The Implementation of Traffic Analytics Using Deep Learning and Big Data Technology with Garuda Smart City Framework

Supangkat, Suhono Harso; Hidayat, Fadhil; Dahlan, Iqbal Ahmad; Hamami, Faqih

doi:10.1109/gcce46687.2019.9015300

Cited by 9 publications

(4 citation statements)

References 13 publications

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“…Menurut Jason [1], smart berarti memiliki kemampuan untuk membuat penyesuaian dalam merespon keadaan yang berubah. Menurut Supangkat [2] , Smart System adalah sistem yang dapat memanfaatkan sumber dayanya untuk menyelesaikan setiap tantangan sistem dengan menyediakan layanan cerdas untuk meningkatkan Kualitas Layanan bagi penggunanya. Layanan cerdas adalah layanan yang menggunakan teknologi yang tersedia untuk menjalankan proses penginderaan, pemahaman, dan bertindak secara otomatis dengan intervensi minimum manusia.…”

Section: Pendahuluanunclassified

Pengukuran User Experience Platform Otomasi Proses berbasis Low Code Menggunakan UEQ

Falih,

Supangkat,

Lubis

et al. 2023

JSC

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This study analyzes the user experience of a Low Code-based Process Automation Platform to enhance efficiency, productivity, and accuracy in business processes. In this study, an analysis of user experience was carried out using a modified long version of the User Experience Questionnaire (UEQ), consisting of six scales: attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty. Based on the evaluation of the 26 items from the UEQ, the dependability and novelty scales scored the lowest compared to the other scales. Therefore, it is necessary to improve the aspects related to these two scales in order to enhance the platform's role in improving the holistic user experience of the platform.

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Section: Pendahuluanunclassified

Pengukuran User Experience Platform Otomasi Proses berbasis Low Code Menggunakan UEQ

Falih,

Supangkat,

Lubis

et al. 2023

JSC

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“…16 over a long period of time it will be accepted as part of the background [1]. The application of image processing and computer vision techniques for the analysis of stream video sequences is able to provide data such as volume, speed, coordinates and object classification, and may be relatively successful in these determinations in different applications and environments [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Approach for Moving Object Detection Using TV-L1 Features and RPCA–MOG

2023

IJIES

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Robust Principal Component Analysis (RPCA) has recently been active everywhere for dimension reduction in image processing, display and pattern recognition. Methods based on low-rank sparse representations, which make some specific significant assumptions, have recently received a lot of attention in background modelling. Meanwhile, a powerful analysis framework is needed to handle background areas or foreground motion at various scales. this paper presents a hybrid approach along with total variation L1 (TV-L1) features and reproductive RPCA model in low rank background subtraction modelling and sparse matrix with mixture of Gaussians (MoG) as foreground modelling. The hybrid structure with TV-L1 features imposes a hierarchical RPCA on the singular values of the low-rank component and MOG sparsity indicators. The proposed work was evaluated on the CDnet2014 (ChangeDetection.net) dataset, obtained result as accuracy was 92.9%, 86.7% 95.7% for Highway, Escalator, and Indoor respectively. The proposed method is compared with traditional methods and obtained relative reconstruction error is 0.01529 as a lower side.

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“…The advent of ‘big data’ has demonstrated the potential and pitfalls of methods used to help understand and manage diverse areas of human endeavour, including customer preferences (Watada et al, 2020), traffic optimisation (Supangkat et al, 2019), political debate (Fournier-Tombs and MacKenzie, 2021) and healthcare (Dash et al, 2019). ‘Big data’ still evades clear definition but is often understood in terms of ‘three Vs’ (Information Commissioner’s Office, 2017): volume – exponentially increasing stores of digital information; variety – the wide range of data types and scope to link multiple datasets; and velocity – the speed at which data is accumulating, to deliver real-time insights, capable of instantaneous update.…”

Section: Introductionmentioning

confidence: 99%

Natural language processing to identify case factors in child protection court proceedings

Coulthard

Taylor

2022

Methodological Innovations

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Social work case files hold rich detail about the lives and needs of vulnerable groups. Traditional case-reading studies to gain generalisable knowledge are resource-intensive, however, and sample sizes thereby limited. The advent of ‘big data’ technology, and vast repositories of centrally stored electronic records offer social work researchers novel alternatives, including data linkage and predictive risk modelling using administrative data. Free-text documents, however – including assessments, reports, and case chronologies – remain a largely untapped resource. This paper describes how 5000 social work court statements held by the Child and Family Court Advisory Support Service in England (Cafcass) were analysed using natural language processing (NLP) based on simple rules and mathematical principles. Thirteen factors relating to harm and risk to children involved in care proceedings in England were identified by automated computer techniques, and almost 90% agreement with professional readers achieved when the factors were clear-cut. The study represents an innovative approach for social work research on complex social problems. In conclusion, the paper discusses learning points; practical implications; future research avenues; and the technical and ethical challenges of NLP.

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The Implementation of Traffic Analytics Using Deep Learning and Big Data Technology with Garuda Smart City Framework

Cited by 9 publications

References 13 publications

Pengukuran User Experience Platform Otomasi Proses berbasis Low Code Menggunakan UEQ

Pengukuran User Experience Platform Otomasi Proses berbasis Low Code Menggunakan UEQ

A Hybrid Approach for Moving Object Detection Using TV-L1 Features and RPCA–MOG

Natural language processing to identify case factors in child protection court proceedings

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