Implementation of LoRa in A Luggage Tracking System Using GPS

Rafli Ramadhan Rohendi — 2026-07-29

Luggage is an item that is often carried when traveling and is often the target of theft, loss, or mix-ups. Therefore, a tracking system is needed that can monitor the location of luggage in real time. This study implements LoRa (Long Range) technology in a luggage tracking system, with the help of a Ublox NEO-6M GPS module and a NodeMCU ESP32 microcontroller. This system sends luggage location data from a LoRa transmitter to a LoRa receiver, which is then forwarded to an Android application via a Bluetooth connection. In addition, this study also analyzes network performance based on the parameters of delay, throughput, packet loss, and RSSI (Received Signal Strength Indicator). The test results show that the system is capable of sending data up to a maximum distance of 160 meters, with the best performance at a distance of 20–80 meters, marked by low delay, high throughput, and low packet loss. At a maximum distance of 160 meters, the delay value was 12.685 ms, the throughput was 4.37 bps, the packet loss was 60%, and the RSSI was –102.2 dBm. Based on a total of 90 test data points, the average test values showed a delay of 2777 ms, throughput of 10.87 bps, packet loss of 23.33%, and RSSI of -95.5375 dBm. This system can be used for luggage tracking without requiring an internet connection, allowing it to function in areas with limited network coverage.

Experimental Analysis of UDP Flood DDoS Attacks Using Network Forensic Methods

Mustamin Mustamin — 2026-07-29

In the ever-evolving digital era, computer networks have become the backbone of various information and communication systems. However, increased network usage has also led to increased security threats, such as Distributed Denial of Service (DDoS) attacks, ARP Spoofing, and other attacks. To address these threats, an approach capable of detecting, analyzing, and recovering networks from cyberattacks is needed. This study aims to analyze DDoS attacks using network forensics methods with an anomaly identification and attack reconstruction approach. This process includes collection, examination, analysis, and reporting stages using tools such as Wireshark and Winbox. Attack simulations were conducted using the LOIC application on a MikroTik router. The analysis results showed that the DDoS attack caused a CPU spike of up to 100%, which made the router unresponsive. Wireshark successfully identified the attack pattern in the form of UDP packet flooding, while Winbox showed a direct impact on device performance. The anomaly identification technique proved effective in detecting traffic spikes, and the reconstruction process helped understand the chronology and methods of the attack. This research contributes to the understanding and mitigation of cyber attacks through a network forensics approach, as well as being a guide in the implementation of security systems based on anomaly identification and attack reconstruction.

Media of Computer Science

Implementation of LoRa in A Luggage Tracking System Using GPS

Experimental Analysis of UDP Flood DDoS Attacks Using Network Forensic Methods