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Samsuriah
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ANALISIS SENTIMEN PERILAKU MANUSIA PADA PRODUK DAN ORGANISASI MENGGUNAKAN K-MEANS DAN SVM Mawar; Syamsia; Samsuriah
Nusantara Hasana Journal Vol. 3 No. 12 (2024): Nusantara Hasana Journal, May 2024
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v3i12.1123

Abstract

Sentiment analysis is the process of extracting information from text and is considered opinion mining. Machine learning experiments have been demonstrated in research involving reviews, blogs, for several texts written in different languages ​​including Dutch, English, and French. A set of example sentences was prepared which were manually labeled neutral, positive, or negative. This study covers consumer curiosity about certain consumer products. A categorization model has been developed that has been used in research. A number of issues involving the noisy nature of text have been addressed in research. With an accuracy of around 83%, positive, negative and neutral sentiment towards the subject under study can be determined using unigram features enriched with linguistic information. The role of active learning approaches in minimizing the number of examples that need to be manually annotated is discussed in this article. This research provides data on the transferability of the studied model. Sentiment analysis of a particular employee has been studied using K-Means Clustering and SVM classification to classify the sentiment of the text.
TRANSFORMASI PENDIDIKAN BERBASIS TEKNOLOGI: PERAN ARTIFICIAL INTELLIGENCE DAN INTERNET OF THINGS DALAM PEMBELAJARAN Yosua, Brayend; Samsuriah
PROGRESS Vol 16 No 2 (2024): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v16i2.436

Abstract

Artificial Intelligence (AI) has had a significant impact on the world of education, especially in improving the quality of learning and administrative efficiency. This study aims to analyze the main benefits of AI in education, including personalization of learning, efficiency of administrative processes, and accessibility to educational resources. Through a literature study approach. In addition, AI enables the development of virtual tutors, learning chatbots, and other technologies that provide flexibility in supporting independent learning. This technology also improves the efficiency of educational administration, such as automated assessment and student data management. Despite its many benefits, the application of AI faces challenges such as technological gaps and data privacy. With its great potential, AI is expected to continue to develop as an innovative solution to create inclusive, adaptive, and sustainable education.
Co-Authors Mawar Syamsia Yosua, Brayend