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Eksplorasi Etnomatematika Geometri pada Arsitektur dan Lingkungan Pantai Sejarah Kabupaten Batubara: Pendekatan Deskriptif Kualitatif Sisca Sri Dewi Saragih; Khofifa Romaito Siregar; Hokkop Efendi Hasibuan; Nayla Aiwina Putri
Media Pendidikan Matematika Vol. 13 No. 2 (2025): J-MPM
Publisher : Program Studi Pendidikan Matematika, FSTT, Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/mpm.v13i2.18355

Abstract

Ethnomathematics is an approach that examines the relationship between mathematics and cultural practices in everyday life. Natural environments and traditional architectural structures contain rich forms and patterns that can be analyzed through mathematical concepts, particularly geometry. This study aims to explore the representation of geometric concepts found in the architectural structures and natural surroundings of Pantai Sejarah Batubara. A descriptive qualitative approach was employed, using observations, documentation, and informal interviews with local communities and site managers as data collection techniques. The findings reveal the presence of various geometric forms such as rectangles, squares, triangles, circles, cubes, blocks, prisms, and natural spirals in gazebos, entrance gates, wave breakers, ocean wave patterns, and mollusk shells. These results indicate that Pantai Sejarah Batubara holds significant potential as a contextual learning resource for geometry through an ethnomathematical perspective. This study contributes to the development of culturally grounded and environmentally based mathematics learning.
PENGEMBANGAN MEDIA PEMBELAJARAN MATEMATIKA ADAPTIF BERBASIS MACHINE LEARNING UNTUK MENINGKATKAN HASIL BELAJAR SISWA Mustika Fitri Larasati Sibuea; Muhammad Ardiansyah Sembiring; Hokkop Efendi Hasibuan
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6801

Abstract

Abstract: This study aims to develop an adaptive mathematics learning media based on machine learning and to examine its feasibility and effectiveness in improving student learning outcomes. The media was developed using the 4D research and development model (define, design, develop, disseminate). A Random Forest algorithm was employed to classify students' ability into three categories (low, medium, high) based on their exercise history, allowing the media to automatically adjust the difficulty level of the exercises. The trial subjects were eighth-grade junior high school students of Tamansiswa Sukadamai. Data were collected through a needs analysis questionnaire, expert validation sheets, a System Usability Scale (SUS) questionnaire, and pretest-posttest learning outcome tests. The results indicate that the media is feasible, practical, and effective in improving student learning outcomes, and that the developed model shows good classification accuracy. Keywords: adaptive learning media, machine learning, learning outcomes, mathematics, Random Forest   Abstrak: Penelitian ini bertujuan untuk mengembangkan media pembelajaran matematika adaptif berbasis machine learning serta menguji kelayakan dan efektivitasnya dalam meningkatkan hasil belajar siswa. Media dikembangkan menggunakan model penelitian dan pengembangan 4D (define, design, develop, disseminate). Algoritma Random Forest digunakan untuk mengklasifikasikan kemampuan siswa ke dalam tiga kategori (rendah, sedang, tinggi) berdasarkan riwayat pengerjaan soal, sehingga media dapat menyesuaikan tingkat kesulitan latihan secara otomatis. Subjek uji coba penelitian adalah siswa kelas VIII SMP Tamansiswa Sukadamai. Data dikumpulkan melalui angket analisis kebutuhan, lembar validasi ahli, angket System Usability Scale (SUS), serta tes hasil belajar (pretest dan posttest). Hasil penelitian menunjukkan bahwa media dinyatakan layak, praktis, dan efektif meningkatkan hasil belajar siswa, serta model yang dikembangkan menunjukkan akurasi klasifikasi yang baik. Kata kunci: media pembelajaran adaptif, machine learning, hasil belajar, matematika, Random Forest