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All Journal JOIV : International Journal on Informatics Visualization Community Empowerment
Rio Wirawan
Universitas Pembangunan Nasional Veteran Jakarta, Jakarta, Indonesia
Arts Humanities Computer Science & IT Education Public Health Social Sciences

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Development of MSMEs' potential through digital marketing in Pabean Udik Village, Indramayu Regency Bambang Saras Yulistiawan; Rio Wirawan; Catur Nugrahaeni; Andhika Octa Indarso
Community Empowerment Vol 7 No 12 (2022)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ce.8212

Abstract

Development of digital marketing techniques is mostly driven by changes in customer behavior and technology advancements. A major element of this transformation is the MSME sector. The Faculty of Computer Science, UPN Veteran Jakarta provides community service by training and implementing digital marketing for MSMEs in Pabean Udik Village. This program was carried out to support MSMEs so they can take advantage of digital technology to promote products, effectively interact and communicate with potential customers wherever they are. The program method involves training participants on how to digitize products using their personal smartphones, which is followed by the development of a company profile that serves as a landing page for customers using the Google My Business program. A technical team and trainers help them develop business profiles and upload images of their products. The training has increased the participants' knowledge of product digitization. Additionally, MSME products are eye-catching and simple to market online using Google My Business applications.
Text Mining for News Forecasting on The Turnback Hoax Website Rio Wirawan; Erly Krisnanik; Artika Arista
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1939

Abstract

News has been disseminated swiftly via the internet due to the rapid growth of information technology. The rapid spreading of news often confuses because the truth cannot be ascertained. Additionally, online social media is becoming increasingly popular, making it an excellent environment for propagating false information, including misinformation, phony reviews, advertising, rumors, political remarks, innuendo, etc. This study's specific goal is to classify data using a data mining approach model called text mining so that a system can automatically do the classification. As a result, the study will produce a dataset, which can then be used to create an application using data mining's ability to predict breaking news. An application was produced by employing data mining to forecast recent news. This study was able to classify data using a naive Bayes data mining approach model so that a system can automatically do the classification. The study produced an accuracy of 77% obtained with training data of 82%. From 994 contents, the classification of misleading content reached 33.9%, false content as many as 24.85%, imitation content was 13.48%, fake content reached 11.07%, manipulated content was 9.86%, parody content was 3.22%, satire content was 2.31%, and connection content as many as 1.31%. This study then visualizes the results using bar charts and word clouds. This work also produced datasets with the naïve Bayes method of news data and news that has been valid. Afterward, the dataset will be used in making applications to produce prototypes of computer program applications.
Co-Authors Andhika Octa Indarso Artika Arista Bambang Saras Yulistiawan Catur Nugrahaeni Erly Krisnanik