Garuda - Garba Rujukan Digital

Style Transfer Generator for Dataset Testing Classification Wedha, Bayu Yasa; Karjadi, Daniel Avian; Wedha, Alessandro Enriqco Putra Bayu; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11375

The development of the Generative Adversarial Network is currently very fast. First introduced by Ian Goodfellow in 2014, its development has accelerated since 2018. Currently, the need for datasets is sometimes still lacking, while public datasets are sometimes still lacking in number. This study tries to add an image dataset for supervised learning purposes. However, the dataset that will be studied is a unique dataset, not a dataset from the camera. But the image dataset by doing the augmented process by generating from the existing image. By adding a few changes to the augmentation process. So that the image datasets become diverse, not only datasets from camera photos but datasets that are carried out with an augmented process. Camera photos added with painting images will become still images with a newer style. There are many studies on Style transfer to produce images in drawing art, but it is possible to generate images for the needs of image datasets. The resulting force transfer image data set was used as the test data set for the Convolutional Neural Network classification. Classification can also be used to detect specific objects or images. The image dataset resulting from the style transfer is used for the classification of goods transporting vehicles or trucks. Detection trucks are very useful in the transportation system, where currently many trucks are modified to avoid road fees

Heavy-loaded Vehicles Detection Model Testing using Synthetic Dataset Karjadi, Daniel Avian; Wedha, Bayu Yasa; Santoso , Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11378

Currently, many roads in Indonesia are damaged. This is due to the presence of large vehicles and large loads that often pass. The more omissions are carried out, the more damaged and severe the road is. The central government and local governments often carry out road repairs, but this problem is often a problem. Damaged roads are indeed many factors, one of which is the road load. The road load is caused by the number of vehicles that carry more than the specified capacity. There are many methods used to monitor roads for road damage. The weighing post is a means used by the government in conducting surveillance. This research is not a proposal to monitor the road, but this is only to create a model for the purpose of detecting heavily or lightly loaded vehicles. This research is to classify using Convolutional Neural Network (CNN) with pre-trained Resnet50. The model generated from the Convolutional Neural Network training process reaches above 90%. Generate Image deep learning algorithms such as the Generative Adversarial Network currently generate a lot of synthetic images. The testing dataset that will be used is generated from style transfer. The model is tested using a testing dataset from the generated style transfer. Style transfer is a method of generating images by combining image content with image styles. The model is pretty good at around 92% for training and 88% for testing, can it detect image style transfer? The Convolutional Neural Network model is said to be good if it is able to recognize the image correctly, considering that the accuracy of the model is very good. One of the reasons why the training model is good but still makes errors during testing, then the image dataset is overfitting

Drowsy Detection in the Eye Area using the Convolutional Neural Network Wedha, Alessandro Benito Putra Bayu; Rahman, Ben; Hindarto, Djarot; Wedha, Bayu Yasa
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12386

Detection of a drowsy driver is an important aspect of driving safety. For this reason, it is necessary to have technology to carry out early detection before fatigue occurs. Mainly focused on driver fatigue that occurs at night. Analysis can be done quickly and accurately. These conditions can be sent via data so that they can be monitored and analyzed in real time. The results of the analysis can be sent by communication via the internet network. In addition, it functions as an early warning and can be used as logging or records that can be stored. This research does not discuss data communication but makes a prototype for detecting sleepy drivers. Prototype created using the Convolutional Neural Network Algorithm. The detection area is in the eye and testing is carried out with the brightness level of the light. In this study, building a prototype to detect signs of driver fatigue using the Convolutional Neural Network algorithm. The detection area used is in the eye, by testing at different light brightness levels. The dataset used in this study consists of a series of eye images, which are divided into two classes, namely open eyes, and closed eyes. After conducting the training process on Convolutional Neural Network, we get results of detection accuracy reaching 90%.

Proposed Enterprise Architecture on System Fleet Management: PT. Integrasia Utama Wedha, Alessandro Benito Putra Bayu; Rahman, Ben; Hindarto, Djarot; Wedha, Bayu Yasa
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12387

An information technology consulting firm that specializes in Global Positioning Systems provides fleet management services for many of its clients. The systems currently used by companies require more advanced modernization to ensure optimal service delivery. To overcome this challenge, a proposed enterprise architecture on system fleet management is presented in this paper. The proposed enterprise architecture is a comprehensive solution that includes the necessary hardware, software and operational processes to improve fleet management services. The proposed architecture is based on the Enterprise Architecture, which enables the integration of various systems and applications used by companies. The proposed architecture includes modules for vehicle tracking, fuel management, maintenance scheduling and driver performance monitoring. These modules work together to provide real-time data on fleet operations, enabling companies to make informed decisions regarding their fleet management services. The proposed architecture also incorporates an easy-to-use interface that simplifies the fleet management process and enhances customer satisfaction. The proposed system is scalable and easily adaptable to meet service requirements across multiple customers. In conclusion, the proposed enterprise architecture for system fleet management provides a comprehensive solution to the current challenges faced by companies as a corporate fleet service provider. The proposed architecture will improve service, reduce costs, and increase customer satisfaction.

Embarking on Comprehensive Exploration of Classification System of Fruits and Vegetables Wedha, Bayu Yasa; Vasandani, Michael Sagar; Wedha, Alessandro Enriqco Putra Bayu
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.13041

This research thoroughly investigates the fruit and vegetable classification system, emphasizing exhaustive investigation. This research aims to comprehend, analyze, and document numerous facets of this classification with MobileNetV2. This investigation included a comprehensive literature review, field investigation, and review of relevant scientific documents. In this investigation, we divide the classification of fruits and vegetables into various levels, ranging from the most general, such as kingdom and division, to the most specific, such as order and family. We also investigate the central role of taxonomy in comprehending the evolutionary and phylogenetic relationships between various categories of fruits and vegetables. This research enables us to identify and understand the taxonomic relationships between multiple varieties of fruits and vegetables and classify them into the appropriate botanical families. In addition, we investigate the global diversity of fruit and vegetable varieties, emphasizing the significance of conservation and genetic management to preserve the diversity of these precious commodities. In their efforts to comprehend, manage, and maintain the genetic variety of fruits and vegetables, this research provides researchers, botanists, and producers valuable insights. The findings of this study indicate that investigating fruit and vegetable classification systems is a crucial step in comprehending and conserving this irreplaceable natural resource, which provides direct benefits to humans in the context of global biodiversity conservation. MobileNetV2 research results accuracy epochs(5) = 94.84%, epochs(10) = 98.35%, epochs(15) = 98.69%.

Enterprise Architecture Design for the Transformation of Online Financial Services Wedha, Bayu Yasa; Vasandani, Michael Sagar; Wedha, Alessandro Enriqco Putra Bayu
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.13042

In the ever-expanding digital era, online financial services have emerged as a significant component of the global financial ecosystem. Digital transformation has altered the operations and consumer interactions of financial services companies. By implementing Enterprise Architecture design, financial services companies can adapt, flourish, and compete in an increasingly competitive environment. This article examines the essential function of Enterprise Architecture in the evolution of online financial services. We explore how Enterprise Architecture provides a strategic framework for driving change and innovation in financial organizations. We examine the primary elements of an Enterprise Architecture, such as the business model, technology infrastructure, and data. Then, we investigate how Enterprise Architecture improves operational efficiency and decreases risk in digital financial services. In addition, the significance of security and conformance in Enterprise Architecture for online financial services is examined. Enterprise Architecture is crucial in integrating security solutions and ensuring regulatory compliance in light of rising cybersecurity threats, strict regulatory compliance, and consumer demands for data privacy. We discuss how Enterprise Architecture facilitates improved consumer experiences in online financial services. By designing solutions with the consumer in mind, businesses can meet customer expectations, increase customer retention, and build a sustainable market share. Enterprise Architecture has become an indispensable instrument for successfully transforming online financial services. Through strategic planning, technology integration, data management, and a focus on security and customer experience, financial institutions can meet the challenges and seize the opportunities presented by the digital era.

Innovative Role of Blockchain Pharmaceutical Supply Chain Digital Transformation: Enterprise Architecture Perspective Wedha, Bayu Yasa; Vasandani, Michael Sagar; Wedha, Alessandro Enriqco Putra Bayu
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.13043

The advent of the Fourth Industrial Revolution has compelled numerous industries to undergo digital changes or transformations. One example is the pharmaceutical industry, which is responsible for providing medicinal products. The pharmaceutical supply chain assumes a crucial position within the pharmaceutical industry as it enables the secure, streamlined, and dependable transportation of medications from producers to individuals in need. The issue of prioritizing digital transformation within the pharmaceutical supply chain has emerged as a significant problem for hospitals and pharmaceutical businesses. Integrating different components inside the system is effectively supported by the substantial function fulfilled by Enterprise Architecture in this specific context. The objective is to minimize errors, enhance inventory management, optimize product distribution, and guarantee the safety and quality of pharmaceuticals. However, the process of adequately monitoring and verifying data has its challenges. However, these challenges can be efficiently addressed through implementing blockchain technology. In addition to this, Blockchain technology has the potential to enhance industrial efficiency. Utilizing blockchain technology enables the facilitation of transparency, immutability, and data integrity across the entirety of the supply chain. Integrating Enterprise Architecture electronic automation with Blockchain technology enables pharmaceutical enterprises to establish robust systems facilitated by Smart Contracts. The use of this system is expected to significantly enhance automation and regulatory adherence within supply chain processes, leading to notable advancements in operational efficiency, security, and data accuracy. Integrating blockchain technology and smart contracts enables pharmaceutical enterprises to enhance their product offers to hospitals and patients at reduced expenses, facilitating notable advancements in Enterprise Architecture.

Optimizing Transportation Services: Using TOGAF for Efficiency and Quality Wedha, Bayu Yasa; Hindarto, Djarot
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3407

In the rapidly expanding transportation industry, it is crucial to make focused and coordinated efforts to improve services with maximum efficiency. This paper seeks to explore the optimization of the Enterprise Architecture approach to effectively attain the primary objectives of the transportation industry, specifically the enhancement of service quality. The main emphasis is on implementing the enterprise architecture methodology of the open group architecture framework on a strategic basis. This paper examines how Enterprise Architecture can offer systematic and quantifiable solutions by identifying problems in infrastructure and operational processes. The research aims to provide comprehensive insights into how the Enterprise Architecture concept can optimize operational efficiency and streamline processes in the provision of transportation services. By implementing TOGAF, it is expected that the integration of systems will be seamless, technology usage will be optimized, and customer experiences will be improved. To summarize, this paper demonstrates the desire to improve transportation services. It explains how Enterprise Architecture methods, specifically within the TOGAF framework, can directly lead to advantages such as increased operational efficiency and improved service quality. This paper aims to be easily understood by a wide range of readers, including management, Information Technology professionals, and other stakeholders in the transportation industry. It avoids using overly technical language to ensure accessibility and comprehensibility.

Implementation Convolutional Neural Network for Visually Based Detection of Waste Types Wedha, Bayu Yasa; Sholihati, Ira Diana; Ningsih, Sari
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3427

Waste detection plays an essential role in ensuring efficient waste management. Convolutional Neural Networks are used in visual waste detection to improve waste management. This study uses a data set that covers various categories of waste, such as plastic, paper, metal, glass, trash, and cardboard. Convolutional Neural Networks are created and trained with refined architecture to achieve precise classification results. During the model development stage, the focus is on utilizing transfer learning techniques to implement Convolutional Neural Networks. Utilizing pre-trained models will speed up and improve the learning process by enriching the representation of waste features. By using the information embedded in the trained model, the Convolutional Neural Network can differentiate the specific attributes of various waste categories more accurately. Utilizing transfer learning allows models to adapt to real-world scenarios, thereby improving their ability to generalize and accurately identify waste that may exhibit significant variation in appearance. Combining these methodologies enhances the ability to identify waste in diverse environmental conditions, facilitates efficient waste management, and can be adapted to contemporary needs in environmental remediation. The model evaluation shows satisfactory performance, with a recognition accuracy of about 73%. Additionally, experiments are conducted under authentic circumstances to assess the reliability of the system under realistic circumstances. This study provides a valuable contribution to the advancement of waste detection systems that can be integrated into waste management with optimal efficiency.

Online Tutoring's Technological Foundation and Future Prospects: Enterprise Architecture Development Ningsih, Sari; Wedha, Bayu Yasa; Sholihati, Ira Diana
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3433

This study examines the advancement of enterprise architecture with the objective of enhancing the technological infrastructure and long-term strategies in the online student tutoring sector. Online tutoring has emerged as the primary option for supporting the learning process in the rapidly advancing digital age. Identify the essential elements involved in establishing robust groundwork for an online tutoring platform, with a focus on highlighting the strategic significance of enterprise architecture. Examining the technological infrastructure that is customized to fulfill the demands of the tutoring sector constitutes the research methodology utilized in this investigation. Enterprise architecture serves as the fundamental framework that enables smooth integration among different systems, applications, and services used in online tutoring. Creating an enterprise architecture will subsequently generate a well-defined technology roadmap, empowering tutoring companies to innovate with greater precision. This architecture enhances the role of online tutoring in providing a more adaptable and personalized learning experience for students by utilizing advanced technologies like artificial intelligence and data analytics. This study emphasizes the significance of enterprise architecture in facilitating educational transformation and establishing a robust framework for online tutoring companies to progress efficiently. To foster the growth and advancement of the online tutoring industry, it is crucial to strategically enhance the technological infrastructure and implement a well-designed enterprise architecture. This will enable the sector to play a substantial role in shaping a dynamic and forward-thinking educational landscape.

Title

Found 13 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 13 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 13 Documents
Search