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All Journal J-PiMat : Jurnal Pendidikan Matematika QISTINA: Jurnal Multidisiplin Indonesia
Rani Rani
Universitas Tanjungpura
Religion Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing

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Agrarian Conflict in Urutsewu: Political Ecology Approach Adelia Salwa; Ashari Ashari; Henny Muldia; Hesti Wulandari; Mita Harniawati; Putri Meiensi; Rani Rani; Rohyadi Andika Chandra; Seli Indriani; Jagad Aditya Dewantara
QISTINA: Jurnal Multidisiplin Indonesia Vol 2, No 1 (2023): June 2023
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/qistina.v2i1.575

Abstract

This book discusses the management of natural resources that are prone to conflict, such as the exploitation of mining materials. In this case, usually the parties involved involve several elements such as the community, local government, non-governmental organizations or environmental NGOs, and of course companies that will carry out mining. In this case, of course, to gain profit and the local government supports mining in order to increase regional income. However, in this case it is not in line with the community and environmental NGOs who refuse mining on the grounds that it disrupts the economic well-being of residents from their original livelihoods and ecological damage due to mining activities. This conflict has frequently occurred in Indonesia since 1999 and has spread to various regions, from Sumatra, Java, Kalimantan, Sulawesi, Nusa Tenggara to Papua. Gold mining in Papua by 2 Agrarian Conflicts in Urutsewu: Political Ecology Approach PT Freeport Indonesia, for example, is one of the causes of the prolonged conflict. The trigger for this conflict is not only about the welfare of local people who are being ignored by the government and PT Freeport Indonesia. Even deeper, the conflict is also rooted in environmental damage due to the dredging of Mount Ersberg's gold deposit.
Deep learning Berbasis Pesan Moral Meminimalisir Math Anxiety Mahasiswa pada Matakuliah Geometri Bistari Bistari; Rustam Rustam; Rani Rani; Dea Walhadiyah; Sari Mulyani
J-PiMat : Jurnal Pendidikan Matematika Vol 8, No 1 (2026): J-PiMat
Publisher : Prodi Pendidikan Matematika STKIP Persada Khatu;istiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/j-pimat.v8i1.6265

Abstract

Geometry learning does not only require cognitive ability but is also influenced by students’ Math Anxiety. The integration of deep learning based on moral messages as a learning strategy that combines cognitive, affective, and character aspects is still rarely explored and has the potential to become a novelty in minimizing mathematics anxiety. This study involved 32 students of the Mathematics Education Study Program, FKIP Untan, using the Design and Development Research (DDR) method simplified into the stages of needs analysis, design, development, and limited trials. The study aimed to develop and test a deep learning model based on moral messages to minimize students’ Math Anxiety through Paired Sample T-test and SEM-PLS analysis. The results showed that deep learning based on moral messages was effective in minimizing students’ Math Anxiety through strengthening emotional regulation and creating a safe learning environment. After the treatment, students’ anxiety was no longer general in nature, but became milder, situational, and more focused on cognitive aspects, enabling students to better control their emotions and understand geometry concepts. Furthermore, this approach contributed 61.6% to changes in students’ conditions by reducing social anxiety, increasing academic courage, and fostering more positive learning engagement. These findings are important because they indicate that mathematics learning based on deep learning and moral messages can improve conceptual understanding while also enhancing students’ psychological conditions, making learning more humanistic, safe, and supportive of students’ academic confidence in mathematics.Keywords: Deep learning; Math Anxiety; Moral Messages.
Co-Authors Adelia Salwa Ashari Ashari Bistari Dea Walhadiyah Dewantara, Jagad Aditya Henny Muldia Hesti Wulandari Mita Harniawati Putri Meiensi Rohyadi Andika Chandra Rustam Rustam Sari Mulyani Seli Indriani