Article Per Year (5 Year)
p-Index From 2020 - 2025
1.116
P-Index
This Author published in this journals
All Journal JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi Jurnal Dinamika Informatika (JDI) Jurnal Sistem Informasi dan Ilmu Komputer JTH: Journal of Technology and Health
Nurirwan Saputra
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Health Professions Medicine & Pharmacology Nursing Other

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi

 1 
Analisis Sentimen Film Kuliah Kerja Nyata (Kkn) Di Desa Penari Menggunakan Metode Naive Bayes Salsa Bella Putri; Yonawati Nur Anisa; Nurirwan Saputra
JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi Vol. 5 No. 2 (2022): Jurnal Sistem dan Teknologi Informasi Komunikasi
Publisher : Universitas Katolik Musi Charitas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32524/jusitik.v5i2.704

Abstract

The film of Kuliah Kerja Nyata (KKN) in the Dancing Village which is being discussed among the Indonesian people is a film based on a novel by a simpleman entitled "KKN in the Dancing Village". The film tells the story of a group of students who are carrying out their KKN activities in a village in East Java where in that village there are still prohibitions that must not be violated by a group of students which caused the death of two students who were carrying out KKN in that village. Thanks to the broadcast, which is being widely discussed, it has formed positive and negative responses from the community towards this KKN film in Dancer Village. So this study aims to analyze the test results of 550 training data using the Naïve Bayes classification method taken from Instagram posts that have positive comments (105), negative (43), neutral (288), very positive (37) and very negative (36). This sentiment analysis produces an accuracy value of 60.7073%.
ANALISIS SENTIMEN INSTAGRAM VAKSINASI MASA PANDEMI COVID-19 MENGGUNAKAN METODE NAÏVE BAYES Dwi Winarti; Fanny Aura Salsabila; Fadia Ayu Cahyani; Nurirwan Saputra; Meilany Nonsi Tentua; Ahmad Riyadi
JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi Vol. 6 No. 1 (2022): Jurnal Sistem dan Teknologi Informasi Komunikasi
Publisher : Universitas Katolik Musi Charitas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32524/jusitik.v6i1.787

Abstract

The Covid-19 pandemic that has spread throughout the world. The government has also minimized the spread of the virus by implementing Large-Scale Social Restrictions (PSBB), implementing a lockdown, banning going home during Eid al-Fitr and so on. The government has also utilized social media as information and services for the community. The government also does not remain silent when there are many negative impacts on society, so the government takes vaccination action. The public's response to the vaccination program is quite interesting and varied on Instagram, both positive and negative. So this study aims to analyze sentiment towards the Covid-19 pandemic vaccination program using the Naïve Bayes method. Based on the results of sentiment analysis testing, the Instagram user with Quadgram tokenization obtained an accuracy value of 75.9124%.
Co-Authors Adikka Yudha Bintang Ramadan Ahmad Riyadi Ahmad Riyadi Ari Kusuma Wardana Berliana Nur Isnayni Dwi Winarti Fadia Ayu Cahyani Fanny Aura Salsabila Firdiyan Syah Riyan Fahmi Gunawan Salsa Bella Putri Selma Maharani Tentua, Meilany Nonsi Tri Hastono Yonawati Nur Anisa