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All Journal Jurnal Tecnoscienza Nivedana : Jurnal Komunikasi dan Bahasa
Anis Sholikhah
Institut Teknologi Al Mahrusiyah
Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Engineering Mathematics Other

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Analisis Algoritma Apriori untuk Mendukung Kesalahan Suku Kata pada Hasil Tes Literasi Siswa Sekolah Dasar Mochammad Ilham Aziz; Atika Nur Fadilla; Anis Sholikhah; Saifulloh Azhar; Muhammad Oktoda Noorrohman
JURNAL TECNOSCIENZA Vol. 10 No. 1 (2025): JURNAL TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/tdz9qa35

Abstract

 Penelitian ini bertujuan untuk menganalisis pola kesalahan pengucapan suku kata pada hasil tes literasi siswa sekolah dasar dengan menerapkan algoritma Apriori sebagai salah satu teknik data mining dalam menemukan pola keterkaitan antar kesalahan. Melalui pendekatan kuantitatif deskriptif, data diperoleh dari hasil tes membaca siswa yang menunjukkan berbagai jenis kesalahan pada suku kata tertentu. Data kemudian diolah menggunakan algoritma Apriori untuk menghasilkan aturan asosiasi dengan memperhitungkan nilai support, confidence, dan lift guna mengidentifikasi hubungan antar kesalahan pengucapan yang paling signifikan. Hasil penelitian menunjukkan bahwa terdapat hubungan kuat antara kesalahan pengucapan beberapa suku kata, seperti Hon, De, dan Dak, dengan kesalahan pada suku kata Yam, yang memiliki nilai confidence di atas 50%. Temuan ini mengindikasikan adanya pola sistematis dalam kesalahan fonologis siswa yang dapat digunakan sebagai indikator kesulitan membaca dan mengenali bunyi bahasa. Kesimpulannya, penerapan algoritma Apriori efektif dalam mengungkap pola tersembunyi pada data kesalahan literasi siswa dan dapat menjadi alat diagnostik pendukung bagi guru untuk merancang strategi pembelajaran fonetik serta intervensi literasi yang lebih tepat sasaran. 
UNDERSTANDING THE IMPLEMENTATION OF DEEP LEARNING APPROACH IN ENHANCING STUDENT’S READING COMPREHENSION Anis Sholikhah; Mohammad Muhyidin; Nurul Hudha Purnomo
NIVEDANA : Jurnal Komunikasi dan Bahasa Vol. 7 No. 3 (2026): NIVEDANA : Jurnal Komunikasi dan Bahasa
Publisher : Sekolah Tinggi Agama Buddha Negeri Raden Wijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53565/nivedana.v7i3.3128

Abstract

The Deep Learning Approach is a method of learning that prioritizes meaningful comprehension over memory. With this method, students are encouraged to take an active role in their education, think critically, make connections between new and existing knowledge, and develop their own understanding. The Deep Learning Approach aids students in gaining a deeper and more meaningful understanding of texts through reading comprehension instruction. The purpose of this study was to look into how the Deep Learning Approach might be used to improve students' reading comprehension at MTs Miftahul Huda and to identify the challenges faced by the teacher during its implementation. Eleven students and one English teacher participated in this study, which used a qualitative descriptive design. Data reduction, data display, and conclusion drawing were used for analysis after the data was gathered through observation, interviews, and documentation. Furthermore, the results demonstrated that the Deep Learning Approach was applied in three phases: pre-activity, while-activity, and post-activity. Students were urged to actively participate, think critically, discuss concepts, and make connections between the reading materials and what they already knew. Students became more involved and demonstrated a deeper comprehension of the readings as a result. Nonetheless, certain difficulties were discovered, including varying degrees of student involvement, a restricted vocabulary, and time management. In order to increase students' reading comprehension and learning engagement, teachers are urged to use this strategy on a regular basis.
Co-Authors Atika Nur Fadilla Mochammad Ilham Aziz Mohammad Muhyidin Muhammad Oktoda Noorrohman Nurul Hudha Purnomo Saifulloh Azhar