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ITEJ (Information Technology Engineering Journals)
Published by Universitas Islam Negeri Siber Syekh Nurjati Cirebon
ISSN : 25482130     EISSN : 25482157     DOI : https://doi.org/10.24235/itej.v7i1
Core Subject :
ITEj (Information Technology Engineering Journals) is a peer-reviewed journal that focuses on the Development of information systems, electronic-based learning, and the application of algorithms and methods in informatics engineering and software engineering. Besides that, the focus is also on developing intelligent systems and artificial intelligence. ITEj (Information Technology Engineering Journals) is published by UIN Siber Syekh Nurjati Cirebon collaborates with Asosiasi Prakarsa Indonesia Cerdas(APIC). Publishing two times a year, ie Issue 1 and Issue 2 in June and December. The journal publishes original research articles and case studies focused on e-learning and information technology. All papers are peer-reviewed by reviewers. The scope of the system discussed is attached but not limited; Systems and software engineering Artificial Intelligence Technology Internet of Thing and Big Data Smart Education systems and components Informatics Management Information Technology etc
Arjuna Subject : -
Articles 128 Documents
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Integration of Multi-Item EOQ and EPQ to Minimize Total Inventory Cost of Outsole Raw Materials Yahya Kusuma; Iriani Iriani
ITEJ (Information Technology Engineering Journals) Vol. 10 No. 2 (2025): December
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v10i2.284

Abstract

This study analyzes the integration of the multi-item Economic Order Quantity (EOQ) and Economic Production Quantity (EPQ) methods to minimize the inventory costs of outsole raw materials at UD. Santoso Mojokerto. The main problem lies in the high storage costs caused by the mismatch between purchasing quantities and the production needs of women’s flat sandals in sizes 37–39. Using demand, production, and inventory cost data for the period of August 2024–July 2025, EOQ is applied to determine the optimal order quantity, while EPQ is used to establish the optimal production quantity. The results show that integrating EOQ and EPQ can reduce total inventory costs compared to the company’s current method, while also maintaining raw material availability and ensuring smooth production processes.
Tsukamoto Fuzzy Logic Method for Determining Mental Health Levels of Final-Year University Students Nabila Rizky Sarip; Sriani Sriani
ITEJ (Information Technology Engineering Journals) Vol. 10 No. 2 (2025): December
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v10i2.291

Abstract

Mental health is an important aspect that affects the ability of final-semester students to complete their studies and face academic and non-academic pressures. The problem that arises is the difficulty in assessing mental health conditions because it is subjective and complex. The Tsukamoto fuzzy method is used because it is able to handle data uncertainty and provides results in the form of measurable crisp values. This study aims to apply the Tsukamoto fuzzy logic method in determining the level of mental health of final-semester students in a more objective and measurable manner. This system model uses four input variables, namely stress level, sleep quality, emotional exhaustion, and duration of gadget use, with 81 rules (rule base) that form relationships between variables. The inference process is carried out through the stages of fuzzification, rule inference, and defuzzification with increasing and decreasing linear triangular membership functions. Testing was carried out using MATLAB by comparing the prediction results to actual data to calculate the model accuracy level using the Mean Absolute Percentage Error (MAPE). The results showed that the total MAPE value was 19.34%, which is in the range of 10%–20% so it is included in the good accuracy category. This demonstrates that the Tsukamoto fuzzy method can provide fairly accurate predictions of the mental health of final-semester students. Therefore, this system can be used as a tool for evaluating and early detection of student mental health in higher education settings.
Waste Analysis in the Aluminum Extrusion Process utilizing Lean Six Sigma and Failure Mode Effect Analysis (FMEA) Gracia Wiranatalie Damanik; Enny Aryanny
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): In Progress
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.293

Abstract

This study aims to identify dominant waste types, analyze the root causes of quality failures, and formulate improvement recommendations to enhance production process efficiency. The methodology integrates Lean Six Sigma and Failure Mode and Effect Analysis (FMEA). Unlike previous studies that focus on a single CTQ in aluminum extrusion processes, this study addresses four dominant CTQs using an integrated Lean Six Sigma and FMEA approach to provide a more comprehensive quality improvement framework. Identification results reveal that defect is the most critical waste, with the highest weight of 0.1206, followed by waiting at 0.0905 and transportation at 0.0854. Root cause analysis of product defects using fishbone diagrams and FMEA indicates that denting poses the highest risk, with a Risk Priority Number (RPN) of 336. Through the proposed improvement designs, the company can entirely eliminate non-value-added (NVA) activities and significantly reduce necessary non-value-added (NNVA) activities. The implementation of these recommendations successfully reduced the total lead time from 2,435.59 minutes to 1,870.41 minutes, resulting in an increase in the Value-Added (VA) time percentage from 40.86% to 46.34%.  
SCM For Monitoring Stock And Demand Online Shop Products Nadrah Umi Kalsum; Riki Andri Yusda; Sumantri
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): In Progress
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.297

Abstract

The development of digital technology is driving the growth of online trading businesses, including sharia fashion businesses that utilize online platforms for their sales activities, faces challenges in managing product stock from various suppliers that are not yet systematically integrated. The imbalance between stock availability and market demand often results in excess stock of less popular products and shortages of stock of products with high demand levels. This condition impacts low operational efficiency and decreases customer satisfaction levels. This study aims to design and implement a web-based Supply Chain Management (SCM) system to monitor and manage product stock and demand effectively. The methods used include system requirements analysis, design using the Unified Modeling Language (UML), and system implementation using the PHP programming language and MySQL database. The results of this study are expected to improve stock monitoring accuracy, accelerate the decision-making process in product procurement, and minimize the risk of overstock and stockouts. Thus, the implementation of SCM can improve inventory management efficiency and response to changes in market demand in the Kisaran Syar'i Online Shop.
Application Of SAW For Best Decor At Mainaka Decoration Anggi Melisa Nasution; William Ramdhan; Zulkarnain Sirait
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): In Progress
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.298

Abstract

The rapid development of the event decoration service industry demands companies to be able to provide optimal services and meet client needs quickly and objectively. Mainaka Decoration as a company engaged in the field of event decoration services faces problems in the process of selecting the best decoration concept which is still done subjectively based on the designer's experience and intuition. This condition causes the decision-making process to be less effective, not standardized, and has the potential to cause a mismatch between client expectations and the decoration results provided. Therefore, a system is needed that is able to assist management in determining the best decoration concept based on measurable criteria. This study aims to design and build a Decision Support System (DSS) in selecting the best decoration concept by applying the Simple Additive Weighting (SAW) method. The SAW method is used to rank several alternative decoration concepts based on predetermined criteria, namely budget, aesthetics, work time, theme suitability, and durability of decoration materials. This study uses a quantitative method with data collection techniques through observation, interviews, and literature studies. The system is designed using Unified Modeling Language (UML) and implemented web-based using PHP programming language with MySQL database. The results of this study indicate that the application of the SAW method in the Decision Support System is able to provide recommendations for the best decoration concepts objectively and systematically according to client needs. The system built can help increase effectiveness and efficiency in the decision-making process, minimize subjectivity in assessing decoration alternatives, and improve service quality and customer satisfaction at Mainaka Decoration
Stunting Risk Cluster Analysis In Petatal Plantation Village Using K-Means Clustering Approach Dewi Andini Putri; Dewi Maharani; Ahmad Muhazir
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): In Progress
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.299

Abstract

Stunting is a chronic nutritional issue that requires accurate, data-driven intervention. This study aims to map the level of stunting risk among toddlers in Perkebunan Petatal Village by categorizing them into high, medium, and low-risk groups. The research method employed is descriptive quantitative, utilizing the K-Means Clustering algorithm to group toddler data based on related risk indicators. The analysis results revealed three risk clusters: Cluster 1 (high risk) consisting of 14 toddler data, Cluster 2 (medium risk) consisting of 17 toddler data, and Cluster 3 (low risk) consisting of 19 toddler data. These findings indicate that while the majority of toddlers fall into the low-risk category, there are still toddlers in the high and medium-risk categories who require specific attention from village authorities and health workers. This information serves as a crucial basis for determining nutritional intervention priorities and designing more targeted and data-driven stunting prevention programs in Perkebunan Petatal Village
K-Means Clustering as a Method for Identifying Consumer Behavior Patterns In Taqimart Urba Yesha Hasibuan; Arridha Zikra Syah; Sudarmin
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): In Progress
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.300

Abstract

Taqimart, as a grocery store developing amid competition from modern retail, still faces challenges in analyzing consumer data, where the transaction data generated has not been optimally utilized to understand consumer shopping behavior patterns. This study aims to identify and classify the shopping behavior patterns of Taqimart consumers by applying the K-Means Clustering method. The data used consist of consumer data and transaction data that reflect shopping behavior characteristics, such as purchase frequency and total spending. The K-Means Clustering method is used to group consumers into several clusters based on the similarity of their shopping behavior. The results of this study can provide more structured consumer segmentation information, helping Taqimart develop more targeted marketing strategies, increase the effectiveness of promotions, and support data-driven business decision-making to enhance business competitiveness
E-CRM System Development Strategy As An Effort To Improve Computer Services and Sales At Media Data Computer Azmi Ainul Rifky; Herman Saputra; Elly Rahayu
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): In Progress
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.301

Abstract

The development of digital technology has significantly changed business patterns and consumer behavior in conducting transactions. Media Data Computer, a business engaged in computer sales, faces challenges in managing customer data that is not yet integrated, which affects the effectiveness of service and marketing strategies. This study aims to design an Electronic Customer Relationship Management (E-CRM) system to improve service quality and sales performance. The method used is descriptive analysis with a web-based system design approach. The results show that the E-CRM system is able to integrate customer data, facilitate the analysis of customer needs, increase customer loyalty, and support more effective and targeted marketing strategies

Page 13 of 13 | Total Record : 128

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