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This research aims to identify and analyze the essential instructional tools needed in gas turbine learning for cadets of the Naval Academy's engineering corps using a mixed-method approach with an explanatory sequential design involving 160 respondents, consisting of 120 engineering corps cadets, 15 instructors, and 25 field engineering officers. The research results identified 28 types of gas turbine instructional tools categorized into four groups, with simulators and software showing the highest level of importance (4.65/5.0), and there were significant differences in the perception of importance levels among the three groups of respondents (F(2,157) = 12.45, p < 0.001). The AHP analysis produced a priority framework in four levels, with Level 1 encompassing 5 essential instructional tools: gas turbine simulator (0.742), gas turbine cut-section model (0.698), control system trainer kit (0.681), interactive learning video (0.673), and troubleshooting simulator (0.667). Regression analysis showed that instructional tools significantly contribute to learning effectiveness (R² = 0.742), with the gas turbine simulator as the main predictor (β = 0.384), positively impacting the cognitive aspect with a 26.8% increase in concept understanding (effect size 1.24), the affective aspect with an increase in learning motivation and career interest from 67% to 84%, and the psychomotor aspect with a 33.7% increase in hands-on skills and a 28.5% reduction in troubleshooting time. The resulting priority framework provides strategic guidance for optimizing resources and gradually developing gas turbine learning capabilities in military educational institutions, despite facing major obstacles such as budget constraints, technology compatibility, lack of quality human resources, and limited laboratory infrastructure.

This research aims to analyze the benefits of learning shipbuilding theory for cadets of the Technical Corps at the Indonesian Naval Academy (AAL) using a mixed methods approach. The research results show that mastery of shipbuilding theory significantly enhances the technical competence of cadets, particularly in understanding ship structure, stability, hydrodynamics, and propulsion systems, and contributes to their operational readiness in the TNI AL environment. However, the main challenges identified include the complexity of the material, limited laboratory and simulator facilities, and the gap between classroom theory and real-world application on warships. The effectiveness of learning is greatly influenced by interactive teaching methods, instructor competence, and the support of learning facilities. This research recommends the development of an adaptive curriculum, increased investment in simulation technology, and collaboration with the maritime industry to enrich the cadets' learning experience. These findings are expected to serve as a basis for the evaluation and development of the shipbuilding theory curriculum at AAL, as well as a reference for other maritime educational institutions in designing more applicable and relevant learning programs that meet operational needs in the field.

IEEE 802.11ax WiFi 6 is the current standard for wireless local area network (WLAN) technology which is a development of the previous standard, namely IEEE 802.11ac (WiFi 5). WiFi 6 has new features that are superior to WiFi 5. For example, it can operate in the 6 GHz frequency band, use 1024-QAM modulation, and use a maximum of 8 spatial streams. In general, to test and verify the implementation of a network technology standard, researchers can buy hardware on the market that has implemented the standard in its entirety or only certain mandatory features. Apart from using hardware directly, testing can also be done using software simulations. This research aims to study the WiFi model in the ns-3 simulator and simulate the IEEE 802.11ax WiFi 6 network. The simulation is carried out to measure the uplink throughput that can be achieved by WiFi 6 with various numbers of client stations (STA) and various distances between the Access Point (AP) and STA. The simulation results show that the throughput value will decrease with increasing AP-STA distance and the number of STA. The maximum throughput value obtained in the simulation with 5 STA at a distance of 2 meters from the AP is 655.41 Mbps.

This research investigates the integration of maritime law education and navigation skill development within vocational school settings. By leveraging qualitative methods, the study engages maritime professionals and vocational educators to assess curriculum effectiveness and alignment with industry standards. Key findings highlight the importance of practical application in maritime law education, emphasizing case studies and scenario-based learning to prepare cadets for real-world challenges. Simulator training emerges as pivotal in developing navigation skills and critical decision-making abilities essential for safe maritime operations. The study also underscores the significance of regulatory compliance, advocating for continuous curriculum adaptation to meet evolving STCW and IMO regulations. Recommendations include enhancing collaboration between stakeholders, expanding experiential learning opportunities, and integrating regulatory awareness throughout educational frameworks. By fostering these initiatives, vocational schools can nurture competent maritime professionals equipped to navigate global maritime challenges while upholding safety, sustainability, and regulatory standards.

This research investigates the integration of sustainability principles and digital advancements in maritime law education within vocational training programmes. Drawing on qualitative perspectives from maritime professionals and educators, the study identifies critical areas for curriculum enhancement and skill development. Key findings highlight the industry's emphasis on regulatory compliance, safety management, and the use of digital technologies in maritime operations. The research underscores the importance of practical training modules, simulation-based learning, and industry partnerships in preparing cadets for real-world challenges. Expertise from industry stakeholders informs curriculum design, focusing on digital navigation tools, safety protocols, and regulatory frameworks like STCW and IMO standards. Assessment of cadet readiness reveals strengths in theoretical knowledge but emphasizes the need for more extensive practical training. Innovative approaches using simulators and online platforms enhance learning outcomes and operational efficiencies. The study concludes with recommendations for ongoing collaboration between academia and industry to sustain curriculum innovation and prepare a competent workforce for the evolving maritime industry.

This study aims to analyze the performance of the OSPF routing protocol in a tree topology using the Cisco Packet Tracer simulator with a router configuration, and a PC/computer. This research involves building a tree topology consisting of several router nodes and PC/computers, where OSPF is implemented to manage routing. Tests were conducted using steady ping on PC to PC, PC to router and PC to server to measure network performance in terms of latency and reliability. The test data was analyzed to evaluate OSPF convergence, network stability and rounting efficiency. The results of this study provide insight into the effectiveness of OSPF in a tree topology.

This journal reviews the use of Cisco simulators in building and analyzing ring topology networks and the routing protocols used in them. Ring topology is one of the commonly used network topologies where all nodes are directly connected to form a circle. The routing protocol in ring topology uses Bellman Ford and Dijkstra algorithms to determine the best path. The main focus of this research is on Enhanced Interior Gateway Routing Protocol (EIGRP), a routing protocol developed from Interior Gateway Routing Protocol (IGRP). EIGRP enables fast convergence and efficiency in data transmission in the network. The research methods used are literature and simulation methods using Cisco Packet Tracer software.    

Data communication is a field of science that studies the process of sending data, as well as how data can be received from sending and receiving terminals. A computer network is a set of "interconnections" between 2 or more autonomous computers connected by cable or wireless transmission media. Cisco packet tracer is a network simulation application developed by Cisco as a simulator as a learning medium for Cisco devices. Peer-to-Peer (P2P) network simulation using Cisco Packet Tracer software is an effective method for understanding, designing, and analyzing P2P networks in a controlled environment. The method used is literature study and carrying out simulation practice on Cisco Packet Tracer software to simulate a network. This research method aims to outline the steps and procedures required to simulate a Peer-to-Peer (P2P) network using Cisco Packet Tracer software. This abstract presents a brief view of the simulation approach used to model and examine the performance of a P2P network using Cisco Packet Tracer contains implementation steps for peer to peer network simulation. Through simulation, in-depth performance analysis can be carried out on various aspects of P2P networks, such as throughput, latency and reliability. This allows researchers and practitioners to understand how P2P networks behave under various conditions. Thus, P2P network simulation with Packet Tracer provides a useful tool for researchers and practitioners to understand and optimize P2P network performance in various scenarios.

Driving in a straight line is one of the fundamental tasks for autonomous vehicles, but it can become complex and challenging, especially when dealing with high-speed highways and dense traffic conditions. This research aims to explore the Deep-Q Networking (DQN) model, which is one of the reinforcement learning (RL) methods, in a highway environment. DQN was chosen due to its proficiency in handling complex data through integrated neural network approximations, making it capable of addressing high-complexity environments. DQN simulations were conducted across four scenarios, allowing the agent to operate at speeds ranging from 60 to nearly 100 km/h. The simulations featured a variable number of vehicles/obstacles, ranging from 20 to 80, and each simulation had a duration of 40 seconds within the Highway-Env simulator. Based on the test results, the DQN method exhibited excellent performance, achieving the highest reward value in the first scenario, 35.6117 out of a maximum of 40, and a success rate of 90.075%.