Adopsi IoT Pada Core Process Trucking di Indonesia Dengan Menggunakan TOGAF Framework

Wedha, Bayu Yasa; Helmi, Hadri; Dazki, Erick; Indrajit, Richardus Eko

doi:10.35957/jatisi.v9i1.1980

Cited by 2 publications

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“…IoT Adoption in Core Process Trucking in Indonesia Using the TOGAF Framework (Wedha, Helmi, et al, 2022). Implementation of IoT technology in trucking companies requires enterprise architecture planning, so that the technology implemented is in accordance with business needs.…”

Section: Literature Reviewmentioning

confidence: 99%

Proposed Enterprise Architecture on System Fleet Management: PT. Integrasia Utama

Wedha

Rahman

Hindarto

et al. 2023

SinkrOn

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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.

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Section: Literature Reviewmentioning

confidence: 99%

Proposed Enterprise Architecture on System Fleet Management: PT. Integrasia Utama

Wedha

Rahman

Hindarto

et al. 2023

SinkrOn

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“…First, we propose various improvements to the YOLO detection method, both novel and drawn from prior work. The improved model, YOLOv2, is state-of-the-art on standard detection tasks like PASCAL VOC and COCO (Rostianingsih et al, 2020), (Tong & Wu, 2023), (Wedha, Helmi, et al, 2022). Using a novel, multi-scale training method the same YOLOv2 model can run at varying sizes, offering an easy tradeoff between speed and accuracy.…”

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confidence: 99%

Detects Damage Car Body using YOLO Deep Learning Algorithm

Gustian

Rahman

Hindarto

et al. 2023

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This journal presents a technique for detecting scratches, cracks and other damage to car bodies using machine learning methods. This method is used to improve process efficiency and checking accuracy and can also reduce the cost and time required for manual inspection. The method includes collecting image datasets of cars in good and damaged condition, followed by preprocessing and segmentation to separate damaged or damaged car parts. not broken. Then, it is followed by a deep learning algorithm, namely You Only Look Once, or Faster Region-based Convolutional Neural Networks, which is used to build a detection model. The model is trained and tuned using the collected data, then evaluated using the test data to measure the accuracy and precision of the detection results. The experimental results show that the proposed method achieves high accuracy and efficiency in detecting scratches, cracks, and other defects on the car body, with precision of an average of more than 70%. This method provides a promising approach to improving the car body inspection process which can be used by taxi companies to help inspect and maintain vehicles more quickly and accurately, to help with insurance, avoid accidents and so on.

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Adopsi IoT Pada Core Process Trucking di Indonesia Dengan Menggunakan TOGAF Framework

Cited by 2 publications

References 0 publications

Proposed Enterprise Architecture on System Fleet Management: PT. Integrasia Utama

Proposed Enterprise Architecture on System Fleet Management: PT. Integrasia Utama

Detects Damage Car Body using YOLO Deep Learning Algorithm

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