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All Journal Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Journal of Humanities Education Management Accounting and Transportation
Mulyani, Ika Dini
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice Physics Social Sciences Transportation

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Memahami dan Menjelaskan Tentang Kesulitan Belajar, Definisi Kesulitan Belajar, Diagnosis Hingga Alternatif Pemecahan Masalahnya Hanifah, Ummu; Hidayah, Nailla; Diniyah, Cantika Alfa; Ismy, Nurul; Mulyani, Ika Dini; Panggabean, Hadi Saputra
Journal of Humanities Education Management Accounting and Transportation Vol 2, No 1 (2025): Februari 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/hemat.v2i1.5088

Abstract

Kesulitan belajar adalah masalah kompleks yang memengaruhi banyak siswa di berbagai tingkat pendidikan. Penelitian ini bertujuan untuk memahami dan menjelaskan definisi, penyebab, serta solusi alternatif untuk mengatasi kesulitan belajar dalam konteks pendidikan. Menggunakan metode penelitian pustaka, informasi dikumpulkan dari berbagai sumber literatur untuk menganalisis faktor-faktor yang berkontribusi terhadap kesulitan belajar, termasuk aspek biologis, lingkungan, psikologis, dan sosial. Hasil penelitian menunjukkan pentingnya diagnosis yang komprehensif dan penerapan intervensi yang holistik, serta dukungan dari orang tua dan guru dalam meningkatkan motivasi dan hasil belajar siswa. Meskipun penelitian ini memberikan wawasan berharga, terdapat kekurangan dalam eksplorasi konteks yang lebih luas dan variasi strategi intervensi. Oleh karena itu, penelitian selanjutnya disarankan untuk melibatkan beragam populasi siswa dan menguji berbagai metode pengajaran. Penelitian ini diharapkan dapat berkontribusi pada pengembangan teori dan praktik pendidikan yang lebih baik, serta menciptakan lingkungan belajar yang inklusif.
Statistika Non- Parametrik Mulyani, Ika Dini; Ismy, Nurul; Panggabean, Hadi Saputra
AURELIA: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Vol 4, No 2 (2025): July 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/aurelia.v4i2.6752

Abstract

Non-parametric statistics is an essential tool in data analysis, particularly when the assumption of normal distribution cannot be met. This method offers a flexible approach applicable to various types of data, including ordinal and nominal data. This article explores the fundamental principles, methodologies, and challenges of using non-parametric statistics, highlighting advantages such as more lenient assumptions and ease of calculation. Despite its limitations, especially regarding the testing of parametric assumptions and large sample sizes, non-parametric statistics remain a relevant choice. Guidelines for the use of one-sample, two-sample, and more than two-sample tests are presented, along with practical examples such as the binomial test, chi-square test, and Wilcoxon test. With a deep understanding of this method, researchers and practitioners are expected to make better decisions based on valid and reliable data analyses.
Statistika Non- Parametrik Mulyani, Ika Dini; Ismy, Nurul; Panggabean, Hadi Saputra
AURELIA: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Vol 4, No 2 (2025): July 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/aurelia.v4i2.6752

Abstract

Non-parametric statistics is an essential tool in data analysis, particularly when the assumption of normal distribution cannot be met. This method offers a flexible approach applicable to various types of data, including ordinal and nominal data. This article explores the fundamental principles, methodologies, and challenges of using non-parametric statistics, highlighting advantages such as more lenient assumptions and ease of calculation. Despite its limitations, especially regarding the testing of parametric assumptions and large sample sizes, non-parametric statistics remain a relevant choice. Guidelines for the use of one-sample, two-sample, and more than two-sample tests are presented, along with practical examples such as the binomial test, chi-square test, and Wilcoxon test. With a deep understanding of this method, researchers and practitioners are expected to make better decisions based on valid and reliable data analyses.
Co-Authors Diniyah, Cantika Alfa Hidayah, Nailla Ismy, Nurul Panggabean, Hadi Saputra Ummu Hanifah, Ummu