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All Journal JITU : Journal Informatic Technology And Communication Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat
Syahputra, Bintang
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Library & Information Science Other

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Pemberdayaan Terhadap Masyarakat Menuju Desa Green Product, Kesehatan Mental Anak Yang Baik, dan Berpengetahuan Ai Syahputra, Bintang; Prayuda, Nazwan Putera; Ilham, Muhammad Maulana; Sadewa, Dimas Ibnu; Mubarok, Khoidar; Nurrohman, Ahmad Alfianto; Yofinaldi, Septian; Syaifulloh, Abu Rahman; Anggraini, Dewi; Ardiansa, Bily; Simatupang, Joshe Samuel Maruba
Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Vol. 5 No. 1 (2024): Juli 2024
Publisher : Fakultas Teknik Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/5h1vsa56

Abstract

The Community Service Program (KKN) carried out by Group 8 aims to empower the people of Bahagia Village towards an environmentally friendly and mentally healthy village. This program involves several main activities such as making hydroponics, catfish hatcheries, making plastic waste banks, socializing the prevention of online game addiction and promiscuity, as well as introducing artificial intelligence (AI) technology. Through this program, it is hoped that the community can obtain alternative sources of income, increase awareness of the importance of environmental management, and understand the impact and benefits of AI technology. The program results show that the activities carried out succeeded in having a positive impact on society both in terms of economics, environment and education.
Analisis Sentimen Komentar Film Merah Putih One For All Metode Naïve Bayes Syahputra, Bintang; Hartono, Budi
JITU Vol 10 No 1 (2026)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jitu.v10i1.2253

Abstract

Social media Twitter (X) has become a platform for expressing public opinion, including reactions to the animated film "Merah Putih: One For All." The film has garnered various criticisms regarding its graphic quality and the use of digital assets deemed unoriginal. Sentiment analysis of this public response is essential to provide an objective evaluation of society's reception of local animated works, identify specific aspects of audience concern, and offer valuable insights for the Indonesian animation industry to improve production quality. Automated sentiment classification using machine learning is an efficient solution for understanding patterns of public perception with large volumes of data, which is difficult to accomplish manually. This study classifies comments on the X platform into positive and negative sentiment categories using the Naïve Bayes method. Data collection was conducted by scraping posts from the account @tanyakanrl in August 2025, totaling 302 comments. The data underwent preprocessing stages, including cleaning, case folding, normalization, tokenizing, stopword removal, and stemming. Feature extraction utilized the TF-IDF (Term Frequency-Inverse Document Frequency) method to convert text data into numerical representation. Classification employed the Naïve Bayes algorithm with an 80:20 data split ratio for training and testing. Evaluation results indicate that the model achieved an Accuracy of 82%, Precision of 79%, Recall of 82%, and an F1-Score of 80%.
Co-Authors Ardiansa, Bily Budi Hartono Dewi Anggraini Ilham, Muhammad Maulana Mubarok, Khoidar Nurrohman, Ahmad Alfianto Prayuda, Nazwan Putera Sadewa, Dimas Ibnu Simatupang, Joshe Samuel Maruba Syaifulloh, Abu Rahman Yofinaldi, Septian