JCEIT: Journal of Computer Engineering and Information Technology
type: channel
description: The Journal of Computer Engineering and Information Technology (JCEIT) is a peer-reviewed scientific journal published by Karya Techno Solusindo, with its first issue released in 2024. The primary goal of this journal is to provide a reliable and high-quality platform for publishing articles that reflect the latest and most impactful advancements in computer science. Through its rigorous Double Blind Review process, JCEIT ensures that only the most significant and relevant contributions are selected, thereby promoting cutting-edge research that helps advance the field. The journal serves as an essential resource for researchers, practitioners, and academics who seek to stay informed about new developments and groundbreaking ideas within computer science. JCEIT is published consistently three times a year, with issues released in November, March, and July. This regular publication schedule is designed to provide timely and continuous access to new research and developments, allowing readers to keep pace with the rapidly evolving landscape of computer science. The journal’s triannual frequency also ensures that it can accommodate a diverse range of high-quality submissions, giving authors a dependable and well-regarded venue to share their work with the academic and professional communities. JCEIT is officially registered with ISSN 3089-106X (online) based on the decree of the Direktur Pusat Nasional ISSN Indonesia No. 3089106X/II.7.4/SK.ISSN/02/2025, ensuring its credibility and recognition as an authoritative scientific publication.
publisher: Karya Techno Solusindo
language: en-US
publication name: JCEIT: Journal of Computer Engineering and Information Technology
issn: 3089-106X
items: Product Segmentation for Apparel MSMEs Using K-Means and CRISP-DM Approach
items: Mapping Research Trends of Query Expansion in Information Retrieval: A Bibliometric Analysis
items: Real-Time Air Quality Prediction Using Metrologically Calibrated Gas Sensors and Random Forest Algorithm
items: Development of a Student-Centered Digital Mathematics Learning Prototype Using the ADDIE Model to Improve Conceptual Understanding
items: Performance Analysis of Mesh Network Implementation Using Mikrotik RouterBoard 941 in Radio Link-Based Secure Networks
items: Performance Analysis of Mesh Networking Implementation on Mikrotik Router Board 941
items: Development of an Arduino-Based Truck Load Detection System for Bridge Safety Monitoring
items: Naive Bayes Classification for Construction Workforce Requirement Prediction

Product Segmentation for Apparel MSMEs Using K-Means and CRISP-DM Approach
type: item
description: Apparel Micro, Small, and Medium Enterprises (MSMEs) frequently provide significant sales data that is inadequately leveraged for strategic business advancement. This study intends to examine sales data utilising the K-Means Clustering technique within the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. The dataset consists of 360 sales records during the period 2021–2023, including factors such as amount sold, unit price, and total turnover. The analysis adheres to the systematic CRISP-DM phases: business understanding, data understanding, data preparation, modelling, assessment, and deployment. The assessment outcomes, quantified by the Silhouette Score, determined two ideal clusters for the dataset. Cluster 1 denotes well-performing products distinguished by elevated sales volume, comparatively high unit prices, and substantial turnover. Conversely, Cluster 2 comprises underperforming products characterised by diminished sales volume, reduced unit pricing, and negligible turnover. These findings offer a data-driven basis for MSMEs to develop more efficient marketing strategies and inventory management procedures. By categorising products according to performance, business owners can prioritise high-value commodities and optimise inventory for less productive categories. This study indicates that employing K-Means clustering inside the CRISP-DM framework effectively converts raw sales data into meaningful business intelligence for the garment sector. Subsequent study may enhance this technique by integrating external variables, including seasonal trends or customer demographics, to improve clustering precision. REFERENCES Abdul-Azeez, O., Ihechere, A. O., & Idemudia, C. (2024). Enhancing business performance: The role of data-driven analytics in strategic decision-making. International Journal of Management and Entrepreneurship Research, 6(7), 2066–2081. https://doi.org/10.51594/ijmer.v6i7.1257 Afari, I. S. (2023). K-medoids customer segmenta…
creator: Rahmat Hidayat
rights: Copyright (c) 2026 JCEIT: Journal of Computer Engineering and Information Technology https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-12
publication date: 2026-03-12
volume: 2
number: 2
starting page: 93
ending page: 104
doi: 10.64810/jceit.v2i2.44

Mapping Research Trends of Query Expansion in Information Retrieval: A Bibliometric Analysis
type: item
description: This study aims to analyze the development of research on query expansion in the field of information retrieval using a bibliometric approach to understand research trends, distribution, and current research focus. The data were obtained from 676 publications indexed in Scopus during the period from 2020 to February 2026. The research method involves quantitative analysis of annual publication trends, distribution of subject areas, document types, and keyword analysis using VOSviewer to map keyword relationships through co-occurrence analysis, overlay visualization to identify keyword trends, and density visualization to observe the concentration of research topics. The results show fluctuations in the number of publications with a peak occurring in 2025 with 141 publications. The research is dominated by the Computer Science field with 596 publications, and the majority of documents are conference papers with 369 publications. Keyword analysis identifies core topics such as information retrieval with 483 occurrences, query expansion with 354 occurrences, and search engines with 221 occurrences. Recent research trends include large language models, word embedding, and retrieval-augmented generation. The keyword network visualization indicates a shift from traditional methods such as relevance feedback toward modern approaches based on artificial intelligence and machine learning, which are increasingly relevant for improving the effectiveness of information retrieval systems. These findings provide both quantitative and qualitative insights into the evolution of query expansion research. The results also highlight the integration of modern technologies in retrieval practices and provide a foundation for new researchers to identify trends, research gaps, and opportunities for future innovation. REFERENCES Ahmed, M. (2024). Bibliometrix: An Easy Yet Powerful Approach for Quantitative and Qualitative Analyses of Scholarly Literature. Information Research Communications…
creator: Roberto Kaban
rights: Copyright (c) 2026 JCEIT: Journal of Computer Engineering and Information Technology https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-26
publication date: 2026-03-26
volume: 2
number: 2
starting page: 105
ending page: 119
doi: 10.64810/jceit.v2i2.57

Real-Time Air Quality Prediction Using Metrologically Calibrated Gas Sensors and Random Forest Algorithm
type: item
description: The increasing level of urban air pollution requires monitoring system that are capable not only of measurement but also real time prediction. Low coast gas sensor such as MQ-135 are widely used due to their affordability and ease of integration. However, these sensors exhibit limitations in terms of accuracy, signal stability, and drift characteristics. This research proposes a real time air quality prediction model based on gas sensor data using a machine learning approach integrated with metrological calibration. The system consists of a microcontroller base data acquisition module, aserver for data storage, and a predictive model deployed for real time computation. Data were collected over a controlled observation period with fixed sampling intervals. Preprocessing steps included regression based calibration, min max normalization, and noise reduction using a movig avarage filter. Three algorithms were evaluated Linear Regression, Random Forest, and Long Short-Term Memory. Model performance was assessed using Root Mean Square Error, Mean Absolute Error, and coefficient of determination. The results indicate that the Random Forest model achieved the lowest RMSE and demonstrated stable prediction performance under sensor signal fluctuations. The integration of calibration prior to model training significantly improved prediction accuracy compared to models without metrological correction. The proposed system provides reliable real-time air quality prediction and can support intelligent environmental monitoring and local decision-making processes. REFERENCES Alahi, M. E. E., Sukkuea, A., Tina, F. W., & Mukhopadhyay, S. C. (2020). Integration of IoT-enabled technologies for air quality monitoring and prediction. IEEE Internet of Things Journal, 7(10), 9871–9882. https://doi.org/10.1109/JIOT.2020.2994523 Chen, J., Li, X., Wang, Y., & Zhang, H. (2022). Comparative evaluation of machine learning models for air pollution forecasting. Atmospheric Environment, 268, 118804…
creator: Nurhafiz Ahmad Rangkuti
rights: Copyright (c) 2026 JCEIT: Journal of Computer Engineering and Information Technology https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-02
publication date: 2026-04-02
volume: 2
number: 2
starting page: 120
ending page: 128
doi: 10.64810/jceit.v2i2.59

Development of a Student-Centered Digital Mathematics Learning Prototype Using the ADDIE Model to Improve Conceptual Understanding
type: item
description: Mathematics learning in higher education still faces challenges in the form of low student conceptual understanding due to the dominance of procedural approaches and the suboptimal use of digital technology. Furthermore, there are still gaps in the development of structured, student-centered, and integrated learning designs in the form of prototype-based digital learning systems. This research aims to develop a student-centered digital mathematics learning prototype using the ADDIE model to improve conceptual understanding. This research employed a Research and Development (R&D) method with Analysis and Design stages. The results are a learning prototype design that includes learning objectives, material structure, student-centered learning strategies, digital media, student activities, and an evaluation system. The prototype is designed to support concept visualization, learning interactions, and exploration and problem-solving activities. The results indicate that the developed prototype has the potential to systematically and interactively improve the effectiveness of mathematics learning. In conclusion, this prototype can serve as the basis for developing innovative digital mathematics learning. The novelty of this research lies in the integration of the ADDIE model with a student-centered approach in the design of a comprehensive digital learning prototype. REFERENCES Anisa Ulva Wahyuni & Hasanuddin. (2025). Teknologi Digital dalam pembelajaran Matematika: Tinjauan Bibliometrik terhadap Dampaknya pada Pemahaman Konsep Matematis Siswa. Buana Matematika : Jurnal Ilmiah Matematika Dan Pendidikan Matematika, 15(1), 41–56. https://doi.org/10.36456/buanamatematika.v15i1.10341 Cevikbas, M., Greefrath, G., & Siller, H.-S. (2023). Advantages and challenges of using digital technologies in mathematical modelling education – a descriptive systematic literature review. Frontiers in Education, 8, 1142556. https://doi.org/10.3389/feduc.2023.1142556 Fawns, T., Ross, J., Carbo…
creator: Ita Margaretta Br Tarigan
rights: Copyright (c) 2026 JCEIT: Journal of Computer Engineering and Information Technology https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-02
publication date: 2026-04-02
volume: 2
number: 2
starting page: 129
ending page: 137
doi: 10.64810/jceit.v2i2.58

Performance Analysis of Mesh Network Implementation Using Mikrotik RouterBoard 941 in Radio Link-Based Secure Networks
type: item
description: The increasingly rapid development of computer network technology demands a network system that is reliable, flexible, and able to adapt to dynamic environmental conditions. One of the network technologies that is currently developing is mesh networking. Mesh networking is a network topology where each node can be connected to each other directly or indirectly through other nodes. This research aims to analyze the application of the mesh networking method using the Mikrotik RouterBoard 941 device. The research method used is experimental by configuring, implementing, and testing mesh networking on the Mikrotik RouterBoard 941. The results of the research show that mesh networking can be applied to the Mikrotik RouterBoard 941 by utilizing available features, such as OLSR (Optimized Link State Routing) and WDS (Wireless Distribution System). Mesh networking is able to increase redundancy and network availability, and can adapt to changes in network topology. However, mesh networking also has several disadvantages, such as configuration complexity, routing overhead, and the possibility of bottlenecks at certain nodes. REFERENCES Adiguna, M. A. (2022). WPA2-PSK network security analysis using penetration testing method (Case study: TP-Link Mercusys MW302R router). Anhar. (2020). Jaringan komputer dan internet. Informatika. Athailah. (2020). Bandwidth management in optimizing the use of Mikrotik routers for network connection services. Journal of Informatics, 7(2), 70–78. Brown, S. (2021). Computer network development system. McGraw-Hill. Cisco Networking Academy. (2020a). Introduction to networks: OSI model. Cisco Press. Cisco Networking Academy. (2020b). The application of virtual local area network. Journal of Electrical Engineering Innovation, 1(1), 70–80. Danniel. (2021). Comparison of IPv4 and IPv6 in building networks. International Journal of Computer Networks, 3(2), 30–40. Efendi, M. Y. (2021). Comparative analysis of 128-bit WEP and WPA wireless security metho…
creator: Riska Andian Turnip
creator: Kitu Gea
creator: Yoga Pramadio Purba
creator: Rasme Kita Kaban
creator: Sumarlin
creator: Ita Margaretta Br Tarigan
rights: Copyright (c) 2026 JCEIT: Journal of Computer Engineering and Information Technology https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-31
publication date: 2026-03-31
volume: 2
number: 2
starting page: 138
ending page: 149
doi: 10.64810/jceit.v2i2.53

Performance Analysis of Mesh Networking Implementation on Mikrotik Router Board 941
type: item
description: The increasingly rapid development of computer network technology demands a network system that is reliable, flexible, and able to adapt to dynamic environmental conditions. One of the network technologies that is currently developing is mesh networking. Mesh networking is a network topology where each node can be connected to each other directly or indirectly through other nodes. This research aims to analyze the application of the mesh networking method using the Mikrotik RouterBoard 941 device. The research method used is experimental by configuring, implementing, and testing mesh networking on the Mikrotik RouterBoard 941. The results of the research show that mesh networking can be applied to the Mikrotik RouterBoard 941 by utilizing available features, such as OLSR (Optimized Link State Routing) and WDS (Wireless Distribution System). Mesh networking is able to increase redundancy and network availability, and can adapt to changes in network topology. However, mesh networking also has several disadvantages, such as configuration complexity, routing overhead, and the possibility of bottlenecks at certain nodes. REFERENCES Aisyah, A. (2022). Mesh Network Model On Internet Of Things (IoT) Systems For Environmental Monitoring. Ardhitya, A. I. (2021). Definition and Explanation of Microtics. Available at Http://Ilmukomputer. org/2013/01/04/Definition-and-Explanation-Mikrotik/. Accessed, 20. Arman, M., & Kasran, K. (2023). Wireless Network Analysis on IoT-Based ATM Machines at PT. Bank Negara Indonesia (Persero) Tbk KCP Watansoppeng. Scientific Journal of Information Systems and Informatics Engineering (JISTI), 6(1), 77–84. https://doi.org/10.57093/jisti.v6i1.151 Bahtiar, D., Febrianto, W. J., Maulana, A., Saputra, S., Darmawan, W., Tafonao, R. P., Julianto, R., Zai, R., & Djutalov, R. (2021). Basic Introduction to Computer Network InstallationUsing Mikrotik. Informatics Student Creativity, 2, 507–518. Fahmi Faizar, F. (2020). The effect of Bluetooth 5.0 interferenc…
creator: Yudi Abdul Halim
creator: Darwin Panjaitan
creator: Alexander Silitonga
creator: Suata Wan Kelispa Halawa
creator: Roberto Kaban
creator: Meiliyani Br Ginting
rights: Copyright (c) 2026 JCEIT: Journal of Computer Engineering and Information Technology https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-31
publication date: 2026-03-31
volume: 2
number: 2
starting page: 150
ending page: 159
doi: 10.64810/jceit.v2i2.54

Development of an Arduino-Based Truck Load Detection System for Bridge Safety Monitoring
type: item
description: The safety of bridge structures is very important to consider, especially in withstanding the weight of passing trucks. Overloading can cause structural damage that can potentially jeopardize the safety of bridge users. Therefore, a truck load weight detection system is needed that is able to monitor the load in real-time and provide early warning in the event of overloading. This research aims to design and implement an Arduino-based truck load weight detection system installed on the bridge. This system uses a load sensor (load cell) to measure the weight of passing vehicles, where the weight data is then processed by an Arduino arduiuno. The system is equipped with a wireless communication module that allows weight data to be sent directly to the control center or bridge operator. The results of system testing show that this system is able to detect the weight of truck loads with a good level of accuracy. With this system, it is expected to improve bridge safety and provide accurate information related to the distribution of loads passing over the bridge. REFERENCES Arsyad, O. R., & Kartika, K. P. (2021). Design and build safe safety devices using Arduino-based fingerprint sensors. JATI (Student Journal of Informatics Engineering), 5(1), 1–6. Gunawan, G., & Ardiyansyah, M. R. (2023). Design and build an Arduino-based photovoltaic panel performance tester. State Polytechnic at the End of the Line. Handiko, Y. T. (2022). Design and Build a Digital Scale Model Using Load Cell Sensors and IoT-Based Scale Recording. Kartika Riyanti, K. P., Kakaravada, I., & Ahmed, A. A. (2022). An Automatic Load Detector Design to Determine the Strength of Pedestrian Bridges Using Load Cell Sensor Based on Arduino. Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics, 4(1), 15–22. https://doi.org/10.35882/ijeeemi.v4i1.3 Kazuya, A. S., Ariyadi, T., Dasmen, R. N., & Fitriani, E. (2024). Design of Digital-Based Scales Equipped with Metal Detectors as Met…
creator: Delima Astuti Rambe
creator: Dwi Anggita Ramanda
creator: Husna Juli Gulvira
creator: Muhammad Ilham Siregar
creator: Meiliyani Br Ginting
creator: Ita Margaretta Br Tarigan
rights: Copyright (c) 2026 JCEIT: Journal of Computer Engineering and Information Technology https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-31
publication date: 2026-03-31
volume: 2
number: 2
starting page: 160
ending page: 169

Naive Bayes Classification for Construction Workforce Requirement Prediction
type: item
description: The determination of construction worker requirements at the Langkat Regency Public Works and Spatial Planning Office (PUPR) is still conducted manually, often resulting in inaccurate workforce allocation and inefficiencies in project implementation. Therefore, a data-driven approach is needed to improve prediction accuracy. This study aims to apply the Naive Bayes algorithm to predict construction worker needs based on historical project data. This research uses a quantitative approach with a classification method. The dataset includes variables such as project type, budget, duration, and previous labor usage. Data processing involves preprocessing, training, and testing, with a data split of 80% for training and 20% for testing. The Naive Bayes model is then evaluated using accuracy, precision, recall, and F1-score metrics. The results show that the Naive Bayes algorithm achieves an accuracy of 86.7%, precision of 84.5%, recall of 87.2%, and F1-score of 85.8%. The model is capable of classifying workforce needs into low, medium, and high categories effectively. In conclusion, the Naive Bayes algorithm provides a reliable and efficient method for predicting construction worker requirements, supporting better decision-making and workforce planning at the Langkat Regency PUPR Office. REFERENCES Agustina, F. D., Arif, M., & Ahmad, S. (2025). Systematic Literature Review atas Kinerja Algoritma KNN, Naïve Bayes, dan Decision Tree pada Berbagai Studi Prediksi dan Klasifikasi. Jurnal Jawara Sistem Informasi, 3(1). Andika, A., Syarli, S., & Sari, C. R. (2022). Data Mining Klasifikasi Kelulusan Mahasiswa Menggunakan Metode Naïve Bayes. 4(1), 423–428. Anggreni, A., Hakim, A., Rahman, A., & Dinata, M. I. (2026). Klasifikasi Partisipasi Pemilih pada Pemilihan Walikota Bima Tahun 2024 Menggunakan Metode Naive Bayes Classifier. Jurnal Sains Natural, 4(1), 1–13. Azhar, S., Informatika, J. T., & Teknik, F. (2019). Decision Tree Dalam Memprediksi Kelulusan. (September), 1–8. Azizah…
creator: Nuzaima Agustari
creator: Roberto kaban
creator: Safarul Ilham
rights: Copyright (c) 2026 JCEIT: Journal of Computer Engineering and Information Technology https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-03-31
publication date: 2026-03-31
volume: 2
number: 2
starting page: 170
ending page: 179
doi: 10.64810/jceit.v2i2.47