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All Journal International Journal of Electrical and Computer Engineering Jurnal SPEKTRUM Techne : Jurnal Ilmiah Elektroteknika Journal of Electrical, Electronics and Informatics Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Majalah Ilmiah Teknologi Elektro Jurnal SPEKTRUM
Ida Bagus Gede Manuaba
Department Of Electrical Engineering, Universitas Udayana
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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Pembuatan Pembangkit Listrik Termoelektrik pada Kompor Berbahan Bakar Pellet Biomassa Kayu Karet Devanka Arya Levin; Jonatan Sinurat; Anak Agung Ngurah Amrita; Ida Bagus Gede Manuaba
JURAL RISET RUMPUN ILMU TEKNIK Vol. 4 No. 3 (2025): Desember : Jurnal Riset Rumpun Ilmu Teknik
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurritek.v4i3.6818

Abstract

Biomass is one of the materials that can be utilized as fuel. To ensure optimal quality, effective management of biomass is required to maximize its potential. One possible approach is the application of a biomass stove fueled by rubber wood pellets. By integrating a thermoelectric generator, data can be obtained to determine whether all aspects meet the established standards. This system is designed to generate electrical energy from combustion heat, supported by components such as a buck-boost converter and a 3V DC lamp. Testing was carried out using proximate and ultimate analyses on the fuel as well as the Water Boiling Test (WBT) on the stove, referring to SNI 8021:2020 and SNI 8021:2014 standards. The results showed that rubber wood pellets contained 7.64% moisture and had a calorific value of 4050 kcal/kg. The stove demonstrated an efficiency of 23.53%–37.28% and a fuel consumption rate of 0.61–0.77 kg/hour, both of which meet the requirements. In addition, the thermoelectric generator produced a voltage of 3.6 V and an electric current of 0.05 A, which are higher than those reported in previous studies (2.06 V and 0.01 A, respectively). Therefore, this thermoelectric biomass stove system is considered successful and feasible for further development as an alternative energy application.
PENGEMBANGAN SISTEM OTOMATISASI PENGENDALI ALAT PENDINGIN BERDASARKAN SUHU RUANGAN DENGAN MENGGUNAKAN SENSOR LM35 I Gede Ketut Ari Wirawan; I Made Anggi Wahyudi Artha; Rukmi Sari Hartati; Ida Bagus Gede Manuaba
Jurnal SPEKTRUM Vol. 12 No. 3 (2025): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/SPEKTRUM.2025.v12.i03.p15

Abstract

Indoor temperature and humidity control plays an important role in creating a comfortable and energy-efficient environment, especially in tropical areas such as Denpasar, Bali. Manual use of air conditioners (AC) is often less than optimal because it does not consider the actual environmental conditions as a whole. This study designs an AC control automation system based on the Internet of Things (IoT) concept that can be controlled via a web interface. This system combines several sensors, such as LM35 for temperature, DHT22 for humidity, and PIR for motion detection, and is controlled by an Arduino UNO microcontroller. In addition, data transmission is carried out via the HM-10 Bluetooth module and a web-based monitoring interface built using the Python programming language. The developed system is able to display temperature, humidity, and user presence data in real time, and automatically regulates AC operation based on these environmental conditions. Tests show that the LM35 sensor has an error of 1,42% and the DHT22 sensor is 0.73%, with an effective range of PIR and IR sensors of up to 4 meters. Overall, this system has succeeded in saving AC energy consumption by up to 35.49%. Based on these results, this system is considered feasible to be applied in real environments as an efficient and adaptive temperature control solution.
Literatur Review Tantangan dan Teknologi dalam Pengembangan Advance Metering Infrastructure (AMI) I Made Agus Artha Putra; Ida Bagus Gede Manuaba
Majalah Ilmiah Teknologi Elektro Vol 24 No 1 (2025): ( Januari - Juni ) Majalah Ilmiah Teknologi Elektro
Publisher : Study Program of Magister Electrical Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.205.v24i01.P01

Abstract

The fundamental challenges related to the inability of traditional metering infrastructure to provide accurate and fast data and the lack of visibility to manage electricity usage information have driven the development of smart metering solutions. Smart metering, which is part of the smart grid architecture, has evolved over the years along with the needs of the electric power system infrastructure that requires efficient energy management initiatives. Advanced Metering Infrastructure (AMI) is one of the technologies being developed as a smart metering infrastructure. AMI consists of systems and networks, which are responsible for collecting and analyzing data received from smart meters. In addition, AMI also manages various electricity-related applications and services based on data collected from smart meters. The implementation of AMI has been proven to provide various positive results for both energy service providers and consumers. AMI is able to increase the accuracy of energy consumption recording by up to ±0.5% and reduce billing errors by up to 95%. Therefore, AMI plays an important role in the smooth functioning of the smart grid. In developing AMI technology, of course, there are challenges. Therefore, this paper provides an overview of smart metering technology, its design requirements, protocols and challenges, and policy issues.
Integrasi Data Science dan AI untuk Optimalisasi Layanan Pemerintahan: Literatur Review Kadek Dwi Mahardika Adnyana; I Made Oka Widyantara; NMAED Wirastuti; Ida Bagus Gede Manuaba
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Indonesia’s digital government agenda establishes a policy backbone for data-driven and AI-enabled public services through the national Electronic-Based Government System (SPBE) and the One Data policy, while the Personal Data Protection Law (PDP) frames privacy-by-design obligations for public institutions. Building on international guidance (OECD’s G7 Toolkit; World Bank’s GovTech Maturity Index), this review synthesizes how Data Science (DS)—via reliable feature engineering and descriptive–predictive analytics—can be aligned with Artificial Intelligence (AI) for automation and decision support under public-sector accountability requirements. We identify recurrent enablers (interoperable data architecture, data governance, civil service capabilities, and MLOps) and barriers (data silos, legacy constraints, skills gaps, and explainability/ethics demands), and propose evaluation indicators that link model performance to service performance: service latency reduction, service quality, model fairness, and explainability. The contribution is a systems view that connects SPBE/Satu Data/PDP compliance to DS–AI operations across the lifecycle (governance ? pipeline/feature store ? training/validation ? deployment ? MLOps & audit), and a graduate-level research agenda on causal impact and federated collaboration across agencies.
The Evolution of Weather-Based Deep Learning in Smart Irrigation: A Systematic Review of Sustainable Approaches and Perspectives Rahayu, Andri Ulus Rahayu; Linawati, Linawati; Sastra, Nyoman Purta; Ida Bagus Gede Manuaba
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 8 No. 1 (2026): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v8i1.285

Abstract

This paper presents a systematic literature review of 191 peer-reviewed studies that link short-term weather information with learning based forecasting and control in irrigation or related applications, focusing on 191 peer-reviewed studies published between January 2020 and early 2025, with four foundational studies published prior to 2020 included via backward citation tracking. The review follows a PRISMA-inspired protocol, with database searches in Scopus, IEEE Xplore, and Web of Science, clear inclusion and exclusion criteria, and structured data extraction on the application domain, sensing and IoT architecture, forecasting models, reinforcement learning algorithms, and reported performance metrics. The results show that deep learning models, especially CNN, LSTM, and their hybrids, are frequently used for short-term environmental prediction and typically outperform classical machine learning baselines. Almost 50 studies employ reinforcement learning or deep reinforcement learning, but only five (≈2.6% of the full corpus) apply these methods directly to irrigation control, while most DRL applications appear in energy and smart-grid management. Around a quarter of the corpus explicitly implements IoT architectures, yet very few systems integrate IoT with reinforcement learning in a closed loop at the edge or fog. Sustainability-related outcomes, such as water use, energy savings, costs, and emissions, are mentioned, but they are not consistently quantified using comparable metrics. The review provides a structured mapping of methods and architectures, clarifies how existing work is fragmented across domains, and highlights open opportunities for developing weather-aware, IoT-enabled, and sustainability-oriented reinforcement-learning frameworks for smart irrigation.
Co-Authors A.A Ngurah Amrita Abdurrahman Sayudi Anak Agung Gede Maharta Pemayun Asep Andang Ayu Rahmawati Devanka Arya Levin Dewa Ayu Sri Santiari Dwi Suryadewi Gede Patrianaya Margayasa Wirsuyana Gede Patrianaya Margayasa Wirsuyana I Dewa Nyoman Anom Manuaba I G.N. Ayrthon Senapati I Gede Bayu Suarsa I Gede Ketut Ari Wirawan I Gusti Ngurah Gede Agung Suniantara I Made Agus Artha Putra I Made Anggi Wahyudi Artha I Made Mataram I Made Oka Widyantara I Made Suartika I N Satya Kumara I Nyoman Wira Mastika I Putu Riasa I Wayan Eka Krisna Putra Indra Sukadiana Putra Jonatan Sinurat Kadek Dwi Mahardika Adnyana Lie Jasa Linawati . Linawati Linawati Made Dika Nugraha Made Sudarma Ngurah Narendra Dananjaya NMAED Wirastuti Putu Arya Mertasana Rahayu, Andri Ulus Rahayu Rukmi Sari Hartati Sastra, Nyoman Purta Sylvi Oktavia Ginting Tjok Gede Indra Partha