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All Journal Dinamik JURNAL INSTEK (Informatika Sains dan Teknologi) Innovation in Research of Informatics (INNOVATICS) Jurnal Teknik Informatika (JUTIF) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Jurnal Pendidikan dan Pembelajaran Indonesia (JPPI) Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Journal of Information System Exploration and Research
Nuk Ghurroh Setyoningrum
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Pengaruh Pelatihan STEAM Menggunakan Assemblr Edu terhadap Peningkatan Kompetensi Guru Sekolah Dasar di Tasikmalaya Nurwendah, Anisa Solehah; Setyoningrum, Nuk Ghurroh; Febriani, N. Nelis; Khozizah, Putri
Jurnal Pendidikan dan Pembelajaran Indonesia (JPPI) Vol. 6 No. 1 (2026): Jurnal Pendidikan dan Pembelajaran Indonesia (JPPI), 2026 (1)
Publisher : Yayasan Pendidikan Bima Berilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53299/jppi.v6i1.3356

Abstract

Penelitian ini bertujuan untuk mengkaji pengaruh pelatihan STEAM yang memanfaatkan platform Assemblr Edu terhadap peningkatan kompetensi guru Sekolah Dasar. Penelitian ini dilatarbelakangi oleh perlunya penguatan kemampuan pedagogis dan digital guru dalam merancang pembelajaran yang inovatif dan kontekstual. Metode penelitian menggunakan desain kuasi-eksperimen dengan model one-group pretest–posttest. Subjek penelitian meliputi 30 guru Sekolah Dasar di Kota Tasikmalaya yang dipilih menggunakan teknik purposive sampling berdasarkan kriteria tertentu, yaitu guru yang aktif mengajar dan bersedia mengikuti seluruh rangkaian pelatihan. Prosedur penelitian mencakup pelaksanaan pretest, pelatihan STEAM berbasis Assemblr Edu, observasi keterampilan mengajar, pengisian angket literasi digital, dan pemberian posttest. Analisis data dilakukan melalui statistik deskriptif, uji normalitas Shapiro–Wilk, uji paired sample t-test, serta perhitungan N-Gain. Hasil penelitian menunjukkan adanya peningkatan kompetensi guru yang signifikan, dibuktikan melalui hasil paired sample t-test (sig. = 0.000) dan nilai rata-rata N-Gain sebesar 0.73 yang termasuk kategori tinggi. Observasi kinerja mengindikasikan bahwa guru mampu mengembangkan proyek berbasis AR dengan kualitas sangat baik, serta memperoleh skor literasi digital yang tinggi. Temuan ini menegaskan bahwa pelatihan STEAM dengan dukungan teknologi augmented reality melalui Assemblr Edu dapat memperkuat pemahaman konseptual, kemampuan perancangan proyek, dan keterampilan pedagogis guru. Dengan demikian, pelatihan STEAM yang memanfaatkan Assemblr Edu berpengaruh positif terhadap peningkatan kompetensi guru Sekolah Dasar.
Analysis and Visualization of Purchasing Pattern in Retail Product Transaction using Apriori Algorithm Febriani SM, N. Nelis; Setyoningrum, Nuk Ghurroh; Lodana, Mae; Pertiwi, Dwika Ananda Agustina; Muslim, Much Aziz
Journal of Information System Exploration and Research Vol. 4 No. 1 (2026): January 2026
Publisher : shmpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joiser.v4i1.650

Abstract

The rapid growth of the retail industry generates large volumes of transaction data that can be analyzed to support data-driven business decision making. This study aims to analyze and visualize purchasing patterns in retail product transactions by applying data mining techniques using the Apriori algorithm and business intelligence visualization through Microsoft Power BI. The dataset consists of 1 million retail transactions collected from an open retail transaction repository. The research stages include data collection, transaction data preprocessing, implementation of the Apriori algorithm with a minimum support threshold of 0.002 and a minimum confidence of 0.5, and visualization of the analysis results through interactive dashboards using Power BI and a Python-based application developed with the Streamlit framework. The results indicate that the Apriori algorithm successfully identifies frequent product associations and generates 12 association rules that meet the criteria of strong association rules. Power BI visualizations provide comprehensive insights into transaction trends based on customer categories, store types, payment methods, seasons, and transaction regions. These findings are expected to assist retail companies in formulating marketing strategies, developing product recommendations, and optimizing inventory management in a more effective and data-driven manner. This study contributes by integrating large-scale association rule mining with interactive business intelligence visualization for retail decision support.
Co-Authors Agung Prihandono ALAM Anisa Solehah Nurwendah Damayanti, Dea Dewi Drajat, Hilmi Maulana Ema Utami Fauzan Natsir Ferry Wahyu Wibowo Hari Murti KAPI, CECEP M. Kholiq Mochamad Ramdan Khozizah, Putri Kusrini, Kusrini Lodana, Mae Lodana, Mae B Maududy, Robby Much Aziz Muslim Mulyani, Fithri Sri Mustofa, Pramesti Melyna N. Nelis Febriani SM Nurdin, Arif Muhamad Nursamsi , Dede Rizal Nursamsi, Dede Rizal Pepi Alpiani Pertiwi, Dwika Ananda Agustina Praseptiawan, Mugi Putri Khozizah Rahmawati, Hilmi Sudiarjo, Aso