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Research and Developing Mathematics Knowledge Child Development Perspectives, 2022 Torang Siregar; Ahmad Arisman; Iskandarsyah; Risky Ardian; Awal ````Harahap
International Journal of Applied Research and Sustainable Sciences Vol. 1 No. 1 (2023): September 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijarss.v1i1.318

Abstract

Proficiency in mathematics is critical to success academically, economically, and in life. Greater success in math is related to entering and completing college, earning more in adulthood, and making more optimal decisions concerning health. Knowledge of math begins to develop at a young age, and this early knowledge matters: Knowledge of math at or before school entry predicts outcomes in math and reading across primary and secondary school. More than one children struggle to learn math. For example, only 60% of fourth-grade and 55% of eighth-grade students in the United States performed at or above proficiency in math on the 2020 National Assessment of Educational Progress, and proficiency rates were even lower for African-American and Hispanic children and for children from low-income homes. More than one students do not master challenging math content. Developing strong knowledge about mathematics is important for success academically, economically, and in life, but more than one children fail to become proficient in math. Research on the developmental relations between conceptual and procedural knowledge of math provides insights into the development of knowledge about math. First, competency in math requires children to develop conceptual knowledge, procedural knowledge, and procedural flexibility. Second, conceptual and procedural knowledge often develop in a bidirectional, iterative fashion, with improvements in one type of knowledge supporting improvements in the other, as well as procedural flexibility. Third, learning techniques such as comparing, explaining, and exploring promote more than one type of knowledge about math, indicating that each is an important learning process. Researchers need to develop and validate measurement tools, devise more comprehensive theories of math development, and bridge more between research and educational practice.
What Makes it Special? : Content Knowledge for Teaching Torang Siregar; Awal Harahap; Ahmad Arisman; Hariman Hasayangan Rangkuti; Iskandarsyah; Indra Saputra Harahap; Risky Ardian; Sulhan Daulay; Zainuddin Batubara
International Journal of Applied Educational Research (IJAER) Vol. 1 No. 1 (2023): October 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijaer.v1i1.405

Abstract

This article reports the authors’ efforts to develop a practice-based theory of content knowledge for teaching built on Shulman’s (1986) notion of pedagogical content knowledge. As the concept of pedagogical content knowledge caught on, it was in need of theoretical development, analytic clarification, and empirical testing. The purpose of the study was to investigate the nature of professionally oriented subject matter knowledge in mathematics by studying actual mathematics teaching and identifying math ematical knowledge for teaching based on analyses of the mathematical problems that arise in teaching. In conjunction, mea sures of mathematical knowledge for teaching were developed. These lines of research indicate at least two empirically discernable subdomains within pedagogical content knowledge (knowledge of content and students and knowledge of content and teaching) and an important subdomain of “pure” content knowledge unique to the work of teaching, specialized content knowledge, which is distinct from the common content knowledge needed by teachers and nonteachers alike. The article con cludes with a discussion of the next steps needed to develop a useful theory of content knowledge for teaching.
STUDI KASUS SMA N 1 SINUNUKAN : IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR UNTUK KLASIFIKASI PENERIMA BEASISWA PROGRAM INDONESIA PINTAR (PIP) Torang Siregar; Riski Ardian; Ahmad Arisman; Iskandarsyah
Jurnal Cermatika Vol. 4 No. 1 (2024): VOLUME 4 NOMOR 1 BULAN APRIL TAHUN 2024
Publisher : Program Studi Matematika Universitas Graha Nusantara Padangsidimpuan

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

Abstract

Abstrak Program Indonesia Pintar (PIP) merupakan salah satu kebijakan pemerintah yang diharapkan dapat meningkatkan aksesibilitas dan pemerataan pendidikan di Indonesia, namun dalam pelaksanaannya pemberian beasiswa dari program ini masih dijumpai banyak kasus yang kurang tepat sasaran. Salah satu permasalahannya adalah masih ditemukan siswa penerima bantuan pendidikan yang berasal dari keluarga yang mampu, sedangkan siswa yang kurang mampu justru tidak mendapatkan bantuan. Sehingga diperlukan suatu sistem klasifikasi berbasis web yang dapat mengklasifikasikan siswa layak atau tidak untuk mendapatkan PIP. Penelitian ini mengimplementasikan algoritma -nearest neighbor untuk mengklasifikasikan siswa penerima beasiswa PIP. Penelitian ini menggunakan data siswa/i SMAN 1 Sinunukan, Mandailing Natal yang didapat melalui penyebaran angket sesuai dengan kriteria yang telah ditentukan. Data yang telah diperoleh kemudian dilakukan preprocessing data dengan menggunakan Label Encoder dan Normalisasi Min-Max. Data dibagi menjadi dua jenis yaitu data training dan data testing. -fold cross validation digunakan untuk menentukan nilai yang optimal. Hasil penelitian ini memperlihatkan tingkat akurasi yang dihasilkan berdasarkan hasil pengujian yang dilakukan untuk implentasi algoritma -nearest neighbor dalam klasifikasi kelayakan penerima beasiswa PIP yaitu sebesar 70% dengan nilai .