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All Journal Insand Comtech : Information Science and Computer Technology Journal JEECS (Journal of Electrical Engineering and Computer Sciences)
Mohammad Reza Fahalevi
Universitas Nahdlatul Ulama Indonesia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Sentiment Analysis of Public Opinion on PSSI Naturalization Program Based on Social Media Using the Naive Bayes Algorithm Mohammad Reza Fahalevi; Akbar Ilhamsyah; Arifin A. Abd. Karim
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 2 (2025): December
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.
Implementasi Usability Testing Menggunakan Metode Eucs Pada Web Sianas Universitas Nahdlatul Ulama Indonesia Mohammad Reza Fahalevi; Khusnul Khotimah; Sry Dhina Pohan
Insand Comtech : Information Science and Computer Technology Journal Vol. 11 No. 2 (2026): Insand Comtech
Publisher : Universitas Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53712/jic.v11i2.3134

Abstract

SIANAS, singkatan dari Sistem Informasi Akademik Universitas Nahdlatul Ulama Indonesia, merupakan layanan berbasis website yang dipakai oleh mahasiswa, dosen, dan tenaga pendidik untuk mempermudah berbagai urusan akademik. Melalui sistem ini, pengguna dapat mengisi Kartu Rencana Studi (KRS), mengatur jadwal kuliah, memantau nilai, hingga mengurus administrasi akademik lainnya secara daring. Namun perlu dipahami, baik atau tidaknya sebuah sistem informasi sebenarnya tidak cukup dinilai hanya dari lengkap tidaknya fitur yang ditawarkan. Ada faktor lain yang sama pentingnya, yaitu tingkat kepuasan pengguna saat benar-benar memakai sistem tersebut dalam aktivitas sehari-hari. Atas dasar itulah penelitian ini disusun, dengan tujuan mengukur seberapa puas pengguna terhadap Website SIANAS. Metode yang dipilih adalah End User Computing Satisfaction (EUCS), yang meninjau kepuasan dari lima sisi sekaligus yaitu content, accuracy, format, ease of use, serta timeliness. Untuk memperoleh data, peneliti menyebarkan kuesioner kepada 97 responden yang terdiri dari mahasiswa, dosen, dan tenaga pendidik, dengan jumlah sampel dihitung memakai rumus Slovin. Selanjutnya, seluruh data diolah melalui IBM SPSS Statistics versi 27, melewati tahap uji validitas, uji reliabilitas, hingga analisis deskriptif. Hasil penelitian menunjukkan bahwa Website SIANAS UNUSIA memiliki tingkat kepuasan pengguna yang tergolong baik berdasarkan lima dimensi EUCS, dengan dimensi Content memperoleh nilai tertinggi dan Format memperoleh nilai terendah sehingga menjadi prioritas perbaikan.
Co-Authors Akbar Ilhamsyah Karim, Arifin A Abd Khusnul Khotimah Pohan, Sry Dhina