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The advancement of Autonomous Underwater Vehicles (AUVs) is transforming the way scientists conduct deep-sea exploration and environmental monitoring. AUVs equipped with sophisticated sonar, AI-driven navigation systems, and real-time data transmission capabilities can explore extreme marine environments where human intervention is impossible. This paper reviews state-of-the-art developments in AUV technology, including enhanced battery efficiency, swarm intelligence for coordinated underwater missions, and AI-based anomaly detection for marine biodiversity assessment. Additionally, the study highlights the role of AUVs in disaster response, such as oil spill detection and ocean pollution analysis. By addressing technical challenges such as communication latency, data processing in harsh environments, and energy efficiency, this research aims to contribute to the next generation of AUV applications.

PT GMP Sukses Makmur Indonesia is a company engaged in the production of Bubble Wrap (bubbled plastic). This company produces 818,680 rolls with an average monthly production of 68,223 rolls. The problem that often arises at Pt Gmp Sukses Makmur Indonesia is the high production machine delay time with a downtime of 705.43 hours and a breakdown of 663.33 hours in one year, so the engine performance is less effective. This can lead to not achieving production targets which cause losses. The purpose of this study is to determine the effectiveness of the Bubble Wrap production machine using the Overall Resource Effectiveness (ORE) measuring tool and to find the causes of the problems that have been carried out using the ORE method on Bubble Wrap production machines during the period September 2021 – August 2022. ORE is a method that is useful in measuring the effectiveness of production time by taking into account the resources which include humans, machines, materials and methods. In the ORE method there are seven factors that are measured including readiness, availability of facility, changover efficiency, availability of material, availability of manpower, performance efficiency, dan quality rate. The results of measuring machine effectiveness using the Overall Resource Effectiveness (ORE) method for Ektruder machines were 76.41%, Crushers 99.59%, Cooling 98.99%, Mixers 99.79%, and Air Compressors 98.88%. Based on the method used, it is known that in the Bubble Wrap production process, the extruder machine does not meet the ORE standard of 85%, while the influencing factors are performance efficiency and quality rate. where the value of performance efficiency and Quality rate does not meet the standard so that it affects the high value of Overall Resource Effectiveness (ORE).

The development of digital technology in the field of education continues to advance, including in academic administration. This article discusses the socialization of a digital system for undergraduate exam registration based on a database in the Physics Education Study Program. The purpose of this socialization is to introduce and implement a system that simplifies the process for students to register for undergraduate exams online. This system is designed to replace the manual registration method, which is time-consuming and prone to errors. Through this socialization, it is expected that students and academic staff can understand the benefits and how to use this new system. The results of the socialization show that the majority of users are satisfied with the ease and speed offered by this system. This system not only improves operational efficiency but also supports transparency and accuracy in academic data. In conclusion, the implementation of this digital system is a positive step towards modernizing academic services in the Physics Education Study Program.

This research is mainly aimed at improving the way of discharging coal at PLTU Rembang, which is one of the power plant business units of a subsidiary of PT PLN located in Sluke District, Rembang Regency, Central Java Province. It maps the dimensions of the discharging speed using conveyor and grape . Data collected through surveys to coal shipping companies are regressed in the Linear Regression model. The results show that two characteristics of discharging services with conveyors and grapes affect time and cost (1) The duration of coal discharging (2) The cost of coal discharging. using qualitative and quantitative primary and secondary by direct observation to the field and data collection then the data is processed using multiple linear regression, the targeted outputs are national journals, national seminars, monographs.