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All Journal Bidik : Jurnal Pengabdian kepada Masyarakat JEECS (Journal of Electrical Engineering and Computer Sciences)
Karim, Arifin A. Abd.
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Arts Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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Membangun Semangat Melanjutkan Pendidikan Melalui Seminar Motivasi Belajar Hakim, Rafi Wildzan; Ernawati; Afiah, Dafa; Maulida, Zulfa; Al Imani, Muhammad Nasim Adil; Izaanatulhaqq, Ziyaan; Karim, Arifin A. Abd.
BIDIK: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 1 (2024): BIDIK: Jurnal Pengabdian kepada Masyarakat
Publisher : Fakultas Ilmu Budaya Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/bidik.v5i1.23537

Abstract

The community service activity in the form of a Learning Motivation Seminar was carried out by KKN students from Nahdlatul Ulama Indonesia University at SD Negeri Gadog 02, Sukajadi Village, involving 86 fourth-grade students. The program aimed to enhance students' motivation to pursue higher education. The low interest in continuing education was the main issue, prompting the KKN MD-V-03 group to organize this seminar. The methods used included initial observations, presentations, interactive discussions, as well as games and simulations to increase student participation. As a result, the students showed increased motivation, marked by their active engagement and courage in presenting their aspirations. This seminar not only provided short-term benefits but also motivated students to continue their education to higher levels. In conclusion, this program successfully boosted students' learning enthusiasm and raised awareness of the importance of education.
Sentiment Analysis of Public Opinion on PSSI Naturalization Program Based on Social Media Using the Naive Bayes Algorithm Reza Fahalevi, Mohammad; Ilhamsyah , Akbar; Karim, Arifin A. Abd.
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 2 (2025): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i2.7

Abstract

Football is the most popular sport in Indonesia and receives tremendous support from the public. However, the player naturalization program initiated by PSSI (the Indonesian Football Association) has become an issue that has captured public attention, generating diverse opinions on social media, particularly on the Twitter platform. This study aims to analyze public sentiment toward the naturalization program by applying the Naïve Bayes classification method. The data used consists of tweets containing keywords related to PSSI naturalization, naturalized players, descendant players, national team naturalization, and overseas players for the national team. The analysis process includes several stages of data preprocessing—such as text cleaning, normalization, and stop word removal—feature extraction using TF-IDF, and sentiment classification using the Naïve Bayes algorithm to categorize opinions into positive, negative, and neutral sentiments. The Naïve Bayes model achieved an accuracy of 0.65, precision of 0.42, recall of 0.65, and an F1-score of 0.51. It performed well in classifying neutral tweets but was less effective in identifying positive and negative sentiments. Overall, the Naïve Bayes method can be utilized for sentiment analysis; however, its classification performance is not yet optimal due to the limited amount of data.
Co-Authors Afiah, Dafa Al Imani, Muhammad Nasim Adil Ernawati Hakim, Rafi Wildzan Ilhamsyah , Akbar Izaanatulhaqq, Ziyaan Maulida, Zulfa Reza Fahalevi, Mohammad