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All Journal JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Padma: Jurnal Pengabdian Kepada Masyarakat Jurnal Medika: Medika
Salma Ngarifatul Khofiyah
Universitas Amikom Purwokerto
Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Comparison of Naive Bayes and SVM in Public Opinion Sentiment Analysis on Platform X Salma Ngarifatul Khofiyah; Pungkas Subarkah
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.478

Abstract

The growth of social media has made it the primary means for the general public to express their opinions, including on political and legal issues in Indonesia. One topic that has been widely discussed is the abolition of Tom Lembong and the amnesty granted to Hasto Kristiyanto by President Prabowo Subianto, which has garnered mixed public reactions on the X platform. The purpose of this study is to analyze public sentiment regarding current issues and compare the performance of two machine learning algorithms, Naïve Bayes and Support Vector Machine (SVM), to classify public opinion. Data was obtained through a crawling process of 3,003 tweets, followed by a preprocessing stage that included cleaning, case folding, slang normalization, tokenizing, stopword removal, and stemming. Next, a suitability analysis using the TF-IDF method was conducted before the data was processed by the two algorithms. The results showed that, of the 2,998 valid tweets, 78.6% of public opinion was negative and only 21.4% was positive, indicating a predominance of criticism of the issues discussed. When comparing the algorithms, SVM provided more accurate results with an accuracy rate of 78.66%, while Naïve Bayes only achieved 58%. This shows that SVM is more flexible in analyzing text data with a high level of complexity compared to Naïve Bayes.
Pendampingan Digitalisasi Layanan Komunitas Captain Singalodra Berbasis Aplikasi Sewa Perahu Suliswaningsih; Anugerah Bagus Wijaya; Lina Puspitasari; Nurul Khotimah Ansyari; Salma Ngarifatul Khofiyah
PADMA Vol 5 No 2 (2025): JURNAL PENGABDIAN KEPADA MASYARAKAT (PADMA)
Publisher : LPPM Politeknik Piksi Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/padma.v5i2.2121

Abstract

Pengabdian ini mengatasi keterbatasan informasi, transparansi layanan, promosi digital, dan literasi teknologi pada komunitas Captain SingaLodra (CSL) melalui aplikasi Book Capt. Tujuannya meningkatkan kapasitas kapten kapal dalam pengelolaan akun, penjadwalan, serta promosi digital. Metode partisipatif meliputi sosialisasi, pelatihan, pendampingan, dan evaluasi. Hasil menunjukkan peningkatan literasi digital, layanan lebih profesional, serta kepuasan wisatawan. Dari 30 responden, mayoritas merasa lebih mudah memperoleh informasi harga, ketersediaan jadwal, dan layanan yang transparan. Program ini berdampak pada meningkatnya daya saing CSL dalam ekosistem wisata bahari berbasis teknologi.
Pendampingan e-Smart Early Warning untuk Peringatan Dini Banjir di Wisata Desa Karangsalam Lor Nandang Hermanto; Pungkas Subarkah; Dini Riandini; Refida Septiana Putri; Salma Ngarifatul Khofiyah; Bagus Adhi Kusuma; Primandani Arsi
Jurnal Medika: Medika Vol. 4 No. 4 (2025)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/0yyt8272

Abstract

The Juneng Mijil Community Self-Help Group (KSM) in Karangsalam Lor Village, Baturraden District, Banyumas Regency is a village tourism manager, one of which is Juneng Waterfall. The problem with the partners is that there is no technology used for early flood warning at the Juneng Waterfall and Twin Waterfall tourist sites, as well as low community literacy regarding early flood management. This activity aims to optimize the use of Android-based information technology and the Internet of Things (IoT) applied at Juneng Waterfall and Kembar Waterfall, through KSM Juneng Mijil in Karangsalam Lor Village. The implementation methods in this community service include the Pre-Implementation Stage, Implementation Stage, and Evaluation Stage. The results of the activity showed high enthusiasm among participants, as well as an increase in understanding and knowledge regarding the benefits, usage, and maintenance of the Internet of Things (IoT) and Android. This activity is important in the utilization of technology, particularly in optimal and safe flood warning systems for the community.
Co-Authors Anugerah Bagus Wijaya Bagus Adhi Kusuma Dini Riandini Lina Puspitasari Nandang Hermanto Nurul Khotimah Ansyari Primandani Arsi Pungkas Subarkah Refida Septiana Putri Suliswaningsih