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All Journal DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
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Digital Marketing Sebagai Strategi Meningkatkan Jumlah Konsumen UMKM Putra Salman di Kabupaten Magelang Dimas Sasongko; Agung; Gandhi; Arif Aryawan; Bagus; Alwan
DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Vol 5 No 1 (2021)
Publisher : Politeknik Negeri Madiun

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Digital Marketing adalah kegiatan promosi dan pencarian pasar melalui media digital secara online dengan memanfaatkan berbagai sarana misalnya jejaring sosial. Digital Marketing sangat diperlukan guna meningkatkan banyak sektor mulai dari micro hingga macro. Kendala yang dialami dari usaha UMKM Putra Salman antara lain kesulitan mengemas produk dalam menarik dan belum memanfaatkan Teknologi Informasi dalam promosi produk. Tujuan dari kegiatan ini adalah memberikan pelatihan dan pendampingan kepada UMKM Putra Salman tentang implementasi Digital Marketing untuk meningkatkan jumlah konsumen. Kegiatan Pengabdian kepada Masyarakat ini dilaksanakan dalam waktu 3 (tiga) bulan terbagi dalam lima tahap yaitu: (1) tahap sosialisasi, (2) tahap pelatihan, (3) tahap pendampingan, (4) tahap monitoring evaluasi, dan (5) pelaporan. Hasil dari Pengabdian Kepada Masyarakat adalah UMKM Putra Salman memiliki sosial media Instagram dan Facebook, selain itu pemilik UMKM Putra Salman memiliki kemmapuan mengelola media sosial dan memiliki pengetahuan tambahan tentang Digital Marketing.
Kategorisasi dan Visualisasi Semantik-Topik Berbasis LLM pada Refleksi Guru Koding Kecerdasan Artifisial Tubagus Mohammad Akhriza; bagus; Meivi Kartikasari; Syntia Widyayuningtias Putri Listio
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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The training program for Senior and Vocational High School teachers of the Coding and Artificial Intelligence (KKA) subject serves as a strategic effort to strengthen human resource capacity in response to digital transformation. Teachers are expected to understand the KKA learning outcomes and be able to design and implement technology-based learning in their respective schools. This study employs a Large Language Model (LLM)-based categorization technique to analyse the reflective content of SMA/SMK teachers in Malang City after attending the KKA training, aiming to identify their learning achievement levels and how they interpret their learning experiences. The dataset, consisting of presentation files in PDF and PPTX formats, was text-extracted, processed by the LLM, categorized into ten main themes in JSON format, and visualized as a mind map using Mermaid scripts. The findings demonstrate that the LLM effectively performs consistent semantic categorization on unstructured reflective data and produces visual representations that facilitate the interpretation of learning achievements. Content analysis of teacher reflections reveals strong motivation to enhance digital and pedagogical competencies, successful implementation of project-based learning, and emerging challenges related to student scepticism toward AI adoption in art and design education. Furthermore, the comparison between a general-purpose LLM (GPT-OSS) and coder-type LLMs (such as GLM-4.6:Coder and Qwen3-Coder) indicates comparable accuracy in generating JSON structures and Mermaid scripts. However, the non-coder LLM exhibits greater stability in maintaining contextual coherence and processing speed. These findings highlight the potential of LLMs in analysing reflective educational data and underscore the need for pedagogical adaptation and continued digital competence development among teachers toward AI-driven educational independence.
Co-Authors Agung Alwan Arif Aryawan Dimas Sasongko Gandhi Meivi Kartikasari Syntia Widyayuningtias Putri Listio Tubagus Mohammad Akhriza