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All Journal TESLA: Jurnal Teknik Elektro Jurnal Mandiri IT Gotong Royong
Dananjaya Ariateja
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences

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Portable oceanic solutions for enhanced IoT-based desalination and salt extraction (POSEIDON) Randi Agustio; Onky Prilianda Putra; Dananjaya Ariateja; Refino Maulana Hansbullah Subarkah; H. A Danang Rimbawa
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

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Abstract

The clean water crisis remains a significant challenge in many remote areas, particularly on small islands in Indonesia where freshwater resources are limited. Desalination technology offers a promising solution; however, conventional methods often face obstacles such as high energy consumption, costly operations, and limited real-time water quality monitoring. This study aims to design and evaluate a distillation-based desalination device integrated with Internet of Things (IoT) technology, called POSEIDON. The system utilizes solar energy and heating elements to support the distillation process and is equipped with pH, TDS, ultrasonic, and water level sensors connected to the Blynk application for real-time monitoring and alert notifications. Testing was conducted over 10 hours under both daytime and nighttime conditions. Results show that the distilled water had pH values ranging from 7.01 to 7.51 and PPM values from 798 to 588.38. One-way ANOVA indicated no statistically significant variation (p > 0.05), demonstrating consistent system performance. The average volume of fresh water produced was 0.403 liters from 0.7 liters of seawater, with an average salt yield of 23.1 grams. POSEIDON exhibits good energy efficiency and portability, and it can operate at night. Nevertheless, improvements are needed in production capacity and water quality. Overall, POSEIDON presents a viable and sustainable solution to meet clean water needs in remote, water-scarce regions.
DESIGN AND CONSTRUCTION OF A RASPBERRY PI-BASED HUMAN FOLLOWING ROBOT WITH TENSORFLOW LITE-BASED DETECTION Ariq Farras Zhafran; Dananjaya Ariateja; Herwin Melyanus Hutapea
TESLA: Jurnal Teknik Elektro Vol 27 No 1 (2025): TESLA: Jurnal Teknik Elektro
Publisher : Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/tesla.v27i1.35263

Abstract

The application of artificial intelligence (AI) in robotics has provided innovative solutions to various operational challenges, particularly those related to the system's ability to automatically detect and interact with humans. One such implementation is the Human Following Robot, an autonomous robot designed to follow human movements using an AI-based image processing system. This research proposes the design and development of a Raspberry Pi 4-based Human Following Robot prototype with a TensorFlow Lite algorithm. The research methodology uses an experimental approach with a focus on evaluating target detection accuracy and robot movement stability under varying lighting and terrain conditions. The experimental approach was used by testing the robot on flat and rocky terrain, as well as in bright and dim lighting conditions. The limitation of this research is that the system only tests the detection of one target person without any obstacles or other people around the robot. The results of the study show that the robot has optimal performance at a detection distance of 200–300 cm with an accuracy of 92%–94% in lighting conditions above 100,000 lux, as well as stable movement on flat terrain. Based on these results, this robot has great potential to support more efficient and safer military logistics operations. Future development will focus on improving accuracy in low-light conditions, improving mechanical design, and integrating multi-object tracking capabilities. Abstrak Penerapan kecerdasan buatan (Artificial Intelligence/AI) dalam bidang robotika telah menghadirkan solusi inovatif terhadap berbagai tantangan operasional, khususnya terkait kemampuan sistem dalam mendeteksi dan berinteraksi dengan manusia secara otomatis. Salah satu implementasinya adalah Human Following Robot, yaitu robot otonom yang dirancang untuk mengikuti pergerakan manusia dengan memanfaatkan sistem pengolahan citra berbasis AI. Penelitian ini mengusulkan perancangan dan pembangunan prototipe Human Following Robot berbasis Raspberry Pi 4 dengan algoritma TensorFlow Lite. Metodologi penelitian menggunakan pendekatan eksperimental dengan fokus penelitian diarahkan pada evaluasi akurasi deteksi target serta kestabilan pergerakan robot pada kondisi pencahayaan dan medan yang bervariasi. Pendekatan eksperimental digunakan dengan menguji robot pada medan datar dan berbatu, serta pada kondisi pencahayaan terang dan redup. Batasan penelitian ini adalah sistem hanya menguji pendeteksian satu orang target tanpa adanya objek penghalang atau orang lain di sekitar robot. Hasil penelitian menunjukkan bahwa robot memiliki kinerja optimal pada jarak deteksi 200–300 cm dengan akurasi 92%–94% pada kondisi pencahayaan di atas 100.000 lux, serta pergerakan stabil di medan datar. Berdasarkan hasil tersebut, Robot ini memiliki potensi besar untuk mendukung operasi logistik militer yang lebih efisien dan aman. Untuk pengembangan selanjutnya diarahkan pada peningkatan akurasi di kondisi minim cahaya, perbaikan desain mekanik, serta integrasi kemampuan pelacakan multi-objek
Peningkatan Kompetensi Siswa SMK Tunggal Prakarsa Melalui Pelatihan Instalasi Dan Monitoring Pembangkit Listrik Tenaga Surya (PLTS) Berbasis Internet Of Things Dananjaya Ariateja; Joni Welman Simatupang; Sunarta Sunarta; Bagus Hendra
Gotong Royong Vol. 3 No. 2 (2026)
Publisher : CV. Akira Java Bulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63935/gr.v3i2.297

Abstract

Ketersediaan sumber daya manusia (SDM) yang kompeten di bidang energi terbarukan dan Internet of Things (IoT) menjadi salah satu kebutuhan penting di bidang pendidikan sekolah menengah atas dalam menghadapi era Industri 4.0. Namun, pemahaman dan keterampilan siswa Sekolah Menengah Kejuruan (SMK), khususnya di SMK Tunggal Prakarsa, masih terbatas pada teori dan belum banyak mendapatkan pengalaman praktik terkait instalasi serta monitoring Pembangkit Listrik Tenaga Surya (PLTS) berbasis IoT. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi siswa dalam aspek pengetahuan, keterampilan praktik, dan sikap profesional pada instalasi dan sistem monitoring PLTS berbasis IoT. Metode pelaksanaan meliputi: (1) pemetaan kebutuhan dan tingkat pemahaman awal siswa melalui pre-test dan wawancara singkat, (2) penyampaian materi konsep dasar PLTS, dasar-dasar IoT, serta penerapan IoT pada sistem monitoring energi, (3) praktik langsung instalasi miniatur PLTS dan perakitan sistem monitoring menggunakan mikrokontroler serta sensor yang terhubung ke platform IoT, dan (4) evaluasi hasil pelatihan melalui post-test, unjuk kerja praktik, serta refleksi peserta. Hasil kegiatan menunjukkan adanya peningkatan nilai rata-rata pengetahuan teknis siswa, peningkatan kemandirian dan keterampilan dalam merangkai serta mengkonfigurasi sistem PLTS berbasis IoT, serta bertambahnya minat siswa untuk mengembangkan proyek energi terbarukan di sekolah. Kegiatan ini memberikan dampak positif bagi penguatan kompetensi vokasi siswa dan dapat menjadi model pelatihan berkelanjutan untuk mendukung pengembangan sekolah berbasis teknologi hijau. Juga meningkatkan sinergi antara perguruan tinggi (universitas), sekolah (masyarakat), dan dunia industri (industry) yang dikenal dengan istilah triple-helix.   The availability of competent human resources in the field of renewable energy and the Internet of Things (IoT) is one of the important needs in facing the Industry 4.0 era. However, the understanding and skills of vocational school students, especially at SMK Tunggal Prakarsa, are still limited to theory and have not received much practical experience related to the installation and monitoring of IoT-based Solar Power Plants (PLTS). This community service activity aims to improve student competency in the aspects of knowledge, practical skills, and professional attitudes in the installation and monitoring system of IoT-based PLTS. The implementation method includes: (1) mapping the needs and level of initial understanding of students through pre-tests and short interviews, (2) delivering material on basic PLTS concepts, IoT basics, and the application of IoT to energy monitoring systems, (3) direct practice of installing miniature PLTS and assembling monitoring systems using microcontrollers and sensors connected to the IoT platform, and (4) evaluation of training results through post-tests, practical performance, and participant reflections. The results of the activity showed an increase in the average score of students' technical knowledge, increased independence and skills in assembling and configuring IoT-based solar power systems, and increased student interest in developing renewable energy projects at school. This activity has a positive impact on strengthening students' vocational competencies and can serve as a model for sustainable training to support the development of green technology-based schools. It also increases synergy between universities, schools (society), and the industrial world (industry) which is known as the triple-helix.
Co-Authors Ariq Farras Zhafran Bagus Hendra H. A. Danang Rimbawa Herwin Melyanus Hutapea Joni Welman Simatupang Onky Prilianda Putra Randi Agustio Refino Maulana Hansbullah Subarkah Sunarta Sunarta