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All Journal Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Indonesian Journal on Software Engineering (IJSE) Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Jurnal Teknik Komputer AMIK BSI Paradigma SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Riset Informatika Journal of Information System, Applied, Management, Accounting and Research Jurnal Informatika Kaputama (JIK) JSAI (Journal Scientific and Applied Informatics) Bilancia : Jurnal Ilmiah Akuntansi BISEI: Jurnal Bisnis dan Ekonomi Islam Babul Ilmi Jurnal Ilmiah Multi Science Kesehatan Jurnal Ilmiah Islamic Resources Jurnal Riset Akuntansi dan Manajemen Malahayati (JRAMM) Pena Medika : Jurnal Kesehatan Jurnal Litbang Kota Pekalongan Open Access Indonesian Journal of Medical Reviews Computer Science (CO-SCIENCE) Simpatik: Jurnal sistem Informasi dan Informatika Profitabilitas J-Com (Journal of Computer) Academic Journal of Computer Science Research (AJCSR) Journal of Applied Management Research Jurnal Farmasi Klinik dan Sains At-Thullab : Jurnal Mahasiswa Studi Islam DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY FASKES : Jurnal Farmasi, Kesehatan, dan Sains Jurnal Sistem Informasi dan Manajemen Journal of Artificial Intelligence and Technology Information Prawara Jurnal Pengabdian Masyarakat
Eka Fitriani
Universitas Bina Sarana Informatika
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Pelatihan calistung menggunakan media flash card bagi siswa Sekolah Dasar Mahsup, Mahsup; Aditia, M.; Aprilianicahyati, Aprilianicahyati; Aminah, Aminah; Orowala, Anggriani; Utami, Anita Syafira; Sopian, Sopian; Zaenudin, Zaenudin; Fitriani, Eka
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 8, No 1 (2024): March
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v8i1.17505

Abstract

Abstrak                                                                                 Permasalahan pada siswa SDN 1 Keruak bahwa ada beberapa siswa yang masih kesulitan dalam membaca, menulis dan berhitung.  Tujuan Kegiatan pengabdian ini untuk meningkatkan kemampuan mengenal huruf dan angka. Metode pelaksanaan kegiatan dengan tahapan terdiri dari perencanaan, pelaksanaan dan evaluasi. Jumlah peserta kegiatan sebanyak 10 siswa. Hasil pengabdian bahwa kegiatan pelatihan calistung dengan menggunakan media Flash card diperoleh data sebesar 80% siswa ada peningkatan pemahaman dalam mengenal huruf dan angka. Kata Kunci: calistung; pelatihan; media flash card AbstractThe problem with SDN 1 Keruak students is that there are some students who still have difficulty in reading, writing and arithmetic.  The purpose of this service activity is to improve the ability to recognize letters and numbers. The method of implementing activities with stages consists of planning, implementation and evaluation. The number of participants in the activity was 10 students. The results of dedication that calistung training activities using Flash card media obtained data of 80% of students there was an increase in understanding in recognizing letters and numbers. Keywords: calistung; training; media flash card
Enhancing Sentiment Classification Performance on Tentang Anak Application Reviews Using Optimized Support Vector Machine Riska Aryanti; Eka Fitriani; Royadi Royadi; Dian Ardiansyah
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 4 No. 2 (2026): Volume 4 Number 2 June 2026
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v4i2.271

Abstract

The increasing use of parenting and child development applications has generated a large volume of user reviews containing valuable insights regarding application quality, usability, and user satisfaction. One of the widely used applications in Indonesia is Tentang Anak: Kehamilan & Anak. However, manually analyzing these reviews is inefficient due to the large amount of unstructured textual data. Therefore, this study aims to enhance sentiment classification performance on user reviews of the Tentang Anak: Kehamilan & Anak application using an optimized Support Vector Machine (SVM) model. The dataset consisted of user reviews collected from application platforms, which were processed through several text preprocessing stages, including cleaning, normalization, tokenization, stopword removal, and stemming. Sentiment labeling was conducted using polarity scores to classify reviews into positive and negative sentiments. The proposed model was evaluated using different test size scenarios (0.1, 0.2, 0.3, and 0.4) and random state configurations to identify the optimal parameter setting. Experimental results demonstrate that the best performance was achieved at a test size of 0.1 with random state 0, obtaining an accuracy of 89.8%, precision of 91.7%, recall of 55.0%, and F1-score of 68.8%. The findings indicate that the optimized SVM model is effective in classifying sentiment in reviews of the Tentang Anak: Kehamilan & Anak application, particularly in achieving high precision and classification stability across multiple testing scenarios. Furthermore, the study highlights the importance of parameter optimization in improving sentiment analysis performance for user-generated textual data.
Analisis Sentimen Pengguna GoPay pada Layanan Keuangan Digital dengan Perbandingan Naïve Bayes dan SVM Dian Ardiansyah; Riska Aryanti; Eka Fitriani; Royadi
PROFITABILITAS Vol 5 No 2 (2025): JURNAL PROFITABILITAS
Publisher : Sistem Informasi Akuntansi Kampu Kabupaten Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/profitabilitas.v5i2.11513

Abstract

The rapid development of digital financial services has led to increased use of digital wallets, one of which is the GoPay application, resulting in a large volume of user reviews. These reviews contain valuable information regarding user satisfaction and service-related issues, making automated methods necessary to accurately analyze user sentiment. This study aims to analyze sentiment in GoPay user reviews and compare the performance of the Naïve Bayes and Support Vector Machine (SVM) algorithms for sentiment classification.This research uses a dataset of 132,393 GoPay user reviews obtained from the Kaggle platform. The data are labeled based on user ratings into three sentiment classes: positive, neutral, and negative. The research stages include text preprocessing, feature transformation using the Term Frequency–Inverse Document Frequency (TF-IDF) method, sentiment classification using the Naïve Bayes and SVM algorithms, and model performance evaluation using accuracy, precision, recall, and F1-score metrics.The results show that 79.2% of the reviews are classified as positive, 17.1% as negative, and 3.7% as neutral. Based on performance evaluation, the SVM algorithm demonstrates superior results with an accuracy of 90.65%, precision of 90.7%, recall of 90.65%, and F1-score of 89.05%, compared to Naïve Bayes, which achieves an accuracy of 87.89%, precision of 89.1%, recall of 87.89%, and F1-score of 88.42%. These findings indicate that SVM is a more optimal method for sentiment analysis of GoPay user reviews, while Naïve Bayes remains an efficient and competitive alternative for large-scale text classification.
Transformasi Literasi Digital dan Penguatan Kompetensi Basis Data bagi Santri Yayasan Rumah Harapan di Era Revolusi Industri 5.0 Suhardi; Muhammad Tabrani; Widya Apriliah; Eka Fitriani
PRAWARA Jurnal ABDIMAS Vol 5 No 2 (2026): PRAWARA JURNAL ABDIMAS
Publisher : CV. Manha Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Akselerasi transformasi digital secara global telah menempatkan penguasaan teknologi informasi sebagai pilar utama dalam pembangunan sumber daya manusia yang kompetitif, terutama bagi generasi muda di lingkungan pendidikan non-formal dan lembaga sosial. Kegiatan pengabdian kepada masyarakat ini difokuskan pada upaya strategis untuk menjembatani kesenjangan literasi digital melalui pelatihan dasar pengkodean (coding) dan pengenalan konsep basis data bagi santri di Yayasan Rumah Harapan Karawang. Mengingat urgensi kebutuhan talenta digital nasional yang diproyeksikan mencapai sembilan juta orang pada tahun 2030, intervensi edukatif pada tingkat akar rumput menjadi krusial. Metode pelaksanaan kegiatan ini mengadopsi pendekatan partisipatif dan interaktif, mencakup tahapan analisis kebutuhan, transfer pengetahuan melalui workshop teknis, hingga praktik mandiri yang berorientasi pada pemecahan masalah. Hasil evaluasi melalui analisis data statistik pre-test dan post-test menunjukkan adanya peningkatan signifikan dalam pemahaman kognitif dan keterampilan psikomotorik peserta terhadap logika pemrograman dan struktur data. Selain aspek teknis, kegiatan ini berhasil memicu transformasi pola pikir santri dari pengguna teknologi yang konsumtif menjadi inovator yang produktif. Keberhasilan program ini menegaskan bahwa integrasi antara nilai-nilai pendidikan tradisional pesantren dengan kompetensi teknologi modern merupakan katalisator utama bagi kemandirian ekonomi dan penguatan ekosistem digital nasional di tengah dinamika Masyarakat 5.0.
Co-Authors Abdillah Abdillah Abdussomad, Abdussomad Aditia, M. Agus Herianto Alta, Ulik Aminah Aminah Apridonal M, Yori Aprilia, Widya Aprilianicahyati, Aprilianicahyati Ardiana Priharwanti Arina, Yudi Asharsyira, Almeyda Atang Saepudin Azwir Nasir Baiti, Nurul Dahlia Dahlia Dede Firmansyah Saefudin Dede Saefudin Dewi, Lucia Vita Inandha Dian Ardiansyah Dila Delia Fadilah Duwi Cahya Putri Buani Dzulfikar, Dzulfikar Emrinaldi Nur, Emrinaldi Erna Listyaningsih Galih Pratiwi, Galih Hafidz, Putra Hakim, Ahmad Ibrahim Ibrahim Ilham Kurniawan Mahsup, Mahsup Mariaty Ibrahim Mastur Mizan habibi, Moh Muhamad Tabrani Muhammad Faittullah Akbar Muhammad Tabrani Negsi, Ratika Nindi Vaulia Puspita, Nindi Vaulia Onny Indriani Orowala, Anggriani R, Herowati Ramadhiani, Aninditha Rachmah Richardus Eko Indrajit Rifky Permana Riska Aryanti Risky Cahyani, Fhadilla Rizal Amegia Saputra Royadi - Royadi, Royadi Rr. Vita Nurlatif SALMAN ALFARIZI Sativa, Risya Oriza Sintayana Muhardini Siregar, Iqbal Kamil Sopian sopian Suhardi Suhardi Swahip, Swahip Syafril Syafril Tari, Mayang Utami, Anita Syafira Vera Mandailina, Vera Widya Apriliah Wijaya, Mario Wuryanti, Lestari Yuliari, Kartika Yuniarti Yuniarti Zaenudin Zaenudin