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All Journal Jurnal Minds: Manajemen Ide dan Inspirasi Jusikom : Jurnal Sistem Komputer Musirawas Journal of English for Academic and Specific Purposes (JEASP) Jurnal Sinergitas PkM & CSR FaST : Jurnal Sains dan Teknologi SEIKO : Journal of Management & Business Jurnal Teknologi Informasi MURA Martabe : Jurnal Pengabdian Kepada Masyarakat JURNAL AKUNIDA International Journal of Public Budgeting, Accounting and Finance Nation State : Journal of International Studies Sang Pencerah: Jurnal Ilmiah Universitas Muhammadiyah Buton JPEK (Jurnal Pendidikan Ekonomi dan Kewirausahaan) Best Journal (Biology Education, Sains and Technology) Jurnal Abdi Insani Jurnal Ilmiah Manajemen Kesatuan Journal of Industrial Engineering & Management Research (JIEMAR) Jurnal Pengabdian Nasional SUPREMASI Jurnal Hukum Nobel Management Review LEARNING : Jurnal Inovasi Penelitian Pendidikan dan Pembelajaran Jurnal Info Sains : Informatika dan Sains Didaktika Jurnal Pengabdian Kesehatan Masyarakat Prosiding Konferensi Nasional PKM-CSR PAKDEMAS : Jurnal Pengabdian Kepada Masyarakat Journal Of Human And Education (JAHE) Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi TRANSFORMATIONAL LANGUAGE, LITERATURE, AND TECHNOLOGY OVERVIEW IN LEARNING (TRANSTOOL) Proceeding Applied Business and Engineering Conference Journal of Artificial Intelligence and Digital Business Jurnal Ekonomi, Teknologi dan Bisnis Entrepreneurship and Small Business Research International Journal of Application on Economics and Business Jurnal Teknologi Informasi Mura Community Empowerment Journal The Indonesian Journal of General Medicine Berbakti Journey: Journal of English Language and Pedagogy Economics Monetary Journal
Sylvia, Sylvia
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EVALUASI KINERJA KNN DAN NAÏVE BAYES UNTUK ANALISIS SENTIMEN KOMENTAR INSTAGRAM PEJABAT PUBLIK BERBASIS TF-IDF Permata, Rizka; Sylvia, Sylvia; Arpan, Atika
Jurnal Teknologi Informasi Mura Vol 17 No 2 (2025): Jurnal Teknologi Informasi Mura DESEMBER
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v17i2.2861

Abstract

Penelitian ini bertujuan mengevaluasi kinerja algoritma K-Nearest Neighbors (KNN) dan Naïve Bayes untuk klasifikasi sentimen komentar publik pada akun Instagram pejabat publik di Indonesia. Sebanyak 137.141 komentar dikumpulkan melalui web scraping dan diproses menggunakan tahapan text preprocessing, meliputi case folding, pembersihan teks, tokenization, stopword removal, normalisasi, dan stemming. Representasi fitur menggunakan Term Frequency–Inverse Document Frequency (TF-IDF). Evaluasi performa meliputi accuracy, precision, recall, F1-score, dan waktu komputasi. Hasil menunjukkan bahwa Naïve Bayes memiliki akurasi tertinggi sebesar 0,9230, sedikit lebih baik dibandingkan KNN sebesar 0,9209. Kedua model menunjukkan performa sangat tinggi pada kelas netral, namun rendah pada kelas positif dan negatif akibat ketidakseimbangan kelas. Temuan ini menegaskan bahwa kombinasi TF-IDF dan Naïve Bayes masih menjadi baseline yang efektif untuk analisis sentimen berskala besar pada teks pendek media sosial.
EVALUASI KINERJA KNN DAN NAÏVE BAYES UNTUK ANALISIS SENTIMEN KOMENTAR INSTAGRAM PEJABAT PUBLIK BERBASIS TF-IDF Permata, Rizka; Sylvia, Sylvia; Arpan, Atika
Jurnal Teknologi Informasi Mura Vol 17 No 2 (2025): Jurnal Teknologi Informasi Mura DESEMBER
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v17i2.2861

Abstract

Penelitian ini bertujuan mengevaluasi kinerja algoritma K-Nearest Neighbors (KNN) dan Naïve Bayes untuk klasifikasi sentimen komentar publik pada akun Instagram pejabat publik di Indonesia. Sebanyak 137.141 komentar dikumpulkan melalui web scraping dan diproses menggunakan tahapan text preprocessing, meliputi case folding, pembersihan teks, tokenization, stopword removal, normalisasi, dan stemming. Representasi fitur menggunakan Term Frequency–Inverse Document Frequency (TF-IDF). Evaluasi performa meliputi accuracy, precision, recall, F1-score, dan waktu komputasi. Hasil menunjukkan bahwa Naïve Bayes memiliki akurasi tertinggi sebesar 0,9230, sedikit lebih baik dibandingkan KNN sebesar 0,9209. Kedua model menunjukkan performa sangat tinggi pada kelas netral, namun rendah pada kelas positif dan negatif akibat ketidakseimbangan kelas. Temuan ini menegaskan bahwa kombinasi TF-IDF dan Naïve Bayes masih menjadi baseline yang efektif untuk analisis sentimen berskala besar pada teks pendek media sosial.
Teacher’s Perception on AI Overuse by Students: Did AI Do Your Task? Wicaksono, Julien Arief; Setiarini, Rimbi Budi; Suharsono, Degita Danur; Surayya, Siti Ayu; Murti, Ghanesya Hari; Sylvia, Sylvia
Journey: Journal of English Language and Pedagogy Vol. 8 No. 2 (2025): Journey: Journal of English Language and Pedagogy
Publisher : UIBU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33503/journey.v8i2.1778

Abstract

Artificial Intelligence (AI) applications such as ChatGPT, Grammarly, and Google Translate are often used by students to help them to find ideas, write, translate, and even organize the ideas. These applications can support learning, yet many teachers have noticed that students are using them excessively. This study aims to look at university English teachers’ perceptions and responses toward students’ overuse of AI tools in asynchronous learning contexts. This study employed a narrative inquiry approach. The source of the data was five narratives from five university teachers reflected on real situations when they suspected students were overusing AI. The narratives were then thematically analysed to identify emerging patterns and emotional responses. The findings of this research highlight some emotional and ethical dilemmas that teachers experienced, the signs they noticed in student work, and the strategies they used to deal with the problems, and he strategies they employed to promote responsible AI use among students. This study also shows that teachers are trying to balance the use of AI as a helpful tool, not a replacement for learning. It also suggests clearer policies from the institutions, better digital ethics education for the students, and stronger support for teachers in today’s AI era.
EVALUASI KINERJA ALGORITMA SUPPORT VECTOR MACHINE (SVM) UNTUK ANALISIS SENTIMEN KOMENTAR PUBLIK TERHADAP PEMERINTAHAN PRESIDEN PRABOWO ARPAN, ATIKA; Sylvia, Sylvia; Permata, Rizka
Jurnal Teknologi Informasi Mura Vol 18 No 1 (2026): Jurnal Teknologi Informasi Mura
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v18i1.2864

Abstract

Penelitian ini bertujuan untuk menganalisis sentimen komentar publik terhadap pemerintahan Presiden Prabowo menggunakan algoritma Support Vector Machine (SVM). Data komentar diambil dari platform media sosial dan melalui tahapan preprocessing seperti case folding, tokenization, stopword removal, stemming, dan ekstraksi fitur menggunakan TF-IDF. Model SVM diterapkan untuk mengklasifikasikan komentar ke dalam kategori positif, negatif, dan netral. Berdasarkan hasil evaluasi, algoritma SVM menunjukkan tingkat akurasi sebesar 92%, yang menandakan efektivitasnya dalam mengidentifikasi sentimen publik. Penelitian ini diharapkan dapat berkontribusi pada pengembangan metode analisis sentimen serta meningkatkan pemahaman terhadap persepsi masyarakat mengenai kinerja pemerintahan.
EVALUASI KINERJA ALGORITMA SUPPORT VECTOR MACHINE (SVM) UNTUK ANALISIS SENTIMEN KOMENTAR PUBLIK TERHADAP PEMERINTAHAN PRESIDEN PRABOWO ARPAN, ATIKA; Sylvia, Sylvia; Permata, Rizka
Jurnal Teknologi Informasi Mura Vol 18 No 1 (2026): Jurnal Teknologi Informasi Mura
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v18i1.2864

Abstract

Penelitian ini bertujuan untuk menganalisis sentimen komentar publik terhadap pemerintahan Presiden Prabowo menggunakan algoritma Support Vector Machine (SVM). Data komentar diambil dari platform media sosial dan melalui tahapan preprocessing seperti case folding, tokenization, stopword removal, stemming, dan ekstraksi fitur menggunakan TF-IDF. Model SVM diterapkan untuk mengklasifikasikan komentar ke dalam kategori positif, negatif, dan netral. Berdasarkan hasil evaluasi, algoritma SVM menunjukkan tingkat akurasi sebesar 92%, yang menandakan efektivitasnya dalam mengidentifikasi sentimen publik. Penelitian ini diharapkan dapat berkontribusi pada pengembangan metode analisis sentimen serta meningkatkan pemahaman terhadap persepsi masyarakat mengenai kinerja pemerintahan.
Transformasi pembelajaran di PAUD Arjuna melalui inovasi pendidikan Puspitasari, Maya; Juhana, Juhana; Ardiasih, Lidwina Sri; Sylvia, Sylvia; Putri, Mylanita Widya; Adhania, Rifa Fajri
Community Empowerment Journal Vol. 4 No. 1 (2026)
Publisher : CV. Yudhistt Fateeh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61251/cej.v4i1.322

Abstract

Program Pengabdian kepada Masyarakat (PkM) di PAUD Arjuna dilaksanakan dengan tujuan meningkatkan kapasitas guru dan memperkuat inovasi pembelajaran melalui pemanfaatan media edukatif berbasis teknologi serta pengembangan kreativitas anak. Kegiatan PkM ini melibatkan tim dosen Universitas Terbuka (UT) bersama mitra, yaitu kepala sekolah, guru, dan siswa PAUD, dalam rangka mendorong implementasi praktik pembelajaran yang interaktif dan menyenangkan. Selama pelaksanaan, tim PkM memberikan pendampingan berupa pelatihan serta penyediaan media ajar inovatif yang sesuai dengan kebutuhan anak usia dini. Hasil kegiatan menunjukkan adanya peningkatan pemahaman guru terhadap strategi pembelajaran kreatif, motivasi siswa dalam mengikuti kegiatan, serta kesadaran lembaga untuk terus berinovasi. Penutupan kegiatan ditandai dengan sesi foto bersama tim PkM, kepala sekolah, guru, dan siswa sebagai simbol kebersamaan dan keberlanjutan program. Secara keseluruhan, PkM ini menjadi motivasi penting bagi PAUD Arjuna untuk memperkuat kualitas lembaga, mengembangkan pembelajaran berbasis inovasi, serta meningkatkan peran aktif dalam mendukung perkembangan anak usia dini. The Community Service Program (PkM) at PAUD Arjuna in Tangerang Selatan aimed to enhance teacher competencies and foster innovative learning by integrating technology-based educational media. This strategy was designed to facilitate children's creative development. Educators from Universitas Terbuka collaborated with the principal, teachers, and students of PAUD Arjuna. The program's primary activities consisted of training and mentoring on the application of innovative teaching media specifically designed for early childhood education. The outcomes included increased understanding of creative learning strategies among educators, higher student engagement in classroom activities, and improved institutional recognition of the need for ongoing innovation. The knowledge management initiative enhanced learning quality at PAUD Arjuna and promoted the adoption of sustainable, innovation-oriented practices in early childhood education.
PEMBUATAN VIDEO PEMBELAJARAN DESTINASI PARIWISATA DENGAN MENGGUNAKAN MODEL ADDIE Fitriyah, Fitriyah; Kartika, Ni Made Ayu Windu; Meidasari, Reski; Sari, Desmala; Sylvia, Sylvia
LEARNING : Jurnal Inovasi Penelitian Pendidikan dan Pembelajaran Vol. 6 No. 2 (2026)
Publisher : Pusat Pengembangan Pendidikan dan Penelitian Indonesia (P4I)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51878/learning.v6i2.9699

Abstract

The background of this research is based on the importance of innovative learning media to overcome student boredom due to monotonous material in the Tourism Destination course at the Lampung State Polytechnic. The focus of the problem is the design of interactive learning videos to improve understanding and learning motivation. This research uses the Research and Development (R&D) method through the ADDIE model which includes the stages of analysis, design, development, implementation, and evaluation. The quantitative validation results show that the media is categorized as very feasible with a percentage of assessments from media experts of 86.9% and material experts reaching 88%. The implementation stage in the classroom proved a significant increase in student learning outcomes, as seen from the comparison of pre-test and post-test scores that showed progress after the use of the video. Through a systematic process, technical obstacles such as audio noise and software limitations were successfully overcome to produce an educational product. The main conclusion of the study confirms that creating learning videos with the ADDIE model effectively transforms the delivery of theoretical material to be more interactive and adaptive to technological developments. This media not only facilitates various student learning styles but also becomes a strategic solution in enriching digital teaching materials in the tourism sector. Thus, the integration of technology in the higher education curriculum can provide a real contribution to the achievement of students' academic achievements in a sustainable and professional manner in the future. ABSTRAK Latar belakang penelitian ini didasarkan pada pentingnya media pembelajaran inovatif untuk mengatasi kejenuhan mahasiswa akibat materi yang monoton pada mata kuliah Destinasi Pariwisata di Politeknik Negeri Lampung. Fokus masalah adalah perancangan video pembelajaran interaktif guna meningkatkan pemahaman dan motivasi belajar. Penelitian ini menggunakan metode Research and Development (R&D) melalui model ADDIE yang mencakup tahapan analisis, desain, pengembangan, implementasi, serta evaluasi. Hasil validasi secara kuantitatif menunjukkan bahwa media tersebut dikategorikan sangat layak dengan persentase penilaian dari ahli media sebesar 86,9% dan ahli materi mencapai 88%. Tahap implementasi di kelas membuktikan adanya peningkatan hasil belajar mahasiswa yang signifikan, terlihat dari perbandingan nilai pre-test dan post-test yang menunjukkan kemajuan setelah penggunaan video tersebut. Melalui proses sistematis, kendala teknis seperti kebisingan audio dan keterbatasan perangkat lunak berhasil diatasi demi menghasilkan produk yang edukatif. Simpulan utama penelitian menegaskan bahwa pembuatan video pembelajaran dengan model ADDIE efektif mentransformasi penyampaian materi teoritis menjadi lebih interaktif dan adaptif terhadap perkembangan teknologi. Media ini tidak hanya memfasilitasi berbagai gaya belajar mahasiswa tetapi juga menjadi solusi strategis dalam memperkaya bahan ajar digital di sektor pariwisata. Dengan demikian, integrasi teknologi dalam kurikulum pendidikan tinggi mampu memberikan kontribusi nyata bagi pencapaian prestasi akademik mahasiswa secara berkelanjutan dan profesional di masa depan nanti.  
PENINGKATAN KOMPETENSI GURU BAHASA INGGRIS SMP DI KABUPATEN BOGOR MELALUI PELATIHAN PENGEMBANGAN VIDEO PEMBELAJARAN BERBASIS ANIMAKER sylvia, sylvia; Bachtiar, Bachtiar; Zuhairi, Aminuddin; Puspitasari, Maya; Gardina, Inggit
Jurnal Abdi Insani Vol 13 No 1 (2026): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v13i1.3354

Abstract

In the era of digital transformation, teachers are expected to integrate technology into classroom practices to enhance students’ engagement and 21st-century skills. Within the framework of the Merdeka Belajar curriculum, technology-enhanced learning plays a vital role in fostering creativity, collaboration, communication, critical thinking, and character development. However, many English teachers still face challenges in utilizing digital tools effectively due to limited technological competence and pedagogical readiness. This community service (Pengabdian kepada Masyarakat or PkM) program was designed to strengthen the digital and pedagogical capacities of junior high school English teachers in Bogor Regency through training on the development of deep learning–based instructional videos using the Animaker platform. The activity was conducted on September 26, 2025, and involved 36 teachers who are members of the Musyawarah Guru Mata Pelajaran (MGMP) English Teachers Association. The program adopted a four-stage model consisting of observation, socialization, training and mentoring, and evaluation. Data were collected through observation, participant feedback, and reflective discussions. The findings indicate that the program significantly improved teachers’ understanding and skills in designing and producing animation-based instructional videos. Teachers demonstrated greater creativity, confidence, and motivation in integrating technology into their English lessons. Moreover, the training fostered collaborative learning, reflective practice, and professional growth among participants. This program highlights the importance of ongoing professional development and institutional support in equipping teachers with digital pedagogical competencies to meet the demands of modern education.
Co-Authors Abdul Haeba Ramli Adhania, Rifa Fajri Adnan Aqsya, Mohammad Albitar Septian Syarifudin Ardiasih, Lidwina Sri Ariawan Gunadi Arifin, Oki Arpan, Atika Atika Arpan Azlan Azhari Bachtiar Bachtiar Cahyani, Mutiara Casta, Ramadhani Eria Cecilia, Cecilia Christian, Natalis Christiana, Petrycia Christiani, Agustina Dara Ayu Nianty Delima Rahayu Istiqomah, Delima Rahayu Derista, Fanny Dharmawan, C.N. Djangkaru, Elliana DM., Rustan Dwi Handoko Dwirgo Sahlinal Dwirgo Sahlinal, Dwirgo Egnes, Egnes Fathurrahman Kurniawan Ikhsan Febrianus, Justin Fitriani, Hema Fitriyah Fitriyah Frederica, Viona Gaora, Putra Ansa Gardina, Inggit Ghanesya Hari Murti Gunawan, Andrew Riccardo Harmiati Harnis, Zola Efa Hendri Purnomo Herman, Erry Irene Irene Iskandar Itan, Iskandar Ismayanti, Galuh Jennifer Jennifer Jony Jony Juhana, Juhana Kartika, Ni Made Ayu Windu Kyoko, Kyoko Laurence Laurence Lila Maria Kaban Limiyana, Fanny Linda Santioso magfiroh, diana Maryadi Maryadi Mas’ud, Masdar Maya Puspitasari, Maya Meidasari, Reski Meiviana, Meiviana Mercyo, Steve Monica , Christiana Gracia Muh. Said, Muh. Mulyawan, Heru Dwi Nurkhotimah, Jihan Susan Ofel Boas , William Pedrason, Rodon Permata, Rizka Pratiwi, Yessi Anissa Puspitasari, Kristanti Ambar Putri, Mylanita Widya Rahayu, Priskila Christine Rifin Khong Rima Maulini Romanda, Novandro Sari, Desmala Sendi Ramdhani Setiarini, Rimbi Budi Silalahi, Rudy Solly Aryza Sri Dewi Nirmala sri wuryastuti Suhardi, Steven Suhardjo, Iwan Suharsono, Degita Danur Sukmawati, Shintya Alvira Suratno, Tatang Surayya, St. Ayu Topuh, Jelpris Viona viona, Viona Wahyurianto, Ibnu Wibowo, Yusep Windhu Ari Wicaksono, Julien Arief Widya Rizky Pratiwi, Widya Rizky Widyawati, Dewi Kania Zuhaira, Salsabila Zuhairi, Aminuddin Zuriati, Zuriati