Article Per Year (5 Year)
p-Index From 2019 - 2024
0.983
P-Index
This Author published in this journals
All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Simantec Jurnal Ilmiah Kursor Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) Network Engineering Research Operation [NERO] Journal of Information Systems and Informatics
Ika Oktavia Suzanti
University Of Trunojoyo Madura
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

Published : 8 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Jurnal Simantec

 1 
IMPLEMENTATION OF WEBSITE PERFORMANCE EVALUATION WITH SIMILARWEB ON ACADEMIC WEBSITES Ika Oktavia Suzanti; Fifin Ayu Mufarroha; Khusnul Fatimah; Doni Abdul Fatah; Hanifudin Sukri; Achmad Dafid
Jurnal Simantec Vol 10, No 2 (2022)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v10i2.14234

Abstract

Trunojoyo University Madura is a state university in Indonesia. The Trunojoyo Madura University website is used for information delivery media. The website can be accessed by anyone and used to make announcements for both students and outsiders. Based on this, the desired website quality must have high performance, usability, mobile friendliness, accessibility, SEO (Search Engine Optimization), connected to social media, and safe. This study was conducted to determine the level of usability through evaluating the performance of the academic website of Trunojoyo Madura University. Therefore, this study evaluates the performance of the website by using an automatic evaluation tool, namely SimilarWeb. This tool checks the level of popularity of a website both in terms of ranking and the number of visitors who access the website. In addition, measurements from the usability side were taken to determine the usability of the website obtained from the responses of students and visitors who have accessed the website. The results showed that by using SimilarWeb website traffic was obtained at a good level. Usability measurement has been carried out, as many as 58 respondents have answered 15 questions.
DETEKSI CYBERBULLYING PADA DATA TWEET MENGGUNAKAN METODE RANDOM FOREST DAN SELEKSI FITUR INFORMATION GAIN Rachmad Masbadi Hatullah Nurnaryo; Mulaab Mulaab; Ika Oktavia Suzanti; Doni Abdul Fatah; Andharini Dwi Cahyani; Fifin Ayu Mufarroha
Jurnal Simantec Vol 11, No 1 (2022): Jurnal Simantec Desember 2022
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v11i1.17256

Abstract

Indonesia merupakan salah satu negara dengan pengguna media sosial terbanyak. Dengan banyaknya pengguna media sosial, hal ini dapat memicu munculnya cyberbullying. Cyberbullying adalah tindakan berulang yang melecehkan, mempermalukan, mengancam, atau mengganggu orang lain melalui komputer, ponsel, dan perangkat elektronik lainnya, termasuk situs web jejaring sosial online. Twitter merupakan salah satu media sosial yang sering digunakan untuk melakukan cyberbullying. Deteksi cyberbullying merupakan langkah penting untuk membuat lingkungan yang baik dalam interaksi media sosial. Penelitian ini mendeteksi cyberbullying yang berasal dari tweet berbahasa Indonesia dengan menggunakan metode Random Forest sebagai pengklasifikasi. Seleksi fitur information gain juga digunakan untuk menyeleksi fitur yang berupa atribut. Penelitian ini bertujuan untuk mengetahui akurasi deteksi cyberbullying dari metode Random Forest dan memilih fitur penting untuk meningkatkan kinerja metode. Dari hasil pengujian, didapatkan nilai Accuracy tertinggi sebesar 72.1% dengan atribut berjumlah 1295 dari 2277 atribut. Hal ini berarti, pemilihan fitur yang baik dapat meningkatkan performa dari metode machine learning.Kata kunci: Cyberbullying, Information Gain, Random Forest, Tweet
Co-Authors Achmad Dafid Achmad Jauhari Andharini Dwi Cahyani Doni Abdul Fatah Fatah, Doni Abdul Fifin Ayu Mufarroha Hanifudin Sukri Ifandia, Alfian Mahendra Khozaimi, Ach. Khusnul Fatimah MHD. Reza M.I. Pulungan Mulaab Mulaab Rachmad Masbadi Hatullah Nurnaryo Yudha Dwi Putra Negara, Yudha