Výsledky vyhledávání - "Ketut Agung Enriko"

Akademický článek

Deep learning performance analysis for facial expression based autism spectrum disorder identification

Autor: Melinda Melinda, Nur Afni Catur Andriyani, Yudha Nurdin, Veni Khariyunnisa, Yulita Yulita, I Ketut Agung Enriko

Publikováno v: Радіоелектронні і комп'ютерні системи, Vol 2024, Iss 2, Pp 30-40 (2024)

The subject matter of this paper revolves around the utilization of Deep Learning techniques for the identification of Autism Spectrum Disorder (ASD) through facial expression analysis. The goal is to assess the performance of various Deep Learning a

Externí odkaz: https://doaj.org/article/4f4c38127c2647f2950fb5abf7ce66ea

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Akademický článek

Experimental Visualization of the LoRaWAN Variable Correlation in Jakarta

Autor: Andrianingsih Andrianingsih, Eri Prasetyo Wibowo, Setia Wirawan, I. Ketut Agung Enriko, Robby Kurniawan Harahap

Publikováno v: IEEE Access, Vol 12, Pp 22978-22990 (2024)

This work presents empirical research into the efficacy of LoRaWAN, a wireless communication protocol that enables data transmission over extensive distances while minimizing power consumption and cost. This research aims to understand the correlatio

Externí odkaz: https://doaj.org/article/938a9866afcf4380b9d7fd67de826d41

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Akademický článek

Big data analytics for relative humidity time series forecasting based on the LSTM network and ELM

Autor: Kurnianingsih Kurnianingsih, Anindya Wirasatriya, Lutfan Lazuardi, Adi Wibowo, I Ketut Agung Enriko, Wei Hong Chin, Naoyuki Kubota

Publikováno v: IJAIN (International Journal of Advances in Intelligent Informatics), Vol 9, Iss 3, Pp 537-550 (2023)

Accurate and reliable relative humidity forecasting is important when evaluating the impacts of climate change on humans and ecosystems. However, the complex interactions among geophysical parameters are challenging and may result in inaccurate weath

Externí odkaz: https://doaj.org/article/a4bf0df939844839887ffd48b5ea948f

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Akademický článek

Application of continuous wavelet transform and support vector machine for autism spectrum disorder electroencephalography signal classification

Autor: Melinda Melinda, Filbert H. Juwono, I Ketut Agung Enriko, Maulisa Oktiana, Siti Mulyani, Khairun Saddami

Publikováno v: Радіоелектронні і комп'ютерні системи, Vol 0, Iss 3, Pp 73-90 (2023)

The article’s subject matter is to classify Electroencephalography (EEG) signals in Autism Spectrum Disorder (ASD) sufferers. The goal is to develop a classification model using Machine Learning (ML) algorithms that are often implemented in Brain-C

Externí odkaz: https://doaj.org/article/0ce674c9084b41e09827020e71d0f8bd

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The effect of power spectral density on the electroencephalography of autistic children based on the welch periodogram method

Autor: Nurlida Basir, Yunidar Yunidar, Muhammad Irhamsyah, Muhammad Furqan, I Ketut Agung Enriko, Melinda Melinda

Publikováno v: JURNAL INFOTEL. 15:111-120

Autism spectrum disorder (ASD) is a serious mental disorder affecting social behavior. Some children also face intellectual delay. In people with ASD, the signals detected have abnormalities compared to normal people. This can be a reference in diagn

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::25b47142cc73edaabbedc148877937e8
https://doi.org/10.20895/infotel.v15i1.874

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Improvement of Student Attendance System for Recording Student Surface Body Temperature Based on Internet of Things

Autor: Mas Aly Afandi, I Ketut Agung Enriko, Muhammad Aulia Baihaqy

Publikováno v: Elinvo (Electronics, Informatics, and Vocational Education). 7:92-100

Student attendance is a system used for tracking student activity in school. Many methods are used to develop student attendance systems, such as Quick Response (QR) Code systems, Radio Frequency Identification (RFID) systems, fingerprint systems, an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6e5afbb20996fea991645825ddf20297
https://doi.org/10.21831/elinvo.v7i2.53944

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Breast cancer recurrence prediction system using k-nearest neighbor, naïve-bayes, and support vector machine algorithm

Autor: I Gusti Bagus Astawa, Agnesia Candra Sulyani, Melinda Melinda, I Ketut Agung Enriko

Publikováno v: JURNAL INFOTEL. 13:185-188

Breast cancer is a serious disease and one of the most fatal diseases in the world. Statistics show that breast cancer is the second common cancer worldwide with around two million new cases per year. Some research has been done related to breast can

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::af8c23c38b5266a07c7de1b8813c2ac2
https://doi.org/10.20895/infotel.v13i4.692

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Akademický článek

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