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: Analysis of Accuracy and Computational Efficiency of Android-Based Palm Maturity Classification System Using K-Nearest Neighbor Method
items: Early Warning System for Student Academic Risk Prediction Using Gradient Boosting with SMOTE-Based Class Balancing
items: Modeling and Performance Analysis of a Series-Parallel AC Circuit under Supply Voltage Variations Using Simulation
items: Design of Augmented Reality-Based Learning Media Using the TPACK Framework for Visualizing Graph Concepts in Discrete Mathematics
items: Implementation and Optimization of a Voucher-Based Internet Access System Using MikroTik RB941 for RT/RW Net Networks
items: Performance Evaluation of HTB-Based Bandwidth Management for Campus Networks Using MikroTik Routerboard

Analysis of Accuracy and Computational Efficiency of Android-Based Palm Maturity Classification System Using K-Nearest Neighbor Method
type: item
description: Accurately determining the ripeness of oil palm Fresh Fruit Bunches (FFB) is crucial to maximizing the quality of Crude Palm Oil (CPO). Conventional methods rely on visual assessment or laboratory tests that are destructive, expensive, and inefficient at the field scale. This study proposes an android-based, non-destructive FFB ripeness classification system that uses color feature extraction and the K-Nearest Neighbors (K-NN) algorithm. A total of 65 FFB images directly from the tree are divided into training data (50 images) and test data (15 images) with three ripeness classes: raw, ripe, and overripe. Features are extracted through multilevel color thresholding segmentation, then calculated using RGB color averages, RGB normalization, and four Vegetation Indices (NDVI, SAVI, EVI, VARI). The test results show that the combination of Vegetation Indices with K-NN achieves the highest accuracy, 98% on the training data and 93.33% on the test data, with only one classification error. The system runs on-device with an average computation time of 3.3 seconds per image, demonstrating sufficient efficiency for real-time applications in plantations. This study concludes that the mobile approach based on K-NN and the Vegetation Index is worthy of adoption as a fast, accurate, and non-destructive harvest decision-support tool. However, further lighting optimization and dataset expansion are still needed for broader generalization. REFERENCES Alfatni, M. S. M., Mohamed Shariff, A. R., Ben Saaed, O. M., Albhbah, A. M., & Mustapha, A. (2020). Colour Feature Extraction Techniques for Real Time System of Oil Palm Fresh Fruit Bunch Maturity Grading. IOP Conference Series: Earth and Environmental Science, 540(1). https://doi.org/10.1088/1755-1315/540/1/012092 Bannari, A., Asalhi, H., & Teillet, P. M. (2002). Transformed difference vegetation index (TDVI) for vegetation cover mapping. IEEE International Geoscience and Remote Sensing Symposium, 5, 3053–3055 vol.5. https://doi.org/10…
creator: Ahmad Ridwan
rights: Copyright (c) 2026 Ahmad Ridwan https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-07-21
publication date: 2026-07-21
volume: 2
number: 3
starting page: 180
ending page: 190
doi: 10.64810/jceit.v2i3.63

Early Warning System for Student Academic Risk Prediction Using Gradient Boosting with SMOTE-Based Class Balancing
type: item
description: This study proposes a machine learning-based Early Warning Academic System for predicting student academic risk levels using historical academic performance data from ITB Indonesia. The aim of this research is to identify at-risk students at an early stage using routinely collected academic indicators, including Quiz Score, Attendance, Assignment Score, and Midterm Score. The proposed framework integrates Gradient Boosting as the classification model, Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance, and Stratified 5-Fold Cross Validation to ensure robust performance evaluation. The model classifies students into three categories, namely Safe, Warning, and Risk. Experimental results show that the proposed model achieves an accuracy of 80.00%, macro F1-score of 78.24%, Cohen’s Kappa of 0.6306, and Matthews Correlation Coefficient of 0.6311, indicating strong and reliable predictive performance under imbalanced data conditions. ROC-AUC analysis further confirms strong discriminative capability, particularly for identifying Risk students. Feature importance analysis reveals that Midterm Score is the most influential predictor (43.49%), followed by Quiz Score (25.60%) and Assignment Score (21.99%), while Attendance contributes 8.93%. These findings indicate that academic performance indicators, especially midterm assessments, play a critical role in early risk detection. The results demonstrate that effective early warning prediction can be achieved using a limited set of routinely available academic variables, providing a practical and scalable approach to support early intervention strategies in higher education institutions. REFERENCES Akello, E. F., Ijiga, O. M., & Idoko, I. P. (2026). Sequence-Aware Learning Analytics for Early Identification of At-Risk Academic Trajectories in Higher Education Using Transformer Models. International Journal of Innovative Science and Research Technology, 818. https://doi.org/10.38124/ijisrt/26jan563 Albr…
creator: Roberto Kaban
creator: Jamaludin Bin Sallim
creator: Susmanto Susmanto
creator: Rozlina Binti Mohamed
rights: Copyright (c) 2026 Roberto Kaban, Jamaludin Bin Sallim, Susmanto Susmanto, Rozlina Binti Mohamed https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-07-21
publication date: 2026-07-21
volume: 2
number: 3
starting page: 191
ending page: 207
doi: 10.64810/jceit.v2i3.64

Modeling and Performance Analysis of a Series-Parallel AC Circuit under Supply Voltage Variations Using Simulation
type: item
description: Series-parallel Alternating Current (AC) circuits are widely used in electrical power distribution and electronic systems because their operating characteristics are strongly influenced by supply voltage variations. Although simulation-based circuit analysis using Multisim has been widely applied in engineering education, studies systematically investigating the operating characteristics of series-parallel AC circuits over a broad range of supply voltages remain limited. This study aims to analyze the effect of gradual supply voltage variation on the operating characteristics of a series-parallel AC circuit using Multisim simulation. A quantitative experimental approach based on computer simulation was employed. The simulated circuit consisted of two resistors (220 Ω and 230 Ω) and two lamps connected as electrical loads. The supply voltage was gradually varied from 100 V to 320 V to observe changes in the operating conditions of the loads. The simulation showed that increasing the supply voltage progressively changed the lamp operating conditions, ranging from no illumination at 100 V, low brightness at 130 V, gradual increases in brightness at intermediate voltage levels, maximum brightness at 300 V, and lamp failure at 320 V due to excessive applied voltage. These observations are consistent with the theoretical relationships described by Ohm's Law, where increasing supply voltage results in greater electrical power delivered to resistive loads. The findings suggest that Multisim provides a practical environment for the preliminary evaluation of circuit behavior under different supply voltage conditions. However, the conclusions of this study are limited to simulation-based observations and require further validation through quantitative electrical measurements and hardware experiments. REFERENCES Anindya et al. (2025). Analisis Arus Dan Tegangan Pada Rangkaian Seri Dan Paralel Berdasarkan Hukum Ohm. Phydagogi : Jurnal Fisika Dan Pembelajarannya, 7(2), 1–8. Bhowm…
creator: Eka Feby Ronauli Lubis
creator: Nurhafiz Ahmad Rangkuti
creator: Nirwan Sinuhaji
creator: Indah Mawati Giawa
rights: Copyright (c) 2026 Eka Feby Ronauli Lubis, Nurhafiz Ahmad Rangkuti, Nirwan Sinuhaji, Indah Mawati Giawa https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-07-21
publication date: 2026-07-21
volume: 2
number: 3
starting page: 208
ending page: 217
doi: 10.64810/jceit.v2i3.65

Design of Augmented Reality-Based Learning Media Using the TPACK Framework for Visualizing Graph Concepts in Discrete Mathematics
type: item
description: The advancement of educational technology has created opportunities to develop innovative learning media that can enhance students’ understanding of complex and abstract concepts. In the Discrete Mathematics course, graph theory is considered one of the most challenging topics because it involves abstract relationships among vertices and edges, making concepts such as paths, cycles, trees, and spanning trees difficult for students to comprehend through conventional two-dimensional learning media. Therefore, this study aims to design an Augmented Reality (AR)-based learning media using the Technological Pedagogical Content Knowledge (TPACK) framework to support graph concept visualization in higher education. This study employed the Design and Development Research (DDR) method, consisting of problem identification, literature review, needs analysis, TPACK analysis, learning media design, system architecture design, user interface design, prototype development, and expert validation. The results produced a conceptual model of AR-based learning media that integrates technological, pedagogical, and content knowledge within a unified framework. The proposed design includes learning materials, AR-based three-dimensional graph visualization, practice exercises, evaluations, and user guidance features. The practical implication of this study is the provision of a systematic design framework that can serve as a reference for the development of AR-based educational applications in mathematics and computer science education. In conclusion, the integration of AR technology and the TPACK framework has the potential to facilitate the visualization of abstract graph concepts and support more interactive learning experiences. Further research is recommended to implement and evaluate the effectiveness of the proposed design in actual learning environments. REFERENCES Adipat, S. (2021). Developing Technological Pedagogical Content Knowledge (TPACK) through Technology-Enhanced Content…
creator: Ita Margaretta Br Tarigan
rights: Copyright (c) 2026 Ita Margaretta Br Tarigan https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-07-21
publication date: 2026-07-21
volume: 2
number: 3
starting page: 218
ending page: 230
doi: 10.64810/jceit.v2i3.62

Implementation and Optimization of a Voucher-Based Internet Access System Using MikroTik RB941 for RT/RW Net Networks
type: item
description: The increasing demand for stable, secure, and affordable internet access in RT/RW Net environments requires more effective network management strategies. Although MikroTik-based hotspot systems have been widely implemented, many existing studies primarily focus on basic hotspot deployment without integrating bandwidth optimization and voucher-based user authentication into a unified network management framework. Consequently, network administrators continue to encounter challenges related to unequal bandwidth allocation, inefficient user management, and limited access control. This study aims to implement and optimize a voucher-based internet access system using the MikroTik RB941 router to improve bandwidth management, user authentication, and network administration in RT/RW Net networks. The research employed an experimental approach involving network design, router configuration, hotspot implementation, voucher generation, bandwidth management using the Per Connection Queue (PCQ) method, and system testing. The implementation utilized MikroTik RouterOS, Winbox, and Mikhmon to configure and manage the network services. The proposed system successfully established centralized user authentication, automated voucher management, and more organized bandwidth allocation under the implemented testing scenario. The novelty of this study lies in the integration of Time-Based and Volume-Based voucher management with PCQ bandwidth allocation within a single MikroTik RB941 framework, providing a more comprehensive network management approach than conventional hotspot implementations. The findings indicate that the proposed configuration provides a structured and practical solution for managing internet access in RT/RW Net environments and establishes a foundation for future evaluations of network performance using Quality of Service (QoS) parameters. REFERENCES Anwar, I. D., & Akbar, Y. (2024). Network Bandwidth Management with Per Connection Queue (PCQ) Method on Mikrotik at…
creator: Adelia Amanda
creator: Alfridom Wau
creator: Dede Priyandi Bawamenewi
creator: Siti Rahmayani Sitorus
creator: Romulo P Aritonang
creator: Meiliyani Br Ginting
rights: Copyright (c) 2026 Adelia Amanda, Alfridom Wau, Dede Priyandi Bawamenewi, Siti Rahmayani Sitorus, Romulo P Aritonang, Meiliyani Br Ginting https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-07-22
publication date: 2026-07-22
volume: 2
number: 3
starting page: 231
ending page: 240
doi: 10.64810/jceit.v2i3.61

Performance Evaluation of HTB-Based Bandwidth Management for Campus Networks Using MikroTik Routerboard
type: item
description: The rapid growth of internet usage in campus environments, driven by academic, administrative, and digital learning activities, has led to significant increases in data traffic that can impact network performance and stability. At ITB Indonesia, the computer network relies on MikroTik RouterBoard as a core device for traffic management. However, during peak usage periods, network congestion may occur, necessitating a comprehensive performance analysis. This study aims to evaluate the performance of the MikroTik RouterBoard network in handling surges in data traffic within the ITB Indonesia campus. The research employs a quantitative experimental approach by simulating different traffic conditions, including normal and peak loads. Data were collected using monitoring tools integrated within the MikroTik system, focusing on key performance indicators such as throughput, latency, packet loss, and CPU utilization. The results indicate that the network performs efficiently under normal conditions, maintaining stable throughput and low latency. However, under high traffic loads, performance degradation is observed, including increased latency, higher CPU usage, and slight packet loss. The application of traffic management techniques, such as bandwidth allocation and load balancing, significantly enhances network performance. Therefore, MikroTik RouterBoard remains an effective solution when supported by proper optimization strategies. REFERENCES Adisetiawan, R. A. R. (2025). Transformation of Education in the Era of Digitalization Efforts Towards Technology-Based Education. Karapan Network Journal: Journal Computer Technology And Mobile Ad Hoc Network, 1(01). Aprelyani, S. (2025). Factors that affect network performance: signal quality and bandwidth. Greenation Journal of Engineering Sciences, 3(2), 85–92. Aritonang, M. A. S., & Simanullang, M. J. (2025). Application of a Network Monitoring System based on SNMP for early detection of network disturbances. Journal of Artif…
creator: Sumarlin
creator: Iscar Meriah Zai
creator: Candra Irawan Batee
creator: Naomi Rut M. Siboro
creator: Tuboy Martin Gea
creator: Hotma Mentalita
rights: Copyright (c) 2026 Sumarlin, Iscar Meriah Zai, Candra Irawan Batee, Naomi Rut M. Siboro, Tuboy Martin Gea, Hotma Mentalita https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-07-23
publication date: 2026-07-23
volume: 2
number: 3
starting page: 241
ending page: 252
doi: 10.64810/jceit.v2i3.60