Article Per Year (5 Year)
p-Index From 2021 - 2026
3.627
P-Index
This Author published in this journals
All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal Pengabdian UntukMu NegeRI SISFOTENIKA INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi IT JOURNAL RESEARCH AND DEVELOPMENT Indonesian Journal of Artificial Intelligence and Data Mining MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JOISIE (Journal Of Information Systems And Informatics Engineering) Zonasi: Jurnal Sistem Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Applied Data Sciences Jurnal Computer Science and Information Technology (CoSciTech) Jurnal J-PEMAS Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) J-COSCIS : Journal of Computer Science Community Service JAIA - Journal of Artificial Intelligence and Applications SATIN - Sains dan Teknologi Informasi The Indonesian Journal of Computer Science INOVTEK Polbeng - Seri Informatika
Wirta Agustin
STMIK AMIK Riau
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences

Published : 33 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 33 Documents
Search

 1   2   3   4 
ANALISIS KESIAPAN SEKOLAH MENENGAH DALAM MENERAPKAN E-VOTING MENGGUNAKAN MODEL TECHNOLOGY READINESS INDEX Hazira, Nadila; Anam, M. Khairul; Agustin, Wirta; Fitri, Triyani Arita; Zamsuri, Ahmad; Syam, Salmaini Safitri
ZONAsi: Jurnal Sistem Informasi Vol. 6 No. 2 (2024): Publikasi Artikel ZONAsi: Periode Mei 2024
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v6i2.18400

Abstract

Voting can be interpreted as a way of making decisions based on the largest number of votes. So far, voting is carried out by ticking or voting on a ballot paper as an option in holding the election for OSIS chairman at SMAN 15 Pekanbaru. This method is considered still very conventional amidst advances in technology and information which has weaknesses in terms of efficiency and effectiveness. The weaknesses of conventional voting are: the decision is not the result of consensus, some participants are forced to accept the decision that has been taken, some participants often do not accept the decision, the aspirations of the participants are not fully channeled. To reduce problems arising from manual voting, it is necessary to analyze the readiness of secondary schools in implementing e-voting using the Technology Readiness Index model. The method that can be used to measure the level of user readiness in using technology is the Technology Readiness Index (TRI). In order to find out the results of the analysis and test the readiness of secondary schools in implementing the new system, the author will conduct a survey by distributing a Google Form link containing a list of statements regarding the readiness of secondary school residents, especially at SMAN 15 Pekanbaru, in using the web-based E-Voting system for the election of chairman. Student Council. The survey results will be analyzed using the SPSS 25.0 application and also calculated using the Technology Readiness Index Method
Retraksi: Penerapan Data Mining Menggunakan Algoritma Apriori untuk Menentukan Pola Penyebab Gelandangan dan Pengemis Agustin, Wirta; Muharmi, Yulya
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 2: April 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020721376

Abstract

Artikel dengan judul "Penerapan Data Mining Menggunakan Algoritma Apriori untuk Menentukan Pola Penyebab Gelandangan dan Pengemis" telah dilakukan retraksi dan pembatalan penerbitan dari Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK), Volume 7 No 2, April 2020 pada link http://jtiik.ub.ac.id/index.php/jtiik/article/view/1376.Alasan pembatalan penerbitan adalah artikel tersebut juga telah terbit di Indonesian Journal of Artificial Intelligence and Data Mining (IJAIDM) pada Volume 1 No. 2, September 2018 dengan judul "Apriori Algorithm through RapidMiner for Age Patterns of Homeless and Beggars" dan link http://ejournal.uin-suska.ac.id/index.php/IJAIDM/article/view/5670.Di lihat di proses review:Proses review pada artikel di IJAIDM:Artikel direvisi pada tanggal : 15 dan 20 Agustus 2018Artikel diterima untuk diterbitkan tanggal: 26 September 2018Proses review pada artikel JTIIK:Artikel dikirimkan: 7 Desember 2018Revisi dilakukan: 7 Januari 2019 dan 4 Maret 2019Dinyatakan diterima untuk diterbitkan: 5 Mei 2019Cek Turnitin terakhir: 4 Maret 2019 (belum terdeteksi jurnal yang sama di IJAIDM) Dilihat dari proses review pada kedua jurnal tersebut, penulis dianggap melakukan pelanggaran terhadap etika publikasi yang sudah ditandatangani penulis saat mengirimkan artikel tersebut di JTIIK.  
Framework for Analyzing Netizen Opinions on BPJS Using Sentiment Analysis and Social Network Analysis (SNA) Anam, M Khairul; Mahendra, Muhammad Ihza; Agustin, Wirta; Rahmaddeni, Rahmaddeni; Nurjayadi, Nurjayadi
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 6 No 1 (2022): February 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (514.221 KB) | DOI: 10.29407/intensif.v6i1.15870

Abstract

The Social Security Administrative Body is a legal entity established to administer social security programs. News about BPJS policies is often found online and social media that has received responses from netizens as a form of public opinion on the policy. One of them is the opinion of netizens on social media Twitter. Ideas can be positive, neutral, or negative. These opinions are processed using the Support Vector Machine (SVM) method, in some SVM studies still getting unsatisfactory results, with rates below 60%. For this reason, it is necessary to have feature selection or a combination with the other methods to obtain higher accuracy. To see the actors who influence the opinion of netizens on the topic of BPJS, the Social Network Analysis (SNA) method is used. Based on the SVM Method's test results, the best accuracy results are obtained in combining the SVM Method with Adaboost, with an accuracy rate of 92%. Compared to the pure SVM method by 91%, the Combination of SVM Particle Swarm Optimization (PSO) by 87% and SVM using Feature Selection Genetic Algorithm (GA) by 86%.
Co-Authors -, Dwi Haryono -, T. Sy. Eiva Fadtha -, Tashid Adlan, Radhi Agustin Agustin Ahmad Zamsuri, Ahmad Anam, M Khairul Arita Fitri, Triyani Azhari, Zahra Bakaruddin Bakaruddin bambang suyono Edwar Ali Efrizoni, Lusiana Firdaus, Muhammad Bambang Fransiskus Zoromi Fransiskus Zoromi Hazira, Nadila Helda Yenni, Helda Hendrawan, Riki Irwanda Syahputra Junadhi Junadhi Karpen Kurniawan, Fadly Lathifah, Lathifah Lusiana Lusiana Efrizoni Lusiana Lusiana Lusiana Lusiana Mahendra, Muhammad Ihza Muhammad Bambang Firdaus Muhammad Oase Ansharullah Muhammad Oase Ansharullah Munawir Munawir Nora Lizarti Nurjayadi Nurjayadi Nurul fadillah, Nurul Pandu Pratama Putra Pratama, Farhan Putra, Ryanda Satria Radhi Adlan Rahmaddeni Rahmaddeni Rahmiati Rahmiati Rini Yanti Rini Yanti, Rini Rizky Afrinanda Rometdo Muzawi, Rometdo Sari, Atalya Kurnia Septia, Rapindra Suhada, Khairus SUSI ERLINDA Susi Erlinda Syahrul Imardi Syam, Salmaini Safitri Tashid, Tashid Torkis Nasution Tri Putri Lestari, Tri Putri Triyani Arita Fitri Unang Rio Unang Rio, Unang Rio Yaakub, Saleh Yanti, Rini Yoyon Efendi Yulya Muharmi Zahra Azhari