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Muhammad Agreindra Helmiawan
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Infomans: Jurnal Ilmu-ilmu Informatika dan Manajemen
Published by Universitas Sebelas April
ISSN : 19783310     EISSN : 26153467     DOI : 10.33481/infomans
Core Subject : Science,
Computer Science & IT
Infomans Journal is a scientific journal published by LPPM and Fakultas Teknologi Informasi FTI UNSAP. This journal contains scientific papers from Academics, Researchers, and Practitioners about research on informatics. Infomans Journal is published twice a year in May and November. The paper is an original script and has a research base on Informatics. The scope of the paper includes several studies but is not limited to the following study. Artificial Intelligence Computer Graphics and Animation Image Processing Cryptography Computer Network Security Modeling and Simulation Information Retrieval Information Filtering Multimedia Computer Architecture Design Computer Vision and Robotics Parallel and Distributed Computing Operating System Information System Mobile Computing Natural Language Processing Data Mining Machine Learning Expert System Geographical Information System
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1 Documents
 1 
Search results for , issue "Vol. 16 No. 1 (2022): Infoman's" : 1 Documents clear
Analisis Sentimen Stakeholder Atas Layanan Haidjpb Pada Media Sosial Twitter Dengan Menggunakan Metode Support Vector Machine dan Naïve Bayes Harsono, Muhammad Luthfiy Kurniawan; Alkhalifi, Yuris; Nurajijah; Gata, Windu
Infoman's : Jurnal Ilmu-ilmu Informatika dan Manajemen Vol. 16 No. 1 (2022): Infoman's
Publisher : LPPM & Fakultas Teknologi Informasi UNSAP

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Abstract

Creation of a special account on social media Instagram and Twitter that aims to accommodate the delivery of questions, input, criticism and suggestions from stakeholders around the ongoing business processes and the use of applications in the framework of budget planning, commitment making, disbursement of the state budget, accounting receipts and financial reporting based on the fact that social media cannot be separated from community activities because the presence of digital devices (smartphones) and affordable internet access makes various groups of people able to obtain information quickly and easily. Organizations have an interest in getting benchmarks for services that have been provided in order to improve the quality of services going forward based on tweets data obtained from Twitter social media. This study discusses the process of collecting and processing tweet data on the @haiDJPb account in order to perform stakeholder sentiment analysis of haiDJPb services on twitter social media using Support Vector Machine and Naïve Bayes algorithms and the accuracy of the Support Vector Machine algorithm is 74.55 % and 77.18% for the Naïve Bayes algorithm.

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