Article Per Year (5 Year)
p-Index From 2020 - 2025
7.605
P-Index
This Author published in this journals
All Journal Dinamik Sinkron : Jurnal dan Penelitian Teknik Informatika Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Tekinkom (Teknik Informasi dan Komputer) INFOKUM Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Media Informatika TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Jurnal Ilmiah Multidisiplin Indonesia INOVTEK Polbeng - Seri Informatika
Indra, Evta
Universitas Prima Indonesia
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Physics

Published : 49 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Jurnal Media Informatika

 1 
Tinjauan Sistematis: Teknik eye tracking untuk penyakit Skizofrenia Saragih, Septua Fujima; Ginting, Ricci Kincahar Bastoto Kevin; Simajuntak, Yusuf Natanael; Nasution, Adli Abdillah; Indra, Evta
Jurnal Media Informatika Vol. 5 No. 3 (2024): Jurnal Media Informatika Edisi Mei - Agustus
Publisher : Jurnal Media Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Eye tracking technology has emerged as an innovative tool for understanding and diagnosing schizophrenia, demonstrating significant potential in revealing different eye movement patterns between patients and healthy individuals. Literature studies indicate that irregular eye fixations and inconsistent saccades in schizophrenia patients may indicate disruptions in visual information processing and attention allocation. Eye tracking metrics, such as gaze duration and fixation stability, provide crucial insights into cognitive functions and emotional states in patients. Integration of eye tracking technology with machine learning techniques, including eXtreme Gradient Boosting (XGB) and Support Vector Machines (SVM), has achieved diagnostic accuracy up to 94%, highlighting its potential to enhance diagnostic precision. Despite these promising advances, challenges such as symptom variability among individuals, patient comfort, and the need for standard protocols remain. The development of non-intrusive eye tracking systems and applications in virtual reality (VR) shows potential for innovative therapies. Further research is needed to address these challenges and ensure effective and consistent implementation of this technology in clinical practice.
Perbandingan Metode Support Vector Machine (SVM) Dan Naive Bayes Pada Analisis Sentimen Ulasan Aplikasi OVO Lowell, Alvis; Lowell, Audric; Candra, Kevin; Indra, Evta
Jurnal Media Informatika Vol. 6 No. 2 (2025): Jurnal Media Informatika
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jumin.v6i2.5134

Abstract

In the rapidly evolving digital era, sentiment analysis has become crucial for understanding diverse user opinions. However, there is a gap in comparative studies on the effectiveness of machine learning methods for sentiment analysis of e-wallet applications in Indonesia. This research aims to compare the performance of Support Vector Machine (SVM) and Naive Bayes methods in sentiment analysis of user reviews for the OVO application, sourced from the Google Play Store. A total of 3,000 reviews were collected and processed through text preprocessing stages, including data cleaning, case folding, stopword removal, tokenizing, and stemming. Sentiment labeling was performed automatically using the VADER method, resulting in three categories: positive, neutral, and negative. The data was then transformed into numerical format using TF-IDF before being applied to the SVM and Naive Bayes models. Model performance was evaluated using a confusion matrix with metrics such as accuracy, precision, recall, and F1-score. The results showed that the SVM method delivered better outcomes with an accuracy of 89%, precision of 89%, recall of 89%, and F1-score of 88%, compared to the Naïve Bayes method, which achieved an accuracy of 86%, precision of 88%, recall of 86%, and F1-score of 87%. These findings can serve as a reference in selecting machine learning methods for sentiment analysis of e-wallet applications and assist OVO in improving service quality based on user feedback.
Co-Authors ., Calvin Abellista, Tivanez Ballerina Ahmad Rifai Akbari, Deni Adha Alfi, Ahmad Haikal Alifah, Lutfi Aulia Alvarez, Stevin Amalia Amalia Aminatunnisa, Siti Amir Saleh ANITA . Bangun, Dea Monica Bangun, Frans Aditya Banjarnahor, Jepri Barus, Daniel Haganta Brutu, Lolo Frans M. Butarbutar, Serly Yunarti Buulolo, Deniarwinus Candra, Kevin daniel christian Delima Sitanggang, Delima Dina Pratiwi, Dina Dwi Rizky, Atikah Edison, Rizki Edmi Fahmi, Mohammad Irfan Fando, Al Farrona, Rio Fidelis, Rio Giawa, Well Friend Ginting, Nessa Sanjaya Ginting, Ricci Kincahar Bastoto Kevin Gulo, Agustinus Gultom, Yeni Gurusinga, Alta Harahap, Charles Bronson Hutabarat, Fenna Kemala Hutabarat, Lerry Yos Santa Angelina Hutasoit, Leo Nardo Hutauruk, Jesika Avonia Juanta, Palma Juliandra, Vella Karim, Anggie Monica Keliat, Ribka Amelia Yunita Kumar, Sharen Loi, Mentari Hati Lowell, Alvis Lowell, Audric Lumbanraja, Lamtiur Rondang Wulan Maharja, Okta Jaya Manullang, Murni Esterlita Mariyanti, Eka Marpaung, Aldo Andy Yoseph Tama Matondang, Enjelika Mawaddah Harahap, Mawaddah MAYANTI, NUR Meizar, Abdul Muhammad Farhan Muhammad Yasir Muhardi Saputra Napitupuluh, Christian Deniro Nasution, Adli Abdillah Nasution, Syafrani Putri NK Nababan, Marlince Okta Jaya Harmaja Oloan Sihombing, Oloan Pakpahan, Ferdinand Linggo Panjaitan, Ezra Christina Septiana panjaitan, haris samuel pranada Piay, Clara Stephanie Bernadeth Pratama, Febryan Purba, Salda Sari Rahil, Rafif Rahmad, Julfikar Reinaldo, Erick Rifaldo, Rifaldo Ruben Ruben, Ruben Saragih, Septua Fujima Sembiring, Diarnia Mega Selfia Sembiring, Joni Satrio Sembiring, Yudha Brema Agriva Sianturi, Santo Sanro Siburian, Astri Dahlia Silaban, Herlan Simajuntak, Yusuf Natanael Simamora, Wanda Pratama Putra Simangunsong, Sarah Simanjuntak, Mega Herlin Simarmarta, Brando Benedictus Simbolon, Ongki Sopie Sinaga, Putri tua Sinurat, Stiven Hamonangan Siregar, Frissy Siregar, Reinhrad Shodani Siringo Ringo, Jaka Tomi Ronaldo Sitanggang, Audina L Sitompul, Chris Samuel Sitompul, Daniel Ryan Hamonangan Sitorus, Sarah Tri Yosepha Situkkir, Miando Mangara Situmorang, Andreas Solly Aryza Suhamdani, Dadan Suwanto, Jacky Suyanto, Jao Han Tampubolon, Irfan Saputra Tarigan, Nina Veronika Tarigan, Sri Wahyuni VERONICA VERONICA Vicraj, Vicraj Wijaya, Malvin Luckianto Wiranto, David Wiratama, Westlie Wirhan Fahrozi, Wirhan Yonata Laia Ziegel, Dennis Jusuf