Engineering Headway Vol. 3

Abstract: This study aims to assess the diversity of butterflies (Lepidoptera: Rhopalocera) at the location of the PT Pertamina Geothermal Energy (PGE) Lumut Balai Geothermal powerplant, Muara Enim, South Sumatra. This rapid survey was carried out on 4-15 June 2023, taking place in 7 locations namely Cluster 5, Cluster 6, Cluster 7, Cluster 9, Cluster 10, APL 17 and APL 18. The method used is the direct observation method by walking along a 1000 meter transect line (Yustian et al., 2017) in each type of habitat (secondary forest, mixed shrub secondary forest, coffee plantation , open areas and secondary forests near to rivers/water sources). The results obtained in this rapid survey are that there are 5 butterfly families consisting of Papilionidae, Pieridae, Nymphalidae, Hesperiidae and Lycaenidae with a total of 51 species and 254 individuals. The highest diversity index based on Shannon's diversity index and Margaleff's species richness index is in APL 17 with a secondary forest habitat type near to coffee plantations (H'=3.14, R=7.08) and the lowest is in Cluster 9 (H'=2.11, R=3.23) which is a secondary forest near to a geothermal power plant. Meanwhile, the highest evenness index was found in APL 17 (E=0.97) and the lowest in Cluster 7 (E=0.87) with a riparian habitat type. During the research, protected species were recorded, namely Troides amphrysus and Troides helena.

Abstract: Endophytic fungi are microbes that live in plant tissues and can synthesize the same active biochemical compounds as their hosts. This study aims to determine the type of endophytic fungi of Jeruju leaves (Acanthus ilicifolius) isolate DJS1. This research was conducted in January 2020 and is a type of descriptive qualitative research. The subjects in this study were one type of endophytic fungi isolate that has the potential as an antibacterial. Identification of endophytic fungi of Jeruju leaves (Acanthus ilicifolius) isolated DJS1 which have antibacterial potential by observing macroscopic and microscopic morphological phenotypic characters. Macroscopic observations described the form of colony structure, aerial hyphae forms, and radial lines that appeared on the fungal isolates. Microscopic observations were made to observe the shape of the hyphae and the shape of the conidia. While molecular observations were carried out by amplifying DNA using ITS primers.

Abstract: The red color of red rice pericarp and aleurone is regulated by proanthocyanidin protein. Proanthocyanidin protein was encoded by partial sequence of Rc gene. The mutation from DNA sequence would give divers phenotype in pericarp and aleurone. This study used four sample of local red rice (Keli Rejo, Sumber Jaya, Cahya Tani, Sirah Pulau Padang) from South Sumatra as genetic sources and specific primers (RC12) were used to encode Proanthocyanidin protein on local red rice. This research was conducted at the Genetic and Biotechnology Laboratory of Biology Department, Faculty of Mathematics and Natural Sciences, Sriwijaya University. The primary objectives of this study were to identify the correlations between the mutations from DNA sequences which encoded proanthocyanidin protein in local red rice from South Sumatra and the fenotip of pericarp and aleurone. The stapes was DNA isolation, amplification, electrophoresis, sequencing process using First Base Malaysia and sequences analysis using Clustal W to align the DNA sequence. Sequencing result showed all of the samples had high variability (less conserved region) where the alignment process showed deletion mutation and DNA substitution mutation along the sequences of the samples. The highest mutation occurred at local red rice from Cahya Tani and the lowest mutations take place at local red rice from Keli Rejo. The samples have the same phenotype of pericarp, meanwhile different at aleurone color. The sample from Sumber Jaya had the reddest aleurone color than other sample and this sample also showed the highest deletion mutation.

Abstract: Develop an obstacle detection system for Unmanned Aerial Vehicle (UAV) especially for small UAV is challenging. A robust system should be able to not only detect obstacles but the free region for the avoidance path as well. Besides, the configuration of the obstacles in the operating environment should never be disregard. In this paper, expansion cues from the detected feature points with the help of convex hull will be used to categorize the regions in the image frame. A micro LIDAR sensor is used as the initial detector of obstacle and queue for image capturing by the camera. Next, ORB algorithm is applied to find the obstacle regions and free space regions. This is done through the principal of object size changes and distance relationship in an image perspective. The proposed system was evaluated through series of experiments in a real environment which consist of different configuration of obstacles. The experiments show the proposed system was able to find the safe avoidance region regardless of the configuration of the obstacles in the operating environment. Keywords: Expansion cue; ORB; Feature points; Safe avoidance region

Abstract: The extraordinary swimming capacity of fish in nature makes them unique among Allah's creations. It is extremely difficult for a robotic system to achieve fish-like swimming behaviors, especially in terms of swimming performance. Many fish use their pectoral fins to provide thrust over a wide speed range and to carry out tricky maneuvers. In this paper, we report a robotic fish that can travel forward and backward using its propulsion system. In this report, the creation of a conceptual design for an interactive fish robot took into account a number of factors, including swimming ability, leakage testing, and motion controller. This needed considerable mechanical design work, and the result is a quick-return mechanism for the fish's body. We made the decision to divide the body into the head, body, and tail. In order to create the propulsion system, we employed five servo motors. Finally, controlling the robot's motion is absolutely essential, especially if there is an obstruction in its path. The servo controller, which is located at the fish's head, serves as the primary controller for all of the motors and sensors.

Abstract: The application of artificial intelligence (AI) in the manufacturing and service industries has witnessed rapid advancements in recent years. One prominent aspect is the utilization of Natural Language Processing (NLP) to facilitate human-machine interactions and enhance efficiency and user experience. This journal explores the implementation of NLP in the context of the manufacturing and service industry, focusing on the skateboard monitoring device. We demonstrate how NLP can improve analysis, prediction, and personalization in skateboard production, providing users with a more interactive and informative experience.

Abstract: Machine Learning can be used to process a lot of data and learn patterns from that data to predict the future. One of the most widely used parts of machine learning is Deep Learning. The Deep Learning method that currently provides the most significant results in image recognition is Convolutional Neural Network (CNN). Convolutional Neural Network (CNN) is one of the deep learning algorithms used for computer vision use cases such as image or video classification and detecting objects within images or even image areas. Some research related to the CNN model states that this model has a very good accuracy of 92% but with a fairly small amount of data and the use of epochs, namely 100, resulting in a higher validation error value than the error value in the training process, so that over fitting will occur. Based on several problems in the related research literature, this article aims to identify the weaknesses and shortcomings of Deep Learning algorithms using CNN models that refer to the state of the art, so that they can be used as a reference for further research. The state of the art related to research in the last five years, the Deep Learning algorithm using the CNN model found that (1) The number of epochs can affect the accuracy of the CNN model, (2) 2. The application of architecture can affect the accuracy of the CNN model, (3) the application of the type of layer can affect the accuracy of the CNN model. Based on several problems in the research literature related to the identification of weaknesses and shortcomings of Deep Learning using the CNN model which refers to Table 1. State of the Art summary of literature review research for the last five years, it can be concluded that to increase the accuracy of the CNN model, it is necessary to increase the number of epochs, apply the right architecture according to the problems in the research conducted, and use the type of layer. The hypothesis of this article can be used as a reference for further research related to Deep Learning using the CNN model.

Abstract: Analysis of the application of Risk Based Inspection method in the primary and secondary cooling pipe of TRIGA 2000 Bandung Reactor was conducted with the aim of obtaining a risk level value. To obtain the risk level value is carried out secondary cooling pipe thickness measurement using Ultrasonic Testing first. Furthermore, to obtain the risk level value, data such as pipe specifications, flowing fluid specifications, management system factors, measured pipe thickness data and previous inspection results, and pipe maintenance history will be used to calculate probability of failure (PoF) and Consequence of Failure (CoF) values. Probability of Failure and Consequence of Failure values are then plotted into a risk matrix to find out the level of risk that the component has. Risk level results can then be used to determine inspection methods and inspection intervals. The result of the risk level obtained from the calculation of the primary cooling pipe triga reactor 2000 is MEDIUM, lower than the risk level in the primary cooling pipe Kartini Reactor is MEDIUM HIGH. For the risk level of secondary cooling pipe Triga Reactor 2000 is MEDIUM is the same as the risk level of secondary cooling pipe Kartini Reactor. The recommended inspection methods for both reactors are the same using ultrasonic thickness measurement and visual examination inspection methods. Next inspection intervals for primary cooling pipes were 2068, 2092, 2104, 2110 and 2113 and for Kartini Reactor primary cooling pipes every 20 months. For Secondary cooling pipe Triga Reactor 2000 next inspection interval is 2067, 2090, 2101, 2106 and 2108 and for Kartini Reactor secondary cooling pipe every 10.11 years.

Abstract: The current study presents a comprehensive investigation of occupational hazards at a building construction site in Palembang, Indonesia. The primary aim of this research was to identify and understand the range of occupational safety and health (OSH) hazards present at the construction site, including physical, chemical, biological, ergonomic, and psychological hazards, in a bid to enhance the mitigation of these hazards. The primary data collection methods involved direct observations, photographic documentation, and short interviews with on-site personnel where a substantial array of insights was collected, including the presence of a workplace safety program, the recognition of main, potential workplace hazards, and other unsafe activities which workers performed within their job. Considering the scale of the project, with only 40 workers involved and the minimum utilization of heavy equipment, the focus of the physical and biological hazards findings was fixed around the presence of a diesel engine that was used as a part of an improvised crane to lift and lower objects, as well as the accumulated waste (mostly discarded food packaging) that was built-up at one corner of the construction site. Other hazards were also identified, including chemical hazards related to specific on-site activities, ergonomic hazards arising from workers’ movements, and the psychological hazard of extended overtime hours. A series of recommendations were then tailored to address these recognized hazards as the conclusion of the study. While the research is site-specific, the insights and recommendations were expected to provide value for the broader construction sector, particularly for those facing the unique challenges posed by evolving OSH practices and emerging safety culture.