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All Journal Jurnal Ilmiah Sinus Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Ittishal Educational Research Journal JURNAL REKAYASA INFORMASI SWADHARMA (JRIS) Postulat : Jurnal Inovasi Pendidikan Matematika Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Jurnal Pengabdian Masyarakat Teknologi dan Pendidikan (MANTAP) Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA) Jurnal Ilmu Komputer dan Teknik Informatika Indonesian Applied Research Computing and Informatics
Dwi Remawati
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Public Health Social Sciences Other

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Penguatan Identitas Visual UMKM Abon Dua Saudara melalui Kegiatan Desain Spanduk Aditya Bagas Pratama; Remawati, Dwi; Vulandari, Retno Tri; Sandradewi, Kumaratih; Yudanto, Bramasto Wiryawan
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.984

Abstract

The rapid development of technology in the modern era requires micro, small, and medium enterprises (MSMEs) to adapt in order to remain competitive, particularly in the area of marketing and information dissemination. Abon Dua Saudara MSME, which has operated for over twenty years in the food processing sector, faces challenges related to limited promotional media, resulting in low public awareness of its products. This community service activity aims to strengthen the visual identity of Abon Dua Saudara MSME through the design and development of promotional banners using CorelDraw. The method employed in this program includes needs assessment, design training, and direct assistance in creating effective and visually appealing banners. The activity focuses on improving participants’ skills in utilizing digital design tools to produce promotional media that are informative, attractive, and aligned with the business identity. The results of this program indicate an improvement in the MSME’s capability to create independent promotional materials, as well as an enhanced visual identity that supports broader market reach. In conclusion, the implementation of banner design activities contributes positively to strengthening the branding and promotional effectiveness of Abon Dua Saudara MSME. This initiative is expected to increase public awareness and support the sustainability and growth of the business.
PERBANDINGAN METODE SUPPORT VECTOR MACHINE DAN K-NEAREST NEIGHBOR DALAM ANALISIS SENTIMEN ULASAN APLIKASI MyXL Nugroho, Raka Aji; Remawati, Dwi; Susyanto, Teguh; Saptomo, Wawan Laksito Yuly
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 14, No 1 (2026): Jurnal Tikomsin, Vol 14, No.1, April 2026
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v14i1.1062

Abstract

Sentiment analysis is an essential tool for understanding user perceptions of mobile applications, especially when reviews are unstructured text. This study aims to analyze user reviews of the MyXL application using Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) and to compare their performance in classifying sentiments into positive, negative, and neutral categories. The dataset was obtained from Google Play Store via Kaggle and underwent text preprocessing, including case folding, removal of numbers and punctuation, tokenization, stopword removal, normalization, and stemming. Features were transformed into numerical representations using TF-IDF, and the data was split into training (70%) and testing (30%) sets. Evaluation using accuracy, precision, recall, and F1-score showed that SVM outperformed KNN with an accuracy of 0.743 versus 0.64, particularly in classifying neutral reviews. KNN exhibited higher misclassification in positive and negative classes, while SVM was more stable but tended to be biased toward the neutral class. These results provide insights for application developers to better understand user satisfaction and guide service improvement and feature development.
Performa Logistic Regression dalam Klasifikasi Sentimen Opini Publik Pemilu di India Puspa Ningrum, Okky; Remawati, Dwi; Susyanto, Teguh; Laksito Yuly Saptomo, Wawan
Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence) Vol 6 No 1 (2026): Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakaai.v6i1.1566

Abstract

Opini publik tentang pemilu di India melalui media sosial sangat tinggi, terutama melalui twitter. Untuk mengetahui apakah opini tersebut positif, negative atau netral maka dilkukan analisis sentiment. Data teks dari media sosial bersifat tidak terstruktur dan penuh noise sehingga diperlukan model klasifikasi yang mampu bekerja secara efektif pada teks pendek dan bervariasi. Penelitian ini menggunakan algoritma Logistic Regression. Hasil eksperimen menunjukkan bahwa model dapat mencapai akurasi sebesar 84,46%. Temuan ini menunjukkan bahwa pendekatan yang diusulkan dapat berfungsi sebagai metode yang andal dan efisien untuk pemantauan opini publik secara otomatis. Hasil penelitian menunjukkan bahwa Logistic Regression mampu memberikan performa klasifikasi yang stabil dengan tingkat akurasi yang kompetitif untuk analisis sentimen politik pada teks pendek media sosial. Model juga menunjukkan konsistensi dalam menangani distribusi sentimen yang tidak seimbang.
Co-Authors Abdul Dhohir Surya Kusuma, RM Abdullah Ahmad Ma'shum Aditya Bagas Pratama Ady Prabowo, Iwan Afril efan Pajri Ahyar, Khoirul Ajeng Dhanty Yoshima Aji Pratama Wisnu Wardana Amin Joko Susilo Baktiar Setiyaji Bebas Widada Bramasto Wiryawan Yudanto Bramastyo Wiryawan Yudhanto Charles Parningotan Haratua Simanjuntak Cynthia, Dessy Nia Cynthia, Maulidania Mediawati Dicky Jordan Aji Putra Didik Nugroho Didik Nugroho, Didik Effendi, Rohmat Irvan Eka Pandu Cynthia Firman Dwi Wahyudi Fitriani, Putri Asiska Nur Haqiqi, Arif Naofal Hendro Wijayanto Heru Budi Kusumo Iwan Ady Prabowo Khairunnisa Kirana Wardana, Adam Candra Kriswantoro Budi Satrio Kumaratih Sandradewi Kumaratih Sandradewi Kustanto Kustanto Lestari, Zannuba Anugrah Indah Muhammad Hasbi Mujirahayu Meyliana, Nirma Nugroho, Raka Aji paulus harsadi Prasastya Dwi Pamungkas Prasetyo, Danar Aji Puspa Ningrum, Okky Putri Pertiwi, Ina Putro, Bagus Cahyo Raden Arie Febrianto Raharja, Bayu Dwi Restu Utami, Widya Retno Tri Vulandari Ruvyanto Dwi Nugroho Saptomo, Wawan Laksito Yuly Septiana, Anisa Dwi Setiyowati Sri Hariyati Fitriasih Sri Hariyati Fitriasih Sri Hariyati Fitriasih Sri Hariyati Fitriasih, Sri Hariyati Teguh Susyanto Tri Irawati Tri Irawati Tri Irawati, Tri Tulus Wahyuno Vivi Dian Pratiwi Widada, Bebas Widianto, Septian Cahyo Wijayanto, Hendro Yustina Retno Wahyu Utami