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Meningkatkan Prestasi OSN Matematika Melalui Kolaborasi Guru dan Siswa di Kabupaten Malang Solimun; Meilina Retno Hapsari; Mudjiono; Evellin Dewi Lusiana; Kamelia Hidayat; Celia Sianipar; Septi Nafisa Ulluya Zahra
Jurnal Pengabdian Pendidikan Masyarakat (JPPM) Vol 7 No 1 (2026): Jurnal Pengabdian Pendidikan Masyarakat (JPPM) Vol.7 No 1 (Maret 2026)
Publisher : LPPM UNIVERSITAS MUHAMMADIYAH MUARA BUNGO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/jppm.v7.i1.3956

Abstract

This community service program aims to improve achievement in the National Science Olympiad (OSN) Mathematics through collaborative engagement between teachers and students in Malang Regency. The primary challenges identified include the lack of structured training programs, limited intensive mentoring by teachers, and insufficient competition simulations, which negatively affect students’ academic preparedness and psychological readiness. To address these issues, the program was implemented using integrated methods, including teacher workshops, intensive classes for students, collaborative discussion forums, competition simulations, and evaluation and monitoring based on statistical testing. The implementation emphasized strengthening teachers’ roles as active mentors while empowering students through targeted exercises aligned with authentic OSN competition contexts. Teachers were trained to design innovative mentoring strategies, develop problem-solving frameworks, and provide systematic feedback. Meanwhile, students participated in intensive training sessions and simulated competitions to enhance conceptual understanding and resilience under competitive pressure. The results demonstrate improved teacher competencies in developing effective coaching strategies, as well as increased readiness among junior and senior high school students in solving complex mathematical problems and managing competition-related stress. Beyond individual skill enhancement, the program fostered a collaborative, participatory, and sustainable learning ecosystem. Furthermore, this initiative contributes to improving mathematics education quality in Malang Regency by offering a structured coaching model that can be replicated in other schools and regions.
Modified Multigroup Ramsey RESET for Specification Detection in Semiparametric Path Models M. Dziqri nur Rohiim; Adji Achmad Rinaldo Fernandes; Achmad Efendi; Mujiono Mujiono; Kamelia Hidayat
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 2 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i2.43782

Abstract

This study develops a modified multigroup Ramsey RESET (Regression Equation Specification Error Test) within a semiparametric multigroup path model, a statistical framework that combines parametric and nonparametric approaches across multiple groups. Developed using dummy-variable interactions, the method identifies both linear and truncated spline relationships and enables analysis of all groups within a single integrated model, eliminating the need for separate group tests. Simulation studies using empirical data on students’ AI literacy applied combinations of linear and truncated-spline relationship patterns. The method was evaluated using the p-value, Correct-to-Incorrect p-value Ratio, Dominance Ratio, and Accuracy. The results indicate that the modified multigroup Ramsey RESET generally produces larger p-values for models that match the underlying data-generating mechanism than for competing alternative models, demonstrating good discriminatory power in identifying appropriate model specifications. The empirical application further reveals that several relationships among variables exhibit truncated spline patterns rather than purely linear forms. Thus, the proposed method provides an alternative specification test for simultaneously identifying linear and nonlinear relationships within multigroup semiparametric path models.