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All Journal International Journal of Electrical and Computer Engineering JURNAL SISTEM INFORMASI BISNIS JURNAL TEKNIK MESIN Sebatik JURNAL PENDIDIKAN TAMBUSAI ILKOMNIKA: Journal of Computer Science and Applied Informatics TEPIAN Jurnal Lentera Pengabdian JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Fajar Ramadhani
Software Engineering Technology, Agriculture Polytechnic Of Samarinda
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mechanical Engineering Social Sciences

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Development of an Augmented Reality-Based Educational Media for East Kalimantan Endemic Plants Satria, Bagus; Ramadhani, Fajar; Imron, Imron
Sebatik Vol. 29 No. 2 (2025): December 2025
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v29i2.2671

Abstract

East Kalimantan is a region with a high level of biodiversity, including endemic plant species such as Eusideroxylon zwageri (Ulin), Coelogyne pandurata (Black Orchid), and Nepenthes spp. (Pitcher Plant). Unfortunately, public awareness especially among young generations of the importance of conserving these local flora remains low due to the lack of engaging and contextual learning media. This study aims to develop an Augmented Reality (AR)-based educational media that visualizes interactive 3D models and descriptive information about East Kalimantan endemic plants. The research applies an interactive multimedia-based Research and Development (R&D) approach through stages of observation, documentation, 3D modeling, application development using Unity and Vuforia SDK, and testing involving students from local schools. Evaluation was conducted using pre-test and post-test designs, along with expert validation on content and usability. The results show that the developed AR application effectively enhances students’ understanding of local biodiversity and environmental awareness. This media also provides an innovative solution for digital conservation education that integrates technology with local ecological content.
Enhancing sexual education for children with special needs through augmented reality: development and evaluation of the Magical SeDu application Maria, Eny; Satria, Bagus; Andrea, Reza; Imron, Imron; Karim, Syafei; Ramadhani, Fajar; Suswanto, Suswanto; Putra, Emil Riza; Sjamsir, Hasbi
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i1.pp288-296

Abstract

This research focuses on the educational obstacles encountered by children with special needs (CWSN), specifically in sexual education, through developing and evaluating the Magical SeDu application. Using a three-phase instructional design model, the study followed the planning, design, and development phases to create user-centered features that meet diverse learning needs. User acceptance testing (UAT) further confirmed the usability and effectiveness of the app, with a satisfaction rating of 86.04%. These findings underscore the transformative potential of augmented reality (AR) technology in inclusive education, fostering interactive and visually stimulating learning experiences. The study also emphasizes the importance of involving stakeholders in the development process to ensure the app meets the specific needs of its users. Future research should focus on enhancing the app’s features and exploring its integration into broader educational environments to maintain accessibility and continuous improvement. This study contributes to the advancement of inclusive education strategies and highlights the critical role of sex education in increasing self-awareness and protection for children with special needs.
Design IoT for Intelligent Soil Detection in Agriculture and Future Mine-Used Land Reclamation with Mobile Apps Imron, Imron; Satria, Bagus; Ramadhani, Fajar; Karim, Syafei; Dwi Putra Sidik, Rizky
ILKOMNIKA Vol 8 No 1 (2026): Volume 8, Number 1, April 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v8i1.808

Abstract

Former mining lands in Indonesia, particularly in East Kalimantan, experience severe soil degradation characterized by high acidity, nutrient deficiency, and poor physical structure, which limit their potential for agricultural reuse. This study presents the design and implementation of an integrated Internet of Things (IoT)–based soil monitoring system combined with an artificial intelligence (AI)–driven crop recommendation module to support data-driven land reclamation and precision agriculture. The system consists of an ESP32 microcontroller, NPK soil sensors with RS485 communication, and a cloud-connected mobile application developed using Flutter, Firebase, and ThingsBoard. Soil parameters including pH, moisture, electrical conductivity, temperature, and macronutrients (nitrogen, phosphorus, and potassium) are collected in real time and analyzed using an AI-based reasoning model to generate crop suitability recommendations. System validation was conducted through black-box functional testing covering authentication, data acquisition, geotagged storage, analytics, and recommendation modules. A total of 35 test cases were executed, with 33 cases (94.3%) passing successfully. Performance evaluation shows that dashboard visualization and recommendation generation meet predefined service-level thresholds under normal network conditions. The results indicate that the proposed system is technically feasible for real-time soil monitoring and decision support on post-mining land. However, this study is limited to system-level validation and does not yet include large-scale agronomic field trials or comparative evaluation against conventional soil assessment methods. Future work will focus on improving AI model validation, expanding field deployment, and assessing agronomic impacts over longer cultivation cycles.
Co-Authors Altetiko, Faizal Johan annafi franz, annafi Asep Nurhuda Budi, Aditya Septa Dwi Putra Sidik, Rizky Eko Junirianto Emil Riza Putra Husmul Beze, Husmul Ida Maratul Khamidah Imron Imron, Imron irsyad, irsyad Karim, Syafei Kartika Maulida Hindrayani Khoiri Rozi Ladrika Eka Putri Maria, Eny Muslimin Muslimin Nur Aini Rakhmawati Nur Linda Nurhizrah Gistituati Nurhuda, Asep Rachmadani, Budi Reza Andrea Sjamsir, Hasbi Suci Ramadhani, Suci Sulastri Sulastri Suswanto Suswanto, Suswanto Tandi, Yospin TK, Berkah Fajar Wardati, Nanda Kurnia Yulianto Yulianto