Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal bit-Tech JPEG
Suryantiko, Sandy
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Classification of Children's Numerical Intelligence Levels Based on Mathematics Learning Activities Using Machine Learning Suryantiko, Sandy; Mulyadi, Gilang Adriana; Ferawati, Ferawati
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2646

Abstract

Numerical ability is a critical aspect of education that impacts both academic achievement and the development of logical thinking skills. However, in Islamic boarding schools (pondok pesantren), the teaching of mathematics often encounters limitations such as a lack of technological integration and diverse learning resources. This study aims to assess students' numerical intelligence levels based on their mathematics learning activities using machine learning techniques, specifically Decision Tree and Random Forest algorithms. Data was collected through questionnaires that captured key variables such as study duration, frequency of practice, learning methods, class engagement, and the speed of problem-solving. After data preprocessing, both models were evaluated through confusion matrices and cross-validation to determine their classification accuracy and stability. The findings revealed that the Decision Tree model achieved an accuracy rate of 86%, while the Random Forest model surpassed it with a 92% accuracy rate, showing more consistent performance. This study highlights the potential of machine learning to enhance educational outcomes, particularly in pesantren settings, by offering deeper insights into students' learning patterns. Beyond classification accuracy, machine learning helps educators identify key factors influencing students' numerical intelligence. The Random Forest model, in particular, revealed that variables such as practice frequency and student engagement are significant predictors of numerical intelligence levels. This information can be used to develop more personalized and effective teaching strategies aimed at improving students' mathematical skills.
Pelatihan Penggunaan Aplikasi Pembelajaran Interaktif untuk Meningkatkan Minat Belajar Anak di Panti Asuhan LKSA Al-Izan’ni Sofia, Detin; Saepudin, Muhamad; Safitri, Nur Hafidzah; Abdillah, Refa Maulana; Suryantiko, Sandy
JURNAL PENGABDIAN GLOBAL Vol 4, No 2 (2025): Jurnal Pengabdian Global (JPEG)
Publisher : JURNAL PENGABDIAN GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/jpeg.v4i2.16005

Abstract

Kegiatan Pengabdian Kepada Masyarakat (PKM) ini dilaksanakan untuk menjawab permasalahan rendahnya minat belajar anak-anak di Panti Asuhan LKSA Al-Izan’ni, yang dipengaruhi oleh keterbatasan metode pembelajaran, minimnya pemanfaatan teknologi interaktif, serta kurangnya keterampilan pengasuh dalam menggunakan aplikasi digital. Solusi yang ditawarkan berupa pelatihan penggunaan aplikasi pembelajaran interaktif, pendampingan, serta evaluasi implementasi dalam proses belajar. Metode pelaksanaan meliputi tahap persiapan, pelatihan pengasuh, implementasi aplikasi, hingga monitoring dan evaluasi. Hasil kegiatan menunjukkan peningkatan minat belajar anak-anak melalui penggunaan aplikasi seperti Duolingo dan Quizizz yang dikombinasikan dengan metode gamifikasi, kuis, dan video edukasi. Selain itu, keterampilan pengasuh dalam mendukung pembelajaran interaktif juga meningkat sehingga menciptakan lingkungan belajar yang lebih menarik, menyenangkan, dan efektif. Dengan demikian, program ini berhasil memberikan kontribusi nyata dalam mendukung kualitas pendidikan anak-anak di Panti Asuhan LKSA Al-Izan’ni.
Co-Authors Abdillah, Refa Maulana Ferawati Ferawati Mulyadi, Gilang Adriana Saepudin, Muhamad Safitri, Nur Hafidzah SOFIA, DETIN