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Journal : Jurnal Nasional Teknik Elektro dan Teknologi Informasi

Identifikasi Hubungan Sebab-Akibat pada Artikel Kesehatan menggunakan Anotasi Elemen Medis dan Paragraf Susetyo Bagas Bhaskoro; Saiful Akbar; Suhono Harso Supangkat
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 8 No 2: Mei 2019
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (936.485 KB)

Abstract

This paper studies natural language processing on medical articles in Indonesian that aims to identify causal relationship and used as public health surveillance information monitoring system. This paper proposes selection-feature conformity, phrase annotation, paragraph annotation, and medical element annotation. System performance evaluation is carried out using intrinsic aprroach which compares supervised classification methods, i.e. naive bayes method and HMM. Results obtained for recall, precission, and f-measure are 0.905, 0.924, 0.910 and 0.706, 0.750, 0.720, respectively.
Penerapan Computation Offloading Pada Sistem Deteksi Pelanggaran Perlintasan Sebidang Berbasis Komputasi Tepi Rian Putra Pratama; Suhono Harso Supangkat
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 13 No 1: Februari 2024
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v13i1.8795

Abstract

Level crossings remain a problem in several cities due to high violations. Currently, surveillance at level crossings is still performed conventionally. Since problems at level crossings are increasingly complex and conventional solutions are no longer effective, an intelligent video surveillance system is necessary. Intelligent video surveillance system implementation is a complex task and requires devices with extensive computing resources. This research aims to optimize the system for processing data in real-time by conducting computation near the data source and dividing computing tasks across several edge devices. This research proposes a solution in the form of an edge computing-based intelligent video surveillance system with a computation offloading method on limited devices. This research has two development stages. The initial stage involved developing an object detection model using a dataset of level crossings in Bandung City. The second stage was developing an edge computing-based system by applying the computation offloading method on limited computing devices. The edge computing method extends cloud computing to the network’s edge, enabling calculations near the data source. Conversely, the computation offloading method improves edge computing performance by dividing computing tasks. Results showed an increase in computing speed of around 1.5 times faster, with a violation detection accuracy rate reaching 89.4%. Additionally, GPU temperature decreased by 5.50 °C, GPU usage decreased by 44.05%, memory usage decreased by 301 Mb, and power consumption decreased by 2.28 W. The system developed is effective and efficient in optimizing the performance of the violation detection system in level crossings on limited computing devices.