IoT) Computer Networks and Cybersecurity Information Systems Web and Mobile Application Development Human-Computer Interaction 3. Pharmacy and Health Technology Pharmaceutical Technology Pharmacology and Toxicology Clinical and Community Pharmacy Herbal and Natural Product Research Drug Delivery Systems Biomedical and Health Innovation Pharmaceutical Chemistry Public Health and Healthcare Technology INKOFAR Journal welcomes interdisciplinary research that contributes to scientific development, technological innovation, sustainability, and practical solutions for industry and society.
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Articles 30 Documents
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QUALITY CONTROL ANALYSIS FOR REDUCING DEFECTS IN RAYON NE 30 YARN USING SIX SIGMA DMAIC Afriani Kusumadewi; Susi Maulinawati; Fadil Abdullah
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

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Abstract

Background The textile industry is required to consistently produce high-quality products to maintain competitiveness in an increasingly competitive global market. One of the major quality challenges in spinning industries is the occurrence of product defects that reduce production efficiency and increase manufacturing costs Purpose This study aimed to analyze the quality control performance of Rayon Ne 30 yarn production at PT. X using the Six Sigma DMAIC (Define–Measure–Analyze–Improve–Control) methodology. Methodology A quantitative descriptive approach was employed using historical production and quality control data collected from January to April 2026. Data were analyzed through Critical to Quality (CTQ) identification, Pareto analysis, Defects Per Million Opportunities (DPMO), Sigma capability measurement, Statistical Process Control (SPC) using P-chart, Fishbone analysis, and Five Whys analysis to identify dominant root causes. Findings The results indicated that the production process experienced fluctuating defect levels throughout the observation period, with the highest defect rate occurring in April. Crossing was identified as the dominant defect, followed by Ring and Loose Winding, collectively contributing approximately 85% of total production defects. Implications Process capability analysis showed that the production process had not yet achieved the Six Sigma performance target, while SPC analysis indicated the presence of process variation requiring further investigation. Root cause analysis revealed that machine setting instability, inadequate preventive maintenance, inconsistent operating methods, and operator-related factors were the primary contributors to defect occurrence. Originality Based on these findings, several improvement strategies were proposed, including preventive maintenance scheduling, machine calibration standardization, operator competency improvement, and standardized operating procedures. Since the proposed improvements were not implemented during the study period, their effectiveness could not be statistically validated. Future studies are recommended to conduct industrial implementation and long-term monitoring to evaluate the impact of the proposed improvements on process capability and defect reduction.
Optimizing to Predict Purchase Intention in Fashion Thrifting Using Artificial Neural Networks Approach Fadil Abdullah; Manase Sahat H Simarangkir; Adie Kusna Wibowo; Abdullah Rizky Alfatih; Nadiya Maharani
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

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Background Thrifting has emerged as a prominent trend within the fashion industry, driven by increasing consumer awareness of sustainability and the demand for affordable fashion alternatives Purpose This study develops an Artificial Neural Network (ANN) model to optimize purchase intention for thrifting fashion products based on trends, online promotions, and brand image Methodology The model uses three node variations (10, 20, 30), two hidden layers, a sigmoid activation function, 10,000 iterations, and a feed-forward propagation algorithm. The 30-node configuration performed best, achieving a determination coefficient of 0.97 during training and 0.98 during testing, indicating high predictive accuracy. Findings The findings confirm that trends, online promotions, and brand image significantly influence purchase intention, demonstrating the model’s potential to optimize marketing strategies. By leveraging ANN, businesses can enhance marketing efficiency, adapt to market dynamics, and improve decision-making Implications This research highlights the effectiveness of AI-driven methodologies in analyzing consumer behavior and supporting targeted marketing efforts. The model’s success also suggests broader AI integration possibilities in strategic planning for the fashion industry Originality this study contributes to the literature by providing deeper insights into purchase intention formation and offers practical implications for improving marketing efficiency and strategic decision-making in sustainable fashion businesses
DESIGN OF A DIGITALIZED INDEPENDENT WASTE BANK INFORMATION SYSTEM USING GOOGLE APPS SCRIPT WITH AN INTEGRATED INPUT GATEWAY AND LIVE CALCULATOR Fery Andika Kurniawan
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

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Conventional waste bank management often faces challenges regarding transaction data recording accuracy, the risk of incorrect resident ID entry, and delays in updating savings balance information. This research aims to design and implement a digitized, web-based independent waste bank information system using Google Apps Script (GAS), Google Sheets as the database, and Bootstrap for the user interface. The design methodology focuses on minimizing human error by implementing a "Resident ID Master Input" feature (Single Input Gate) that integrates and locks transaction data, alongside a "Live Calculator" for real-time Rupiah value simulations based on pricing data from the *Harga_Komoditas* (Commodity Prices) sheet. Testing results demonstrate that the system successfully eliminates ID input errors across transaction modules (Waste Deposit and Cash Withdrawal), presents transaction history in reverse-chronological order (newest first) with precise timestamps, and displays resident financial data instantly without synchronization delays.
COOLING LOAD-BASED RETROFITTING OF BRIDGE AIR CONDITIONING SYSTEM TO IMPROVE THERMAL COMFORT AND OPERATIONAL SAFETY ON TB. ANANTA SESA 1 Windy Jayusman; I Putu Hikariantara; Ulpen Hiermy; Doni Suseno; Mochammad Zoehry
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

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Background The bridge compartment of a vessel serves as the primary operational area where navigation and monitoring activities are conducted continuously. Maintaining an adequate thermal environment with in this space is essential to ensure operator comfort, concentration, and operational safety Purpose This study aimed to evaluate the cooling load requirements of the bridge compartment onboard TB. Ananta Sesa 1 and assess the effectiveness of an air conditioning retrofitting strategy in improving thermal comfort conditions Methodology The research employed a field observation approach combined with cooling load calculations using the Cooling Load Temperature Difference (CLTD) method. Findings Internal heat gains from occupants and navigation equipment, as well as external heat gains from solar radiation, wall and roof heat transfer, and air infiltration, were considered in the analysis. The results indicated that the total cooling load of the bridge compartment reached 15,900 BTU/h, exceeding the capacity of the existing 1 PK air conditioning unit rated at 9,000 BTU/h. To address this deficiency, the existing system was replaced with a 1.5 PK split air conditioning unit utilizing R32 refrigerant. Performance testing demonstrated that the retrofitted system reduced the indoor temperature from 36°C to 25.5°C within 60 minutes of operation. The measured relative humidity remained at approximately 55%, which is consistent with thermal comfort recommendations provided by ASHRAE Standard 55 Implications These findings indicate that the retrofitting strategy successfully improved the cooling performance of the bridge compartment and provided thermal conditions that support operator comfort and safe vessel operation Originality The results may serve as a practical reference for cooling system evaluation and retrofit planning in similar marine applications.
OUTPATIENT PATIENT SATISFACTION WITH MEDICATION INFORMATION SERVICES AT X PRIMARY INPATIENT CLINIC BASED ON MINISTER OF HEALTH REGULATION NO. 34 OF 2021 Putri Ade Fitriani; Tisa Amalia; Ayu Izzatin Haifa
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

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Abstract

Background Drug information services are a critical component of pharmaceutical care, ensuring patient safety and therapeutic adherence. However, suboptimal delivery of drug information remains a challenge in primary health facilities, potentially leading to patient non-compliance and increased risk of adverse drug reactions. Purpose This study aims to determine the level of outpatient satisfaction with drug information services at Klinik Pratama Rawat Inap X based on Regulation of the Minister of Health Number 34 of 2021 concerning Pharmaceutical Service Standards in Clinics. Methodology A descriptive quantitative method with a cross-sectional approach was employed. Data were collected through a validated nine-item questionnaire distributed to 98 outpatients selected using the Slovin formula. Data analysis used Likert scale (1-5) with percentage calculation and categorized into five satisfaction levels.. Findings The overall satisfaction rate was 69% (satisfied category). The highest score was for drug benefit information (85%, very satisfied), while the lowest was for drug storage information (69%, satisfied). Three mandatory information items, side effects (70%), precautions (70%), and storage (69%), were at the lower threshold of the satisfied category. The staff-to-patient ratio (1:85) exceeded the recommended standard (1:50), contributing to incomplete information delivery. Implications This study recommends strengthening regulatory compliance, increasing pharmaceutical staff capacity, and improving supervision of drug information services in primary health facilities to enhance patient satisfaction and therapeutic outcomes. Originality This research provides a comprehensive evaluation of outpatient satisfaction with drug information services specifically in a primary care clinic setting, using a multidimensional assessment aligned with national regulatory standards.
IMPLEMENTATION OF THE K-NEAREST NEIGHBOR METHOD FOR AN EQUIPMENT INVENTORY SYSTEM AT THE XYZ CITY FIRE AND DISASTER MANAGEMENT DEPARTMENT Dafa Arya Wijaya; Febie Elfaladonna; Meivi Kusnandar; Deri Darfin; Devi Sartika
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

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Abstract

Background Inventory management is essential for ensuring the availability, traceability, and proper maintenance of organizational assets. However, the XYZ City Fire and Disaster Management Department still manages inventory using Microsoft Excel, resulting in inefficient data processing, limited accessibility, and a high risk of data entry errors. Purpose This study aims to develop a web-based inventory management system integrated with the K-Nearest Neighbor (KNN) algorithm to improve inventory management efficiency and automatically evaluate equipment feasibility. Methodology A web-based inventory application was developed to manage inventory records and classify equipment conditions using the K-Nearest Neighbor (KNN) method. System performance was evaluated using classification metrics, including accuracy, precision, recall, and F1-score. Findings The developed system successfully automated inventory management and equipment feasibility assessment. Experimental results showed that the KNN model achieved 100% accuracy, precision, recall, and F1-score, demonstrating its effectiveness in classifying equipment as either suitable for continued use or requiring replacement. Implications The proposed system provides a practical solution for improving inventory management by increasing data accuracy, accelerating decision-making, and supporting real-time monitoring of equipment conditions. Although the system performed exceptionally well in this study, further validation using larger and more diverse datasets is recommended to evaluate its scalability and generalizability.. Originality This study integrates a web-based inventory management system with the K-Nearest Neighbor algorithm to automate equipment feasibility evaluation in a fire and disaster management agency, providing an accurate, efficient, and real-time decision-support tool for inventory management.
Design and Implementation of an Android-Based Student Attendance Application Utilizing QR Codes to Enhance Presence Efficiency Dyah Ayu Nurmumpuni; Angelina Hadriani
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

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Background Manual student attendance recording in educational institutions is inefficient, error prone, and susceptible to proxy attendance (titip absen). Physical presence recapitulation also delays real time attendance reporting for administrators and parents. Purpose This study designs, implements, and evaluates an Android based attendance information system incorporating dual factor verification through dynamic QR codes and location based geofencing. Methodology The system combines dynamically rotating QR tokens (60 second expiration) with the Haversine formula for real time GPS distance validation within a 50M radius boundary. System performance and user acceptance were evaluated using Black box testing, UAT, MOS surveys (N = 5 teachers, N = 30 students), response latency benchmarking, and server load stress testing up to 100 concurrent requests. Findings Empirical evaluation demonstrates that the proposed system reduces classroom attendance duration from an average of 12.5 minutes (10 to 15 minutes) to 1.4 minutes per class session, achieving an 88.8% reduction in administrative time. The average MOS satisfaction score reached 4.57/5.00 for teachers and 4.62/5.00 for students (Excellent category). Response latency benchmarks yielded an average response time of 245 ms under standard operational conditions, maintaining a 0.0% error under load tests up to 50 concurrent requests. Implications The solution offers primary educational institutions a cost effective attendance verification without requiring dedicated door terminal hardware, while providing guidelines for managing indoor GPS signal drift. Originality The primary scientific contribution lies in integrating short lived cryptographic QR tokens with GPS geofencing on commodity mobile devices, providing a zero hardware, zero proxy presence verification mechanism tailored for primary schools.
The Role of Digital Capabilities in Enhancing Customer Satisfaction through Product Quality and Service Quality. Ikbal Anggara; amalia amalia
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

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Background The increasing competition in the fashion industry requires companies to continuously improve their capabilities to maintain customer satisfaction. In this context, digital capabilities have become an important factor that supports firms in improving product and service performance Purpose This study aims to examine the role of digital capabilities in enhancing customer satisfaction through product quality and service quality in the context of local sport fashion brands in Indonesia Methodology The study employs a quantitative approach using data collected from 100 respondents who have experience purchasing products from local sport fashion brands. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings The results indicate that digital capabilities have a significant positive effect on both product quality and service quality. Furthermore, product quality and service quality significantly influence customer satisfaction. Implications The findings also reveal that digital capabilities indirectly enhance customer satisfaction through improvements in product and service quality. These results highlight the importance of integrating digital technologies into business processes to improve product performance and service responsiveness. Originality The study provides practical implications for local sport fashion brands to strengthen their digital capabilities in order to enhance customer satisfaction and maintain competitiveness in the market.
Explainable Hierarchical Retail Demand Forecasting With Time-Series Foundation Models: Comparison With Statistical And Machine Learning Methods Abdul Rohim; Novi Wulandari
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

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Background Retail demand forecasting across multiple aggregation levels is essential for consistent strategic and operational decision-making. Purpose This study develops an explainable hierarchical forecasting framework for weekly retail sales using Seasonal Naive, XGBoost, and LightGBM base models with Base Forecast, Bottom-Up, MinT-OLS, and MinT-Shrink reconciliation. Methodology Unlike single-level retail studies, the framework jointly evaluates accuracy, cross-level coherence, and TreeSHAP interpretability at total, category, and subcategory levels under leakage-safe temporal validation. The Kaggle Superstore Sales Analysis dataset was aggregated into 209 weekly periods containing one total-sales series, three category series, and 17 subcategory series. Findings The final four weeks were reserved as a strict holdout, while the preceding 205 weeks were evaluated using five expanding-window rolling-origin folds with a four-week horizon. LightGBM with MinT-OLS was selected by cross-validation, achieving an MAE of 1,344.3577, RMSE of 2,465.7518, WAPE of 48.4886%, MASE of 2.5970, and zero coherence error. When refitted on the full development period, the selected configuration achieved a holdout WAPE of 63.9589%. TreeSHAP identified rolling_mean_13, lag_52, rolling_mean_8, rolling_std_13, and lag_26 as the strongest predictors. Implications The dependence plot revealed a nonlinear increase in the contribution of rolling_mean_13, moderated by annual-lag conditions. Originality These results demonstrate that reconciliation can improve volume-weighted accuracy and eliminate contradictory forecasts, although intermittent subcategory demand and holdout variability remain important limitations.  
An Integrated Web-Based Monitoring System For Optimizing The Supervision Of Student Internships And Final Projects Ilyas Ruhiyat; Nita Winda Sari; Adie Kusna Wibowo; Santo Wijaya; Manase Sahat H Simarangkir
INKOFAR Vol. 10 No. 1 (2026)
Publisher : Politeknik META Industri Cikarang

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Abstract

Background : The implementation of Field Work (PKL)/Internships and Final Projects is an important part of the academic process at universities, requiring ongoing monitoring by academic advisors and academic programs. However, at many universities, the monitoring of these two activities is still conducted through separate platforms, resulting in inefficient data management, disjointed information, and difficulties in comprehensively tracking student progress Purpose : This research aims to develop and implement a web-based monitoring platform that integrates the supervision processes for PKL/Internships and Final Projects into a single system, so that all data, advising activities, progress, and academic documents can be managed centrally Methodology : The system was developed using the Waterfall method, which includes requirements analysis, design, implementation, testing, and maintenance, utilizing the Laravel framework, the PHP programming language, and a MySQL database Findings : System validation was performed through Black Box Testing on 10 test scenarios. Test results showed a 100% success rate for system functionality, meaning all key features operate as intended to meet user needs Implications : The integration of the monitoring processes for internships and final projects into a single platform is the primary contribution of this research, as it enables unified progress monitoring, reduces data management duplication, and provides consistent academic information for all stakeholders. Originality : The system’s implementation offers benefits such as improved efficiency in the monitoring process, ease of tracking student progress in real time, accelerated academic administration, and the provision of more accurate information as a basis for evaluation and decision-making.

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