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STATISTICAL LITERACY IN PRIMARY SCHOOL MATHEMATICS CURRICULA: HISTORICAL REVIEW AND DEVELOPMENT Ezra Putranda Setiawan
Jurnal Pendidikan dan Kebudayaan Vol. 6 No. 1 (2021)
Publisher : Badan Standar, Kurikulum, dan Asesmen Pendidikan, Kemendikdasmen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24832/jpnk.v6i1.1915

Abstract

Literasi statistika merupakan kemampuan penting untuk menghadapi revolusi industri 4.0. Penelitian ini mengumpulkan informasi sejauh mana kemampuan literasi statistika didukung oleh kurikulum matematika untuk Sekolah Dasar di Indonesia. Studi dokumentasi dilakukan pada beberapa naskah kurikulum, yakni Kurikulum Berbasis Kompetensi 2004, Kurikulum Tingkat Satuan Pendidikan 2006, Kurikulum 2013, serta revisi Kurikulum 2013 (2016, 2018, dan 2020). Sebagai pembanding, dianalisis pula Cambridge Primary Mathematics Curriculum dan kurikulum 1975. Hasil penelitian menunjukkan bahwa perhitungan statistik deskriptif dan pembuatan diagram dijumpai pada semua kurikulum matematika SD tahun 2004 hingga 2020. Pada kurikulum 2013 dan sesudahnya, dijumpai pula kompetensi terkait pengumpulan data dan interpretasi data. Adapun kompetensi terkait peluang hanya dijumpai pada kurikulum 2013, Cambridge, dan kurikulum 1975. Masih diperlukan pengembangan kurikulum pada kompetensi proses pemecahan masalah statistika serta pendalaman terkait penggunaan statistik deskriptif dan diagram secara tepat. Statistical literacy is an essential competence to face the 4.0 industrial revolution. This study aims to collect information on how statistical literacy skills accounted in the Indonesian primary school mathematics curriculum. We study several curriculum documents' that had been used in Indonesia, namely the 2004 Competency-Based Curriculum, the 2006 Education Unit Level Curriculum, the 2013 Curriculum, and the revised 2013 Curriculum (2016, 2018, and 2020). We also analyzed the Cambridge Primary Mathematics Curriculum and the 1975 Indonesian curriculum. We find that calculation of descriptive statistics and chart making appeared on all Indonesian primary school mathematics curricula. The 2013 curriculum and its successor also contains some competencies related to data collection and interpretation. Probability-related competence is found only on the 2013 curriculum, the 1975 curriculum, and the Cambridge Curriculum. Further curriculum development should be focused on the statistical problem-solving competence and appropriate use of descriptive statistics and charts.
Workshop on Comparative analysis of k populations with Non Parametric for Research in Social Sciences and Education Rosita Kusumawati; Dhoriva Urwatul Wutsqa; Kismiantini Kismiantini; Syarifah Inayati; Muhammad Fauzan; Ezra Putranda Setiawan; Bayutama Isnaini
Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Vol 6, No 2 (2022): Vol 6, No 2 (2022)
Publisher : Yogyakarta State University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpmmp.v6i2.46055

Abstract

Data obtained from social science and education research is often in the form of categorical data, namely nominal or ordinal. This makes the parametric approach less appropriate for use in some social science and education data. One solution is to use a nonparametric approach. This underlies the holding of community service activities in a workshop on comparison analysis of k population with a nonparametric approach for social science research and education. Participants in this workshop consisted of academics and practitioners, and students from various study programs in Indonesia. The workshop was carried out by providing material and demonstrating using R software as an analytical tool, which was held online for two days. On the first day, the material presented was a nonparametric approach to the comparison of k independent populations along with a demonstration of using R software, while for k dependent populations along with a demonstration of using R software was given on the second day. Participants were given data on social sciences and education in providing materials and demos of the R software. Based on the results of questionnaires, observations, and questions and answers, participants seemed enthusiastic in participating in the R software's material and demo sessions. In addition, participants can perform various tests in a nonparametric approach for k independent and dependent populations using the R software. Participants can also provide an accurate interpretation of the output of the R software.
Pengembangan Filter Mikroplastik Terinspirasi Dari Cara Hidup Paus Biru (Balaenoptera Musculus) Raisah Kirana Candra; Arif Kurniawan; Ezra Putranda Setiawan; Ridwan Wicaksono; Khakam Ma’ruf
Jurnal Adijaya Multidisplin Vol 3 No 01 (2025): Jurnal Adijaya Multidisiplin (JAM)
Publisher : PT Naureen Digital Education

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

Abstract

Air adalah bagian penting dalam kehidupan manusia, begitu juga dengan perairan. Tetapi seiring bertambahnya penduduk, sampah yang mencemari perairan semakin meningkat, terutama sampah plastik yang sulit terurai. Dalam proses degradasi, plastik menjadi potongan kecil yang disebut mikroplastik. Potongan ini berukuran kurang dari 5 mm dan tersebar dalam perairan. Pencemaran mikroplastik tentu berbahaya bagi kehidupan organisme di sekitarnya. Dari permasalahan tersebut, penelitian ini bertujuan untuk mengembangkan filter mikroplastik dengan metode rapid sand filtration dan granular activated carbon dengan desain yang menyerupai struktur tubuh paus biru. Filter diujikan pada air Sungai Code, Sungai Winongo, Sungai Gajahwong, dan Sungai Manunggal. Hasil penelitian menunjukkan bahwa persentase tertinggi penurunan konsentrasi mikroplastik pada filter sebesar 88,5% dan persentase rata rata 75,4% untuk filtrasi dengan pembilasan dan 71,7% untuk filtrasi tanpa pembilasan. Filter memiliki debit filtrasi rata rata sebesar 6x103 m3/s. Hasil penelitian dan pengembangan pada filter cukup efektif untuk diimplementasikan ke sungai yang tercemar.