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All Journal Indonesian Journal of Mathematics and Natural Sciences Journal of Innovation and Research in Primary Education
Sukestiyarno, Y L
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Education Languange, Linguistic, Communication & Media Mathematics Other

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Identifikasi Publikasi Dosen dalam Mewujudkan Internasionalisasi Universitas Negeri Semarang Menggunakan Neural Network Walid, Walid; Sukestiyarno, Y L; Sunarmi, Sunarmi
Indonesian Journal of Mathematics and Natural Sciences Vol 41, No 2 (2018): October 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini difokuskan pada penerapan Backpropagation Neural Network (BPNN) untuk melakukan identifikasi publikasi dosen dalam mewujudkan internasionalisasi UNNES dengan pengambilan datanya didasarkan pada penelurusuran hasil publikasi ilmiah dosen di SINTA dan didukung dengan kuesioner yang diberikan pada responden dosen di FMIPA UNNES. Selanjutnya hasil data yang ada dianalisis dengan menggunakan program Matlab dan didukung  dengan studi literatur terkait kajian NN. Studi simulasi dilakukan untuk mengetahui kondisi perkembangan hasil publikasi ilmiah dosen dengan menggunakan BPNN. Tujuan penelitian ini adalah untuk mengetahui hasil identifikasi publikasi dosen dalam mewujudkan internasionalisasi UNNES menggunakan BPNN. Berdasarkan hasil penelitian dan hasil pembahasan di bagian sebelumnya, maka disimpulkan bahwa Hasil pelatihan dan analisis numerik memberikan bahwa model terbaik BPNN pada algoritma pelatihan gradient descent dengan momentum dan adaptive learning rate diperoleh model BPNN terbaik dengan algoritma pelatihan gradient descent dengan momentum dan adaptive learning rate pada arsitektur jaringan 9-10-1 dengan momentum = 0,8 dan LR = 0,1 pada fungsi aktivasi tansig. Hasil identifikasi publikasi dosen menggunakan BPNN dan analisis terhadap pelatihan di atas diperoleh bahwa publikasi dosen dengan karya jurnal bereputasi internasional sebanyak 23,75%, untuk jurnal internasional sebanyak 21,23%, dan jurnal nasional terkareditasi sebesar 19,02% dan karya publikasi dalam prosiding internasional sebanyak 31,0%.This research is focused on the application of Backpropagation Neural Network (BPNN) to identify lecturer publications in realizing internationalization of UNNES with the retrieval of data based on the results of scientific publication of lecturers at SINTA and supported by questionnaires given to lecturer respondents at FMIPA UNNES. Furthermore, the results of the existing data were analyzed using the Matlab program and supported by literature studies related to the NN study. Simulation studies were conducted to determine the conditions for the development of the results of lecturers' scientific publications by using BPNN. The purpose of this study was to find out the results of the identification of lecturer publications in realizing the internationalization of UNNES using BPNN. Based on the results of the study and the results of the discussion in the previous section, it was concluded that the training results and numerical analysis provided that the best BPNN model on the momentum gradient descent training algorithm and adaptive learning rate obtained the best BPNN model with a gradient descent training algorithm with momentum and adaptive learning rate on network architecture 9-10-1 with momentum = 0.8 and LR = 0.1 on tansig activation function. The results of the identification of lecturer publications using BPNN and analysis of the training above obtained that lecturer publications with works of international reputation 23.75%, 21.23% for international journals, and 19.02% for national journals and 31.0% for publications in international proceedings.
Bridging Mathematics Literacy and Technology: A Self-Regulated Problem-Based Learning Approach Kusuma, Dani; Sukestiyarno, Y L
Journal of Innovation and Research in Primary Education Vol. 4 No. 4 (2025)
Publisher : Papanda Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56916/jirpe.v4i4.2437

Abstract

The mathematical literacy of Indonesian students is still low since mathematical literacy is one of the capacities that every individual must possess to be competitive in this era by being able to formulate, implement, and interpret mathematics in various contexts of life. This study aims to develop a learning model to improve students' mathematical literacy. The model developed is Self-Regulated Problem-Based Learning (SRPS). The type of research used is development research (RnD) using the Analysis, Design, Development, Implementation and Evaluation (ADDIE) model. The research subjects were 15-year-old 8th-grade junior high school students. The research findings show that the SRPS model of learning has a learning syntax that requires students to follow a systematic learning process. The applied learning syntax begins with problem presentation, analysis, planning, prioritizing, decision-making, discussion, and evaluation. The syntax of SRPS learning integrates problem-based learning and executive function, resulting in a sequence of learning processes that train students to understand problems, plan, make decisions, and evaluate the solutions they design. Learning syntax is integrated into the digital learning system to systematize learning processes and develop learning habits. The final achievement of the research shows that the development model produced meets the criteria of valid, effective, and practical.
Co-Authors Kusuma, Dani Sunarmi Sunarmi Walid Walid, Walid