Article Per Year (5 Year)
p-Index From 2021 - 2026
0.92
P-Index
This Author published in this journals
All Journal Jurnal Pendidikan Agama Islam Jurnal Pendidikan Anak Usia Dini International Journal of Applied Science and Technology Application
Muhammad Hasanuddin
Universitas Pembangunan Panca Budi
Religion Humanities Education Languange, Linguistic, Communication & Media Social Sciences Other

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
Integrasi Nilai-Nilai Islam dalam Pengembangan Karakter Peserta Didik di Era Digital Efriansyah Putra Bahari Barus; Zulfan; Muhammad Hasanuddin
Jurnal Pendidikan Agama Islam Vol. 1 No. 3 (2025): September 2025
Publisher : CV. Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/jurpai.v1i3.24

Abstract

Penelitian ini bertujuan untuk menganalisis proses integrasi nilai-nilai Islam dalam pengembangan karakter peserta didik di era digital serta melihat dampak yang ditimbulkan dari penerapannya pada lingkungan pembelajaran berbasis teknologi. Penelitian menggunakan pendekatan kualitatif dengan desain studi kasus yang melibatkan guru Pendidikan Agama Islam, kepala madrasah, dan peserta didik sebagai informan utama. Data dikumpulkan melalui observasi, wawancara mendalam, dan dokumentasi perangkat pembelajaran digital. Hasil penelitian menunjukkan bahwa integrasi nilai-nilai Islam dilakukan melalui penggunaan media digital, pembelajaran berbasis proyek, pembiasaan etika komunikasi, serta pemanfaatan forum diskusi daring yang berorientasi pada pembentukan akhlak. Peserta didik menunjukkan peningkatan perilaku pada aspek etika komunikasi digital, kedisiplinan, dan tanggung jawab dalam menggunakan teknologi. Guru berperan penting sebagai teladan digital yang memberikan contoh nyata mengenai penerapan nilai Islam dalam interaksi daring. Meskipun terdapat tantangan seperti keterbatasan literasi digital guru dan distraksi peserta didik, dukungan madrasah dan keterlibatan orang tua memperkuat keberhasilan implementasi integrasi nilai Islam. Secara keseluruhan, penelitian ini menegaskan bahwa teknologi dapat menjadi sarana efektif dalam pembentukan karakter Islami apabila digunakan secara terarah dan konsisten dalam pembelajaran.
The Effectiveness of Using Flashcards in Improving Early Childhood Reading Skills Muhammad Hasanuddin; Abil Alwi Prayoga
Jurnal Pendidikan Anak Usia Dini Vol. 1 No. 1 (2025): Desember 2025
Publisher : CV. Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jupaud.v1i1.68

Abstract

This study aims to analyze the effectiveness of using flashcards to improve early reading skills in young children. This research is grounded in the need for engaging, interactive learning methods that align with the developmental characteristics of early childhood. The study employed a quasi-experimental design with a pretest–posttest control group. The sample consisted of children aged 4–6 years, divided into an experimental and a control group. The experimental group received reading instruction using flashcards for four weeks, while the control group used conventional teaching methods. The results indicate a significant improvement in children's reading abilities when using flashcards compared to the control group. The improvement is evident in letter recognition, syllable understanding, and the ability to read simple words. A t-test supports the finding that flashcards have a positive, significant impact on the development of early reading skills. Therefore, it can be concluded that flashcards are an effective and practical learning medium that supports early literacy development in young children.
Dampak Penggunaan Gadget terhadap Perkembangan Sosial Anak Usia 3–6 Tahun Fadilah Ramadani; Siti Khodijah; Cindy Atika Rizki; Muhammad Hasanuddin
Jurnal Pendidikan Anak Usia Dini Vol. 1 No. 1 (2025): Desember 2025
Publisher : CV. Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jupaud.v1i1.69

Abstract

Penelitian ini bertujuan untuk menganalisis dampak penggunaan gadget terhadap perkembangan sosial anak usia 3–6 tahun dengan menyoroti pola interaksi, kemampuan komunikasi, dan regulasi emosi dalam aktivitas bermain. Menggunakan pendekatan kualitatif dengan desain studi kasus, penelitian ini mengumpulkan data melalui observasi, wawancara, dan dokumentasi yang melibatkan anak, orang tua, serta guru pendidikan anak usia dini. Hasil penelitian menunjukkan bahwa penggunaan gadget yang tidak terkontrol dapat menurunkan kualitas interaksi sosial, menghambat kelancaran komunikasi, dan memicu ketergantungan emosional pada perangkat. Sebaliknya, penggunaan yang didampingi dan diatur secara tepat dapat tetap mendukung perkembangan sosial anak melalui keseimbangan antara pengalaman digital dan interaksi langsung. Penelitian ini menegaskan pentingnya pendampingan orang tua dan pengaturan penggunaan gadget dalam mendukung perkembangan sosial anak usia dini.
Integrated Multi-Domain Modeling Framework for Energy Efficiency and Range Prediction in Modern Electric Vehicle Systems Siti Khodijah; Cindy Atika Rizki; Muhammad Hasanuddin
International Journal of Applied Science and Technology Application Vol. 1 No. 1 (2026): Optimization and Computer Science
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/ijapset.v1i1.1

Abstract

The rapid advancement of electric vehicle (EV) technology has intensified the need for comprehensive theoretical frameworks capable of accurately evaluating energy efficiency and driving range under realistic operating conditions. This study presents an integrated multi-domain modelling approach that combines drivetrain physics, battery dynamics, drive-cycle analysis, control strategy optimization, and data-driven prediction to assess energy consumption in modern EV systems. A mechanistic model was developed to capture longitudinal vehicle dynamics, resistive forces, motor–inverter efficiency, battery behavior, and regenerative braking processes. The model was evaluated under standardized driving cycles, including the New European Driving Cycle (NEDC), Worldwide Harmonized Light Vehicles Test Procedure (WLTP), and Indian Driving Cycle (IDC), to investigate the impact of speed profiles and acceleration patterns on energy performance. The results demonstrate that energy consumption varies significantly across drive cycles, with aerodynamic drag and vehicle mass emerging as dominant influencing factors. Regenerative braking contributes meaningful energy recovery in urban conditions, though its effectiveness depends on control strategy and battery constraints. Comparative analysis between mechanistic modelling and machine learning approaches reveals that data-driven models improve predictive accuracy, while physics-based models provide interpretability and theoretical robustness. Furthermore, advanced control strategies such as Model Predictive Control (MPC) show superior performance in reducing energy consumption and range uncertainty compared to conventional PI-based controllers. Overall, the findings confirm that EV energy efficiency is an emergent property shaped by the interaction of design parameters, operational conditions, and intelligent control. The proposed integrated modelling framework provides a reliable foundation for next-generation EV design optimization, accurate range estimation, and sustainable mobility planning.
Urban Vegetation Cover Prediction Using Sentinel-2 NDVI and Random Forest: A Brief Narrative Review Muhammad Hasanuddin; Abil Alwi Prayoga
International Journal of Applied Science and Technology Application Vol. 1 No. 1 (2026): Optimization and Computer Science
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/ijapset.v1i1.3

Abstract

A predictive model of urban vegetation cover is developed by integrating remote sensing technology, cloud computing, and machine learning algorithms. The study used the Normalized Difference Vegetation Index (NDVI), calculated from Sentinel-2 satellite imagery and analyzed in Google Earth Engine (GEE), to monitor vegetation conditions at a wide spatial scale. The research approach uses quantitative methods, including spatial analysis based on satellite imagery and predictive modeling with the Random Forest algorithm. The research process includes acquiring Sentinel-2 Level-2A images, pre-processing them with cloud masking and atmospheric correction, calculating NDVI values, and developing vegetation prediction models using machine learning methods. The results showed that the Random Forest model predicted vegetation cover with high accuracy, as indicated by a Coefficient of Determination (R²) of 0.85 and a Root Mean Square Error (RMSE) of 0.045. The resulting vegetation distribution map shows significant variations in vegetation density between natural vegetation areas, agricultural land, and built-up areas. The findings of this study show that integrating NDVI from Sentinel-2, Google Earth Engine, and the Random Forest algorithm is an effective approach for monitoring and predicting urban vegetation cover. The results of this study make a methodological contribution to the development of remote sensing-based geospatial analysis and provide a scientific basis for sustainable urban planning and green open space management in urban areas.
Co-Authors Abil Alwi Prayoga Cindy Atika Rizki Efriansyah Putra Bahari Barus Fadilah Ramadani Siti Khodijah Zulfan