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All Journal MEDIA ELEKTRIKA ELKHA : Jurnal Teknik Elektro JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro KOMPUTIKA - Jurnal Sistem Komputer Journal of Public Health Education Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Pengabdian Kepada Masyarakat Abdi Putra Fidelity : Jurnal Teknik Elektro International Journal Engineering and Applied Technology (IJEAT) Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia
Anang Suryana
Universitas Nusa Putra
Humanities Astronomy Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Nursing Physics Public Health Social Sciences Other

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Pengembangan STEM-A (Science, Technology, Engineering, Mathematic and Animation) Berbasis Kearifan Lokal dalam Pembelajaran Fisika Utami, Indri Sari; Septiyanto, Rahmat Firman; Wibowo, Firmanul Catur; Suryana, Anang
Jurnal Ilmiah Pendidikan Fisika Al-Biruni Vol 6 No 1 (2017): Jurnal Ilmiah Pendidikan Fisika Al-Biruni
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/jipfalbiruni.v6i1.1581

Abstract

Pembelajaran fisika yang terjadi di lapangan masih minim inovasi. Pembelajaran cenderung berpusat pada pendidik. Pendidik hanya mentransfer pengetahuannya saja tanpa memikirkan apakah peserta didik sudah memahami konsep yang disampaikan atau belum. Rata-rata capaian hasil pemahaman konsep Fisika masih rendah. Teknologi yang berkembang pesat saat ini masih jarang dimanfaatkan oleh para pendidik. Padahal ini bisa menjadi salah satu alternatif untuk membuat pembelajaran lebih menarik dan berkesan. Dengan mengaitkan kearifan lokal yang ada di daerah peserta didik, dapat membuat peserta didik lebih mengenal kekayaan alam di daerahnya dan dapat diperkenalkan baik skala nasional maupun intrnasional. Dengan adanya permasalahan-permasalahan tersebut, maka perlu adanya integrasi anatara model, evaluasi dan media pembelajaran STEM-A (Sciences, Technology, Engineering, Mathematics, and Animation) berbasis kearifan lokal. Metode Penelitian yang dilakukan adalah Kuasi Eksperimen dengan desain penelitian one group pretest-posttest design. Hasil observasi menunjukkan adanya peningkatan pemahaman konsep mahasiswa setelah diterapkan pembelajaran STEM-A (Sciences, Technology, Engineering, Mathematics, and Animation) berbasis kearifan lokal. Dengan kategori sedang pada gain dinormalisasinya. Dari pembelajaran ini mahasiswa menjadi mengetahui kearifan lokal batu kuwung dan cara memanfaatkannya. Hasil penelitian akan terus dikembangkan pada mata kuliah-mata kuliah lain di jurusan Pendidikan Fisika Universitas Sultan Ageng tirtayasa.Development of STEM-A (Science, Technology, Engineering, Mathematics, and Animation) Based on Local Values in Physics LearningLearning physics is still traditional in reality. It tends to be centered on Teachers. They only transfer knowledge without knowing the learners already understand the concept yet or not. The average achievement understanding of physics concept results is still low. Rapidly evolving technology is still rarely used by teachers. Though this could be one of the alternatives to make learning more interesting and memorable. Connecting the local knowledge in the area of learners can make students more familiar with the natural resources in the region and can be introduced to the outside world. Given these problems, the need for integration between models, evaluation and learning media STEM-A (Sciences, Technology, Engineering, Mathematics, and Animation) based on local wisdom. The methods used were a Quasi-Experiment with the design of the study "One Group Pretest-Posttest Design." Observations indicate an increased understanding of the student concept after learning applied STEM-A (Sciences, Technology, Engineering, Mathematics, and Animation) based on local wisdom with medium category in gain normalization. By learning this concept, students could be aware of local wisdom "Batu Kuwung" and understand how to get advantage from it. The results of the study will continue to be developed in the courses in the Department of Physical Education University of Sultan Ageng Tirtayasa.
Bibliometric Analysis of IoT-Driven Smart Agriculture and Irrigation Management Research: Trends, Topics, and Publication Patterns (2019-2024) Hendrawati, Trisiani Dewi; Narputro, Panji; Wicaksana, Fikri Arif; Suryana, Anang
Fidelity : Jurnal Teknik Elektro Vol 7 No 2 (2025): Edition for May 2025
Publisher : Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/fidelity.v7i2.295

Abstract

This study explores the bibliometric analysis of research on smart agriculture and IoT-based irrigation management from 2019 to 2024, focusing on trends, topics, and publication patterns. Smart agriculture integrates advanced technologies such as IoT, artificial intelligence (AI), and big data analytics to enhance productivity and sustainability in farming systems. The analysis identifies a steady growth in publications, with a significant spike in 2023, reflecting the increasing global interest in utilizing IoT technologies to address challenges like water scarcity, climate change, and food security. Key topics include IoT-based sensor technologies for soil and water management, precision agriculture, and sustainable farming practices.The study also highlights the role of international collaboration, with countries like India, China, and the United States emerging as central hubs in fostering interdisciplinary research. Major sources such as Lecture Notes in Networks and Systems, AIP Conference Proceedings, and IEEE Access significantly contribute to the dissemination of research findings. Furthermore, the co-occurrence network analysis reveals the dominance of IoT as a central theme, with strong links to related topics like irrigation, soil moisture, and crop management.This research provides valuable insights for researchers, policymakers, and practitioners by identifying critical trends and research gaps, emphasizing the importance of IoT in optimizing irrigation systems, improving efficiency, and promoting sustainable agricultural innovations. These findings support the development of smart agriculture systems that are adaptive to global challenges and resource constraints.
Wireless Sensor Sub-Network Based IoT System for Probiotic Dosing and Water Quality Management Using Artificial Neural Network Junfithrana, Anggy Pradiftha; Suryana, Anang; Saputri, Utamy Sukmayu
ELKHA : Jurnal Teknik Elektro Vol. 17 No.1 April 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i1.96914

Abstract

Water quality management in aquaculture plays a crucial role in maintaining fish health and optimizing growth, particularly in intensive tilapia farming. This study develops a Wireless Sensor Sub-Network (WSSN) based Internet of Things (IoT) system designed to automate probiotic dosing and monitor water quality conditions using real-time sensor feedback and Artificial Neural Network (ANN) analysis. Utilizing TCS3200 color sensors, flow sensors, and an ANN within a WSSN, the system autonomously manages probiotic delivery based on real-time water color analysis, marking a shift towards intelligent water-quality management in aquaculture. The system architecture consists of three primary sensing and control components: a flow sensor connected to an ESP32 microcontroller to measure the precise volume (in milliliters) of probiotic solution dispensed; a TCS3200 color sensor, also integrated with an ESP32 module, to detect variations in water color as an indicator of pond health; and a solenoid valve controlled through a relay-actuated ESP32 node to regulate probiotic release into the pond. The sensor network operates wirelessly to provide continuous monitoring and intelligent decision-making. The ANN employs the backpropagation algorithm to perform color-based classification, where light green indicates a healthy condition, dark green represents normal stability, light brown signals the need for probiotic dosing, and dark brown denotes a critical condition requiring water replacement. This integration of optical and flow sensing with neural network computation provides an intelligent, non-invasive, and adaptive mechanism for probiotic management in tilapia aquaculture, supporting sustainable aquaculture practices and improving operational efficiency through automation and predictive learning.
Co-Authors Adam Muhamad Ali Ade Sopian Adi Nugraha Adi Nugraha Adi Nugraha Adikara, Fransiskus Ahmad khuzairi Ajat Al Bantani, Rahmat Ato'ullah Gumilang Alya Abdul Zabar Anggy Pradiftha Junfithrana Arrozi , MF Artiyasa, Marina Aryo De Wibowo Astri Sri Rahayu Bayu Indrawan Bobi Grahadinansyah Chairinaufal Salasa Usmi CSA Teddy Lesmana Danang Purwanto Dede Sukmawan Deden Rahmat Dera Septa Dimas Arya Pamungkas Dio Damas Permadi Edwinanto Edwinanto Edwinanto Edwinanto Edwinanto Edwinanto Efendi Efendi Eva Fauziah Evyta Wismiana Firmanul Catur Wibowo Gina Syabani Yuda Grahito Gustian, Dudih Handrea Bernando Tambunan Handrea Bernando Tambunan Harurikson Lumbantobing Harurikson Lumbantobing Hendrawati, Trisiani Dewi Ilman Himawan Kusumah Ilman Himawan Kusumah Indrawan, Bayu Indri Sari Utami Intan Putri Kania Irlan, Ade Okvianti Ivano Kumaran Julia Damayanti Lisa Oksri Nelfia Lumbantobing, Harurikson M. Alfirdan Marina Artiyasa Marina Artiyasa Marina Artiyasa Moch Alif Wicaksana Moch Rizky Mochtar Ali Setyo Yudono Muchtar Ali Setyo Yudono Muhamad Ramdhani Firmansyah Muhammad Galuh Sutisna Muhammad Shobirin Narputro, Panji Neng Rani Nabawiyah Nuraiman Pahmi, Samsul Paikun Popi Puspitasari Pratama Ginanjar Kharisman Rahmat Firman Septiyanto, Rahmat Firman Resnawati Febrian Rintho Rante_Rerung Rizky Taufik , Akhmad Rossa Najwa Saputri, Utamy Sukmayu Setiawati Sholahudin, Sholahudin Ta Aliyono Hadi Taufik Kurnia Azis Tomi Lotama Ula, Rini Khamimatul Utami, Indri Sari Utami, Indri Sari Virya Nanda Romanista Waryani Waryani Wicaksana, Fikri Arif Yopani Selia Almahisa Yosep B. Hutahaean Yudha Putra Yudha Putra Yufriana Imamulhak Yufriana Imamulhak Zafar Akbar