Power systems are critical infrastructure that face significant challenges due to increasing demand and inherent complexity. Predicting failures in power systems is crucial for enhancing grid reliability, minimizing downtime, and optimizing maintenance processes. This study evaluates various deep learning models, specifically convolutional neural networks (CNN), recurrent neural networks (RNN), and transformer models, for predicting power system failures. By analyzing these models’ performance metrics on historical power grid data, the study provides insights into the strengths and weaknesses of each approach. The findings contribute to the development of more robust predictive models for power system reliability.

Accurate image segmentation is a pivotal process in medical imaging, essential for supporting diagnosis, treatment planning, and monitoring disease progression. This study evaluates the effectiveness of machine learning algorithms, including U-Net, Fully Convolutional Networks (FCNs), and Mask R-CNN, in achieving high-precision segmentation of medical images. Experimental results demonstrate that these models significantly enhance segmentation accuracy, enabling more precise diagnostic outcomes in clinical settings and advancing the development of automated medical imaging technologies.

Energy efficiency is a critical concern in wireless sensor networks (WSNs) due to the limited power resources available in sensor nodes. Prolonging network lifespan while ensuring reliable data transmission is essential for successful deployment in various applications, such as environmental monitoring, military operations, and industrial automation. This paper presents a mathematical model designed to optimize energy consumption across various nodes in WSNs. By implementing simulations and analyzing data from these models, the study demonstrates significant improvements in extending network lifespan while maintaining reliable data throughput. The findings contribute valuable insights into energy management for large-scale sensor deployments.

Nemo fish (Amphiprion sp.) is a type of marine ornamental fish that is popular because it is unique in terms of color, shape and movement. Feed is a factor in the growth and survival process of nemo fish. The aim of this research was to determine feed adaptation to the efficiency and feed conversion of nemo fish seeds. The research used an experimental method using a Completely Randomized Design consisting of 3 treatments and 3 replications. Treatment A (silk worms), treatment B (pellets) and treatment C (combination of 70% silk worms and 30% pellets). The best absolute weight growth results were in treatment C, namely 0.33 grams, while the lowest were in treatment B, namely 0.28. The survival rate (SR) during maintenance in each treatment was 100%. The best feed efficiency was in treatment C at 16.17% and the best feed conversion ratio was in treatment C with the lowest conversion ratio value of 4.81. Based on the results of the research conducted, it was concluded that feed adaptation for nemo fish seeds did not have a real influence on the efficiency and feed conversion of nemo fish seeds (Sig. > 0.05).
 
 

The research objective is to produce a gadget sales information system that can simplify the process of recording sales data to sales reports. According to observations and interviews that the author did at PT Kafilah Teknologi Indonesia in processing gadget sales data, all of which still use the manual method, namely recording in the books so that errors often occur. in calculating reporting and which often vary, this can hamper the process of financial reporting performance. The research method used in the Design of Gadget Sales Information Systems at PT. This Indonesian Technology Caravan is grounded research, which is a research method based on facts and using comparative analysis which aims to generalize epirisses, establish concepts, prove theories, and develop theories where data collection and data analysis run at the same time. In addition, the authors also conducted research with data collection methods by means of Observation, Interview and Documentation. After the author designed the Gadget Sales Information System, the author can help build a prototype so that the results are useful for the company so that it is expected to be more effective and accurate.

The purpose of this study is to assist tourists in providing information on tourist services for the waterfall at the foot of Mount Salak, so as to produce precise and accurate information reports. The development method used in this research is the SDLC (System Development Life Cycle) system. SDLC System Development Method This SDLC method is a method with a system development and design process through several stages, starting from system planning to operation and maintenance. Data collection methods used in this study are: observation, interviews, and literature study. This research produces an application that can assist tourists in providing more accurate information on waterfall tourism services at the foot of Mount Salak.

This paper explores energy harvesting techniques applicable to Internet of Things (IoT) devices, focusing on renewable energy sources such as solar, thermal, and kinetic energy. The study reviews current technologies and their efficiencies, presenting a comparative analysis of different energy harvesting methods. Experimental results demonstrate the feasibility of integrating these techniques into low-power IoT applications, potentially extending the operational life of devices without the need for frequent battery replacements. The research underscores the importance of sustainable energy solutions in the IoT landscape.

LP is one of the pharmaceutical companies located in Serang, Banten. The production of the company is tablets, capsules, and syrup. Problems that occur at PT. LP is a product defect that occurs in capsule filling, especially in capsule A. The purpose of this study is to determine the defective products that occur in capsule A and to find out the proposed improvements that will be made to reduce product defects in capsule A. The research methods used are Statistical Process Control (SPC)  and Fuzzy Failure Mode and Effect Analysis (F-FMEA). The population and samples used were defective capsule A during the production process from March 2022 to May 2023, with sampling techniques through production data, observation and interviews. And the results of research using a check sheet show that the percentage of defects reaches 6%, based on the pareto chart, the priority of improvement that needs to be done is for the dominant type of defect, namely  the dented capsule reject reaches 90%, and on the control chart there are still control points that are outside the UCL and LCL. FMEA calculations, the RPN value of the capsule is dented on the head of the capsule or capsule body reaches 384, and the FRPN value is 6.76.

 
 

Background: Stroke is damage to brain tissue caused by a sudden reduction or cessation of oxygen supply in the blood. Brain tissue that experiences a decrease in oxygen supply in the blood will die and no longer function. Stroke can cause weakness in muscles or body movement coordination. Elderly stroke sufferers feel low self-esteem due to disability and anxiety about death. One of the non-pharmacological techniques to overcome muscle weakness and overcome anxiety is rubber ball grip therapy and mindfulness therapy. The purpose of this case study is to determine the effect of Rubber Ball Grasp and Mindfulness Therapy on muscle strength and anxiety levels. The method used in this case study design is a nursing care process approach. The subjects in this case study were 2 patients, obtained from inclusion and exclusion criteria, data collection using Manual Muscle Testing (MMT) and the Hamilton Anxiety Rating Scale (HARS). The results of the case study show that the average muscle strength and anxiety level after being given the rubber ball grip therapy intervention for 6 days and mindfulness therapy for 3 days experienced changes from muscle strength without movement, muscle contractions could be felt/visible to normal full movement against gravity. and combat minimal resistance and severe to moderate levels of anxiety. In conclusion, there is an influence of rubber ball handheld therapy and mindfulness therapy on stroke elderly in the Paduwau Maumere Elderly Social Welfare Section.

This paper examines the considerations of Supreme Court (MA) judges in reducing sentences for defendants of corruption crimes in Indonesia. The problem in this paper is what are the considerations of Supreme Court judges in reducing sentences for defendants of corruption crimes juridically. This research uses a juridical method by analyzing relevant theories, concepts, and laws and regulations. The results show that the judge's consideration is based on the good character of the defendant, the social impact, and the facts of the trial, referring to Law Number 48 of 2009 and Law Number 8 of 1981. Edhy Prabowo's case shows that the sentence reduction does not reflect public justice, on the contrary, Idrus Marham's case shows weakness due to the sentence reduction received.