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All Journal Linguistics and Elt Journal ORBITA: Jurnal Pendidikan dan Ilmu Fisika Mudabbir: Journal Research and Education Studies CONSEN: Indonesian Journal of Community Services and Engagement
Zakiya, Hanifah
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Religion Computer Science & IT Education Engineering Environmental Science Languange, Linguistic, Communication & Media Physics Social Sciences Other

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Socialization of Deep Learning Approach in the Digital Era for Teachers in Indonesia: Sosialisasi Pendekatan Pembelajaran Mendalam / Deep Learning di Era Digital bagi Guru di Indonesia Rahayu, Chika; Zakiya, Hanifah; Falamy, Ryna Aulia; Ubaidillah, Muhammad; Prastyo, Yanuar Dwi; Utami, Lintang Fitra; Hardianti, Desrina; Yosilia, Rani
CONSEN: Indonesian Journal of Community Services and Engagement Vol. 5 No. 1 (2025): Consen: Indonesian Journal of Community Services and Engagement
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/consen.v5i1.2042

Abstract

The Deep Learning approach launched by the Ministry of Primary and Secondary Education is an approach that honors and is not a new curriculum outlined in the academic manuscript. However, there is still a lack of understanding about the Deep Learning approach, with some people thinking that Deep Learning is a curriculum, and many teachers still don’t understand how to plan and implement this approach in the classroom. This service in the form of socialization is carried out to provide teachers in Indonesia with an understanding of the implementation of Deep Learning in the digital era. The socialization was conducted online with approximately 800 participants, most teachers from various regions across Indonesia. The steps of the method used in this socialization include planning, the delivery of material, sharing during the Q&A session, and reflection. This socialization helps teachers to get to know and understand Deep Learning. It can be implemented in the classroom, leading to positive changes in the learning process, which improves students’ learning outcomes to achieve the eight graduate profiles. The result of this socialization activity was met with enthusiasm from the participants, as shown by the positive feedback during the event, such as interactive Q&A and responses from the participants, allowing them to mutually enrich each other’s learning, most of whom are teachers.
Visualisasi Pola Difraksi Berbasis Pemrograman Arduino Uno Menggunakan Sensor BH1750 dan Tracker Falamy, Ryna Aulia; Herlina, Kartini; Zakiya, Hanifah; Rahayu, Sri; Janah, Wardatul
MUDABBIR Journal Research and Education Studies Vol. 5 No. 1 (2025): Vol. 5 No. 1 Januari - Juni 2025
Publisher : Perkumpulan Manajer Pendidikan Islam Indonesia (PERMAPENDIS) Prov. Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56832/mudabbir.v5i1.917

Abstract

Penelitian ini bertujuan untuk memvisualisasikan pola difraksi cahaya berbasis mikrokontroler Arduino Uno yang terintegrasi dengan sensor cahaya BH1750 dan perangkat lunak Tracker. Visualisasi ini untuk membantu siswa dalam memahami fenomena difraksi cahaya melalui pendekatan eksperimen yang interaktif dan berbasis STEM. Eksperimen dilakukan dengan memvariasikan ketebalan kawat (0,008 mm, 0,029 mm, dan 0,05 mm) serta jarak antara kisi dan layar (50 cm, 75 cm, dan 100 cm) guna mengamati perubahan pola difraksi yang terbentuk. Sensor BH1750 digunakan untuk mendeteksi intensitas cahaya secara real-time, sementara aplikasi Tracker menganalisis citra pola difraksi. Hasil penelitian menunjukkan bahwa pola difraksi dipengaruhi secara signifikan oleh ketebalan penghalang dan jarak terhadap layar, di mana kawat lebih tipis dan jarak lebih jauh menghasilkan pola yang lebih lebar dan jelas. Temuan ini membuktikan bahwa alat bantu berbasis mikrokontroler Arduino Uno dapat digunakan secara efektif dalam meningkatkan pemahaman konsep difraksi secara visual dan kuantitatif, serta dapat diterapkan sebagai media pembelajaran fisika di SMA.
Integration of magnus thermodynamic parameters and machine learning algorithms in rainfall prediction Aprilia, Ayu; Zakiya, Hanifah; Pauzi, Gurum Ahmad; Supriyanto, Amir; Syafriadi, Syafriadi
ORBITA: Jurnal Pendidikan dan Ilmu Fisika Vol 11, No 2 (2025): November
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/orbita.v11i2.34505

Abstract

Atmospheric physics is very useful in predicting rainfall, particularly for analyzing air saturation conditions as a prerequisite for condensation. This study aims to model rainfall prediction using thermodynamic parameters, namely relative humidity (RH) and dew point temperature difference (ΔT). These parameters were collected from BMKG Lampung meteorological data (2022–2024) and processed using the Magnus equation. ΔT is important as a sensitive indicator of air unsaturation. The data were statistically analyzed and modeled using a Gradient Boosting Classifier. The results obtained indicate a strong correlation between RH and ΔT and rainfall events (point-biserial correlation of 0.475). Furthermore, ΔT during rainfall is lower (average 2.87°C) and stable, indicating near-saturation conditions. During the evaluation stage, the model achieved 76% accuracy and 84% recall during rainfall. The model's good performance proves the effectiveness of physical parameters as predictive features. Finally, the model was implemented in a Flask-based web application for practical accessibility.
Investigating the Deep Learning Approach and Lampung Cultural Values (Piil Pesenggiri): A Theoretical and Cultural Analysis Prastyo, Yanuar Dwi; Ariyani, Farida; Ubaidillah, Muhammad; Zakiya, Hanifah; Rahayu, Chika; Dharmawan, Yanuarius Yanu
Linguistics and ELT Journal Vol 13, No 2 (2025): Desember
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/leltj.v13i2.36543

Abstract

This conceptual paper investigates how the deep learning approach articulated in the New Pedagogies for Deep Learning (NPDL) framework can be theoretically and culturally aligned with Indonesian national graduate profiles, recent Indonesian government formulations of Pembelajaran Mendalam (PM), and the Lampung cultural philosophy of Piil Pesenggiri in the context of English language teaching (ELT). Drawing on document analysis of NPDL texts, Indonesian curriculum and policy documents, the Academic Paper on Deep Learning, scholarly discussions of graduate profiles, and regional literature on Piil Pesenggiri, the study develops a tri-level comparison between global, national, and local frameworks. The analysis shows that NPDL’s six global competencies-character, citizenship, collaboration, communication, creativity, and critical thinking-broadly converge with Kemendikdasmen’s holistic, competency-based vision of graduates and with national deep learning discourse, which combines knowledge, skills, character, and citizenship in integrated graduate profiles. At the local level, core elements of Piil Pesenggiri such as juluk adok, nemui nyimah, nengah nyappur, and sakai sambayan provide cultural resources that can support the social, ethical, and collaborative dimensions of deep learning, while also generating tensions around honour, face, hierarchy, and group harmony. The paper argues that, when these convergences and tensions are explicitly recognised, ELT classrooms in Lampung can be designed as spaces for deep learning projects that develop the 6Cs through locally meaningful themes, tasks, and interaction norms. The study concludes by outlining principles for culturally responsive, deep learning-oriented ELT and by suggesting directions for future empirical research on the localisation of global pedagogies and national deep learning reforms in Indonesian schools.
Co-Authors Aprilia, Ayu Desrina Hardianti Falamy, Ryna Aulia Farida Ariyani Herlina, Kartini Janah, Wardatul Lintang Fitra Utami Pauzi, Gurum Ahmad Rahayu, Chika Rani Yosilia SRI RAHAYU Supriyanto, Amir Syafriadi Syafriadi Ubaidillah, Muhammad Yanuar Dwi Prastyo Yanuarius Yanu Dharmawan