Article Per Year (5 Year)
p-Index From 2020 - 2025
4.026
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electronics and Instrumentation Systems International Journal of Advances in Intelligent Informatics ELINVO (Electronics, Informatics, and Vocational Education) JOIV : International Journal on Informatics Visualization Journal of Applied Information, Communication and Technology (JAICT) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal ULTIMATICS JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Riset Rekayasa Elektro Tematik : Jurnal Teknologi Informasi Komunikasi Jurnal Teknik Informatika (JUTIF) Journal of Telecommunication, Electronics and Control Engineering (JTECE) Green Intelligent Systems and Applications JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Jurnal INFOTEL Jurnal Indonesia : Manajemen Informatika dan Komunikasi
I Ketut Agung Enriko
Institut Teknologi Telkom Purwokerto
Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

Published : 28 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Jurnal INFOTEL

 1 
Breast cancer recurrence prediction system using k-nearest neighbor, naïve-bayes, and support vector machine algorithm I Ketut Agung Enriko; Melinda Melinda; Agnesia Candra Sulyani; I Gusti Bagus Astawa
JURNAL INFOTEL Vol 13 No 4 (2021): November 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i4.692

Abstract

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 cancer, and with the advancements of technology, breast cancer can be detected earlier by using artificial intelligence or machine learning. There are popular machine learning algorithms that can be used to predict the existence or recurrence of breast disease, for example, k-Nearest Neighbor (kNN), Naïve Bayes, and Support Vector Machine (SVM). This study aims to check the prediction of breast cancer recurrence using those three algorithms using the dataset available at the University of California, Irvine (UCI). The result shows that the kNN algorithm gives the best result in terms of accuracy to predict breast cancer recurrence.
The effect of power spectral density on the electroencephalography of autistic children based on the welch periodogram method Melinda Melinda; I Ketut Agung Enriko; Muhammad Furqan; Muhammad Irhamsyah; Yunidar Yunidar; Nurlida Basir
JURNAL INFOTEL Vol 15 No 1 (2023): February 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i1.874

Abstract

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 diagnosing the disorder with electroencephalography (EEG). This study will analyze the effect of Power spectral density (PSD) on the EEG of autistic children and also compare it with the PSD value on the EEG of normal children using the Welch Periodogram method approach. In the preprocessing stage, the Independent Component Analysis (ICA) method will be applied to remove artifacts, and a Finite Impulse Response (FIR) filter to reduce noise in the EEG signal. The study results indicate differences in the PSD values ​​obtained in the autistic and normal EEG signals. The PSD value obtained in the autistic EEG signal is higher than the normal EEG signal in all frequency sub-bands. From the study results, the highest PSD value obtained by the autistic EEG signal is in the delta sub-band, which is 54.06 dB/Hz, while the normal EEG signal is only 33.14 dB/Hz at the same frequency sub-band. And in the Alpha and Beta sub-bands, the normal EEG signal increases the PSD value, while in the autistic EEG signal, the PSD value decreases in the Alpha and Beta sub-bands. In addition, FIR and ICA methods can also reduce noise and artifacts contained in autistic and normal EEG signals.
A Fire suppression monitoring system for smart building I Ketut Agung Enriko; Angela Niarapika Nababan; Adian Fatchur Rochim; Sri Kuntadi
JURNAL INFOTEL Vol 15 No 2 (2023): May 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i2.940

Abstract

A fire suppression system (FSS) monitoring system is a system to monitor the FSS devices’ status since FSS is a critical system to respond to fire disasters. The monitoring system collects data on important parameters which are water pressure, main power status, and backup power status. The FSS monitoring system is built with an IoT capability where data are collected from the FSS module and sent to the IoT platform through Wi-Fi based Internet connection. Then the data will be displayed in a dashboard application. A QoS assessment framework is referred to and performed to check the performance of the FSS monitoring system, namely the TIPHON framework, which consists of five parameters: bandwidth, throughput, packet loss, delay, and jitter. The overall score for the FSS system using the TIPHON standard is 3.2 or categorized as “good”.
Co-Authors Adi Wibowo Adian Fatchur Rochim Afandi, Mas Aly Agnesia Candra Sulyani Aisyatul Karima Alamsyah, Ahmad Tossin Amin Suharjono Angela Niarapika Nababan Anindya Wirasatriya Chandrayana Giri, Gede Chin, Wei Hong Danny Kurnianto Dewi, Mela Kartika Erika Lety Istikhomah Puspita Sari Erika Lety Istikhomah Puspita Sari* Estananto Fikri Nizar Gustiyana Fikri Nizar Gustiyana Fikri Nizar Gustiyana Fikri Nizar Gustiyana Filbert H. Juwono Gede Candrayana Giri Gilang Hijrian Fahreja Giri, Gede Chandrayana Gustiyana, Fikri Nizar Hedi Krishna Hedi Krishna Hedi Krishna Herryawan Pujiharsono I Gusti Bagus Astawa I Gusti Bagus Astawa Indriyanto, Slamet Kubota, Naoyuki Kurnianingsih Kurnianingsih, Kurnianingsih Kuswanda, Kuswanda Lutfan Lazuardi Maulisa, Oktiana Melinda Melinda Melinda Melinda Muhammad Aulia Baihaqy Muhammad Furqan Muhammad Irhamsyah Muhammad Irwan Yanwari Nabila, Nissa Hasna Nizar Gustiyana, Fikri Nuha, Muhammad Azza Ulin Nurlida Basir Puspita Sari, Erika Lety Istikhomah Rahmat Hardian Putra Rakasiwi, Rizky Khaerul Maulana Ramadhani, Eka Hero Ryan Anugrah Putra Sari, Erika Lety Istikhomah Puspita Silvi Nurandi Sri Kuntadi Sri Kuntadi Yunidar Yunidar Yunidar