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I Gede PUJA Astawa
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Journal of Communication Systems, Networks, and Security (JCSNS)
Published by Politeknik Elektronika Negeri Surabaya
ISSN : -     EISSN : 31635539     DOI : -
Core Subject :
JCSNS publishes original research articles, review papers, and applied studies covering, but not limited to, the following topics: 1. Telecommunications and Communication Systems Wireless and mobile communication systems Mobile Communications 5G, beyond-5G, and 6G technologies MIMO, OFDM, massive MIMO, and advanced modulation techniques Software-defined radio (SDR) and cognitive radio systems Satellite, aerial, and space communications Millimeter-wave and terahertz communications 2. Communication and Computer Networks Communication network architectures and protocols Software-defined networking (SDN) and network function virtualization (NFV) Intelligent and self-organizing networks Edge, fog, and cloud-assisted networking Internet of Things (IoT) and machine-to-machine (M2M) communications Network performance analysis, modeling, and optimization 3.Cybersecurity and Network Security Security in wireless and mobile networks Physical layer security Secure communication protocols and cryptographic techniques Intrusion detection and prevention systems Privacy, trust, and authentication mechanisms Security in IoT, cyber-physical systems, and smart infrastructures Intelligent and Adaptive Communication Systems Machine learning and artificial intelligence for communications and networking Cognitive and adaptive communication systems 4.Intelligent spectrum sensing, sharing, and management Autonomous network control and optimization Data-driven network security and anomaly detection 5.Applied and Experimental Studies Real-time implementation and testbed-based experiments Hardware-aware communication system design Performance evaluation using SDR platforms and experimental networks Case studies and deployment experiences
Arjuna Subject : -
Articles 8 Documents
 1 
Analysis of Load Balancing Performance in Raspberry Pi-Based Clustering Services within a Tourism System Bintang Desta Ramadhani; Norma Ningsih; Haryadi Amran Darwito
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

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Abstract

This study analyzes the performance of load balancing on a Raspberry Pi-based clustering service for a tourism e-ticketing system, focusing on the tourist destination in Trenggalek. E-ticketing systems often face challenges such as slow response times, system failures during traffic spikes, and difficulties in efficiently managing server resources. Therefore, this research aims to improve user experience, accelerate the ticket booking process, and optimize both the reliability and performance of the system. The methods used in this study include performance testing of two load balancing algorithms, Round Robin and Least Connection, implemented on a Raspberry Pi cluster server. Testing scenarios covered various load conditions: idle, normal, peak, and maximum, utilizing tools such as JMeter for load testing simulation, and Grafana and InfluxDB for real- time monitoring of system metrics. Key performance indicators analyzed were CPU usage, response time, throughput, memory usage, and error rate. The results indicate that the Round Robin algorithm is effective under light to moderate load conditions but begins to decline in performance under high loads, with response times exceeding 4000 ms and a significant increase in error rates. Conversely, the Least Connection algorithm proved to be more adaptive in distributing the load, maintaining better system stability, although errors still occurred when the system reached maximum capacity. Based on these findings, it is recommended that e-ticketing systems with dynamic and fluctuating loads prioritize the Least Connection algorithm. For future development, it is suggested to explore more advanced load balancing algorithms and increase server capacity to handle larger traffic loads.
Real-Time Fire Risk Assessment in Server Rooms Using Hybrid Threshold and Fuzzy Logic on Raspberry Pi Renel Cikita Robbyn; Anang Budikarso
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

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Abstract

The server room is a critical area for the storage and operation of server-related machines. In this environment, it is essential to protect data and systems from unwanted events. Significant increases in temperature or humidity can cause severe damage to equipment, system failures, and even fire risks due to sparks from transmission cables. Temperature and humidity readings with average values of 29.83°C and 45.5%, respectively, and low standard deviations, indicating reliable measurements. with an average delay of approximately 2.5 milliseconds. The system continuously monitors temperature, humidity, and flame presence to assess risk levels accurately. Threshold methods provide immediate alerts when sensor readings exceed predefined limits, while fuzzy logic enables nuanced risk classification based on combined sensor inputs. Experimental results demonstrate the system's effectiveness in early detection of hazardous conditions via visual and auditory alarms, thereby enhancing the protection of critical server infrastructure.
Performance Analysis of Full-Duplex DF Relay-Based D2D Communication with Energy Harvesting Afina Nabila Dirganingsih; Anang Budikarso; Yoedy Moegiharto; Mohammad Ridwan; Faridatun Nadziroh; Budi Aswoyo
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

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Abstract

Device-to-device (D2D) communication is a promising technology that leverages spectral efficiency and relieves network congestion in next-generation wireless systems. However, it suffers from significant performance degradation under Interference and limited transmission power and energy limitations, especially in the suburban areas with non-line-of-sight (NLOS) propagation conditions. To tackle these challenges, this paper studies a full-duplex D2D communication system with an energy-harvesting decode-and-forward (DF) relay based on the power-splitting relaying (PSR) protocol. The system model enables simultaneous information and energy transfer using radio-frequency (RF) signals as the energy source. We examine two scenarios: a relay-assisted self-interference model and a multi-node interference model. We evaluate system performance in terms of signal-to-noise ratio (SNR), throughput, and outage probability for different energy-harvesting efficiencies, power-splitting factors, and time-allocation parameters. Simulations show that system performance rises with energy-harvesting efficiency. We also identify optimal power-splitting and time-allocation values for maximum throughput. In the full-duplex DF relay system, self-interference is present at the relays, yet spectral efficiency improves. However, multiple nodes cancel each other out, causing a drop. These results help design effective, energy-efficient D2D communication systems with near-optimal performance for future wireless networks.
AI-Based Smart Cane for the Blind Using Raspberry Pi 3B Muchammad Yahya Ma’ruf; Faridatun Nadziroh; Paramitha Eka Wahyu Lestari
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

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Abstract

The eye is one of the human sensory organs that plays an important role in human life. The main function of the eye is to record the surrounding conditions, so that it can provide information in everyday life. People who have visual impairments are called blind. This limitation is one of the causes of disruption in the daily activities of blind people. Therefore, in their daily activities, blind people use assistive devices, such as canes. In this study, the author will create a system that can later be implemented in a cane with features to facilitate the activities of blind people. This cane has a camera that captures object images, which are later processed by the Raspberry Pi 3B+ using the Faster R-CNN algorithm. Faster R-CNN is a deep learning method used to detect objects in images. In addition, this cane is equipped with several supporting sensors, including an HC-SR04 ultrasonic distance sensor and a water level sensor for detecting water puddles. The output of all systems is sound, transmitted via wireless earphones and a buzzer as an information source/alarm for the visually impaired. The results of this research can assist the visually impaired by providing an assistive device for daily activities.
Performance Analysis of Static Vehicle-to-Vehicle Communication Systems Using Software Defined Radio Muhammad Sirojul Munir; Hendy Briantoro; Mohammad Yanuar Hariyawan
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

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Abstract

Vehicle-to-Vehicle (V2V) communication is a key component of Smart Transportation Systems (STS), enabling improved road safety, traffic efficiency, and cooperative driving. However, developing flexible, cost-effective, and experimentally validated V2V platforms remains challenging, particularly under varying propagation conditions such as Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS). This paper presents the design and experimental evaluation of a static V2V communication system using a Software-Defined Radio (SDR) platform. The system operates at 2.7 GHz and employs Binary Phase Shift Keying (BPSK) modulation, implemented using the GNU Radio framework. Performance is evaluated under LOS and NLOS conditions at varying distances using Packet Loss (PL), Bit Error Rate (BER), and Signal-to-Noise Ratio (SNR) as key metrics. The main contributions of this work are threefold: (1) the practical implementation of an SDR-based V2V communication system, (2) controlled experimental validation under both LOS and NLOS scenarios, and (3) a comprehensive performance analysis highlighting the impact of distance and environmental conditions. Experimental results show that the system achieves reliable performance under LOS conditions, with zero PL, negligible BER, and SNR up to 13.9 dB at short distances, remaining reliable up to 25 m. In contrast, performance degrades under NLOS conditions due to signal obstruction and multipath effects. These findings demonstrate the feasibility of SDR-based V2V systems and provide insights for improving their robustness in real-world environments.
IoT-Based Monitoring and Control of Smoke Concentration in Fish Smoking Warehouses Using Fuzzy Logic and ESP32 Urifah Nur Rohmah; Faridatun Nadziroh; Budi Aswoyo; Anang Budikarso; Ida Anisah
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

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Abstract

Fish smoking is a common practice for preserving and flavoring fish; unfortunately, traditional methods of smoking can produce dangerous air pollutants, including carbon monoxide (CO) and nitrogen oxides (NO₂), which have severe implications for workers' health and environmental performance. In this context, we propose an Internet of Things (IoT)- based intelligent system for real-time monitoring and control of smoke levels in fish smoking warehouses. The MICS-6814 gas sensor, combined with the ESP32 microcontroller, measures CO and NO₂ levels, while a fuzzy-logic algorithm classifies air quality using the CO₂-N₂ Air Pollution Standard Index (ISPU) from the reference. The proposed approach automatically controls ventilation via a fan actuator, which is triggered when pollutant levels exceed specific thresholds. The results of the experiment show that at a distance of 40 cm, as soon as it falls, this system is determined to be an unhealthy air condition if it starts automatic ventilation. Still, at a distance of 1 m, air quality remains moderate and therefore requires no action. The system enabled real-time monitoring, classification, and control, while data visualization was handled via a web-based interface and an LCD. Power, investigations repeatedly reported that indoor air quality management in fish smoking places demonstrated its practicality in reducing health risks from smoke exposure
GPS-Based Proximity Detection System Between Ship and Buoy for Marine Navigation Muhammad Edo Listiawan; Nihayatus Sa'adah; Nailul Muna; Karimatun Nisa'; Faridatun Nadziroh
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

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Abstract

Maritime navigation safety remains a major concern, especially for small vessels that lack advanced navigation aids such as radar or AIS. This study proposes a proximity detection system between a ship and a buoy using GPS data, LoRa communication, and ThingsBoard visualization. The ship node periodically transmits its coordinates through LoRa. In contrast, the buoy node receives the ship position, reads its own GPS coordinates, calculates the separation distance using the Haversine formula, and determines the system status as SAFE or ALERT based on a 50 m threshold. The processed telemetry is then forwarded to a gateway and visualized in real time on ThingsBoard. Experiments were conducted at distances of 10-100 m under two scenarios, with and without an obstacle. In the open-area condition, the system achieved an average percentage error of 3.42%, a mean absolute error (MAE) of 1.82 m, and a root mean square error (RMSE) of 2.47 m. Under obstacle conditions, the average percentage error increased to 24.07%, with MAE and RMSE values of 6.36 m and 6.93 m, respectively. Communication performance remained stable, with a 200-230 ms delay, RSSI values in the good category, and packet loss between 0% and 10%. These results show that the proposed system can provide an affordable early-warning solution for ship-buoy proximity monitoring.
Inorganic Trash Sorting Mobile Application using MobileNetV3 Method Reivan Haidar Ghiffari; Afifah_Dwi Ramadhani; Aries Pratiarso
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

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Abstract

This study aims to develop a mobile application for inorganic waste sorting capable of detecting seven object classes (plastic, glass, metal, electronics, paper, fabric, and cardboard) using the MobileNetV3 Deep Learning architecture. Based on comparative testing results, the MobileNetV3 method proved to be more effective than EfficientDet-d0, characterized by consistent loss reduction, better computational time efficiency, and optimal generalization capabilities without overfitting. Dataset quality was found to be a fundamental factor in model success, where the use of a standardized and noise-free dataset yielded superior performance with a detection accuracy reaching 97.14% and an Overall mAP of 94.13%. In-depth analysis showed that while detection performance was very stable for fabric and electronics categories, accuracy for plastic, glass, and metal categories tended to decrease when high Intersection over Union (IoU) precision was required. Operationally, the system achieved a 100% success rate within the distance range of 30 cm to 150 cm, with the best time efficiency observed between 60 cm and 90 cm. Furthermore, hardware testing concluded that high specifications only provided significant advantages in long-distance detection (>150 cm), whereas for the ideal operational range, devices with standard specifications proved to be highly sufficient and efficient for system implementation

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