Theresia Herlina Rochadiani
Pradita University

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Efforts to Improve the Welfare of Ornamental Fish Farmers in Kalipaten Village Through the Implementation of LoRaWAN-Based IoT Technology William Widjaja; Theresia Herlina Rochadiani; Handri Santoso; Ninuk Yasmarini; Sherensia Putri Angeliani; Gabriel Alexander
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol 7 No 2 (2023): November 2023
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/engagement.v7i2.1339

Abstract

The ornamental fish business is currently one of the popular businesses in the community. The relatively fast reproduction cycle, around 0.5 – 1.5 months, with a relatively high selling price, makes this ornamental fish business much in demand by the public. The maximum utilization of technology will help MSMEs in increasing their income. This service activity aims to build a LoRaWAN-based IoT system for ornamental fish farming along with a mobile-based ornamental fish monitoring application to help manage ornamental fish livestock, which ultimately has an impact on improving the quality of ornamental fish and the income of CV Home Aquafish partners. The method utilizes a service-learning approach through stages: Identify, design, and build a LoRaWAN-based IoT and mobile-based monitoring system, implementing, mentoring, and measuring the effectiveness of the LoRaWAN device in improving the quality of ornamental fish and the income of CV Home Aquafish partners. As a result, LoRaWAN can effectively help minimize mortality in ornamental fish seedlings so that the quality of the fish is maintained. The income of CV Home Aquafish's ornamental fish nursery partners in Kalipaten Village, Gading Serpong, Tangerang also increases.
Sentiment Analysis of YouTube Comments Toward Chat GPT Theresia Herlina Rochadiani
Jurnal Transformatika Vol. 21 No. 1 (2023): July 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.7033

Abstract

Sentiment analysis is used for analyzing the emotions and attitudes expressed in text data. In this study, sentiment analysis is used to understand people’s enthusiasm toward Chat GPT. The primary objective of this study is to investigate the acceptance of people of new artificial intelligence technology, Chat GPT, that may change the future. To get a deep understanding of it, a large dataset of user comments from YouTube is collected and then data pre-processing is done by removing stop words, punctuations, and irrelevant information. Using Text Blob and VADER approaches, comments are classified into positive, neutral, and negative categories. The result shows that most users have a positive sentiment to receive and use Chat GPT. The contribution of this study is to provide insights into the sentiment of people’s response to Chat GPT, which can inform user acceptance of the language model development and give guide its future applications.