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All Journal Transmisi: Jurnal Ilmiah Teknik Elektro ELKHA : Jurnal Teknik Elektro Jurnal Sains dan Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Informatika Jurnal Ilmiah Wahana Pendidikan
Manuaba, Ida Bagus Gede
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Sistem Monitoring Dan Kontrol Berbasis Internet Of Things Pada Prototypesmart Portable Biomass Powerplant Muzhaffar, Raihan Faishal; Putra, I Wayan Sri Atma; Brahmananda, A.A. Ngurah Agung Satria; Sudarma, Made; Manuaba, Ida Bagus Gede
Jurnal Informatika Vol 12, No 1 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i1.5444

Abstract

The use of Internet of Things technology can be implemented in various aspects, one of which is the field of energy generation. The generation of electrical energy, especially biomass fuel, can be one way to achieve more environmentally friendly energy generation. Design prototype smart portable biomass powerplant includes monitoring and control of the generating system. The monitoring and control system is designed to be able to run automatically integrated with the Internet of Things system. To increase the ease of use of the tool, the system is connected in real-time with the internet. Data acquisition with sensors connected to the controller is carried out to observe the condition of the combustion chamber, turbine and generator components. The results of this data acquisition can then be monitored in real-time on a platform that can be done remotely. The control process on the prototype includes protection measures on the device in case of fault so as to provide further damage prevention measures and can be done wirelessly using the same system. Prototype testing results using Arduino mega2560 controller and ACS712 current sensor, voltage sensor, MQ-2 gas sensor and esp32 cam were found to be able to work well and monitor both the condition of the combustion chamber, the power generated by the generator to biomass combustion levels. Then the test also proved to be able to provide remote process control to protect the tool from overheating, overcurrent protection and excessive incomplete combustion process.
Analysis of Wind Energy Potential On Nusa Penida Island Using The Weibull Distribution: Evaluation of Power Density and Intermittency Herlambang, Amanda Austin; Dewi Wirastuti, Ni Made Ary Esta; Manuaba, Ida Bagus Gede
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.v17i1.87857

Abstract

Nusa Penida Island faces increasing energy demands driven by tourism and development, highlighting the need for sustainable energy solutions. While previous wind studies in Indonesia have primarily focused on larger islands, this research evaluates Nusa Penida"™s wind energy potential using the Weibull distribution method for power density and intermittency analysis. Unlike prior studies, this research incorporates seasonal variations and probabilistic modeling to provide a more accurate assessment of wind intermittency. Statistical analysis of 2019"“2020 wind speed data from NASA Power reveals stable wind conditions, with an average power density of 104 W/m ², making it suitable for medium scale wind energy projects. Peak wind speeds occur mid year, optimizing conditions for energy harvesting, while intermittency analysis indicates that wind speeds fall below 3 m/s approximately 30% of the time, emphasizing the need for energy storage or hybrid systems. This research quantifies the impact of intermittency on energy planning, offering a data driven approach to support Indonesia"™s renewable energy diversification and reduce reliance on fossil fuels. The findings establish Nusa Penida"™s feasibility for wind energy deployment, contributing to enhanced energy resilience in remote island communities.
Deteksi Motif Tradisional Bali Dengan Algoritma Learning Vector Quantization Kadyanan, I Gusti Agung Gede Arya; Gunantara, Nyoman; Manuaba, Ida Bagus Gede; Saputra, Komang Oka
JST (Jurnal Sains dan Teknologi) Vol. 13 No. 1 (2024): April
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jstundiksha.v12i3.50399

Abstract

Tidak semua orang mengenal motif tradisional yang beragam hanya melalui ciri-ciri yang tampak secara visual. Sering kali mereka salah dalam mengenali motif tertentu, dikarenakan motif yang bervariasi dan hampir serupa. Penelitian ini dilakukan dengan tujuan merancang dan mengimplementasikan sistem informasi deteksi motif kain yang mampu mengenali citra dari kain tenun dengan cepat dan tepat menggunakan algoritma Learning Vector Quantization. Metode yang digunakan dalam penelitian ini adalah metode Learning Vector Quantization untuk proses deteksi motif tradisional Bali dan ekstraksi fitur tepi dengan metode Sobel. Jenis data yang digunakan pada penelitian ini dilihat dari cara memperolehnya adalah data primer. Pada penelitian ini data motif yang digunakan sebanyak 210 citra, dengan citra yang digunakan sebagai data training sebanyak 80% atau 168 citra dan data testing sebanyak 20% atau 42 citra. Data tersebut dibagi menjadi 6 kelas dari masing-masing motif yang digunakan. Teknik pengumpulan data yang digunakan yaitu wawancara dan observasi langsung ke objek penelitian. Teknik pengujian yang digunakan yaitu pengujian akurasi pada algoritma Learning Vector Quantization. Hasil penelitian menunjukkan bahwa sistem yang dibangun mampu melakukan deteksi motif tradisional Bali dengan mengimplementasikan algoritma Learning Vector Quantization dan metode ekstraksi fitur tepi Sobel dimana hasil ekstraksi fitur Sobel berpengaruh terhadap citra yang akan di klasifikasi dan di deteksi.
MPPT CONTROL ALGORITHM BASED ON OPTIMIZATION OF SOLAR SYSTEM UNDER PARTIAL SHADING CONDITION (PSC) Pandawani, Anak Agung Istri; Manuaba, Ida Bagus Gede; Dharma, Agus
Transmisi: Jurnal Ilmiah Teknik Elektro Vol 27, No 4 Oktober (2025): TRANSMISI: Jurnal Ilmiah Teknik Elektro
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/transmisi.27.4.191-200

Abstract

Sistem fotovoltaik memiliki sifat intermiten karena bergantung pada kondisi lingkungan yang dinamis. Oleh karena itu, metode MPPT dikembangkan untuk melacak daya maksimum sehingga dalam kondisi lingkungan yang bervariasi sehingga sistem fotovoltaik dapat memaksimalkan produksinya. Metode tersebut adalah proses identifikasi titik daya maksimum melalui pelacakan yang dapat dilakukan dengan berbagai algoritma yang dikenal sebagai metode MPPT. MPPT menghadapi tantangan selama kondisi lingkungan yang dinamis, seperti ketika terjadi Partial Shading Condition (PSC) di mana panel surya menerima iradiasi yang tidak merata yang dapat menyebabkan kerugian daya dan memengaruhi kinerja panel surya. Selama kondisi PSC, tidak semua algoritma MPPT memiliki kemampuan untuk menemukan titik maksimum yang akurat sehingga algoritma berbasis optimasi digunakan untuk melacak titik daya maksimum secara akurat dan dalam waktu singkat. Makalah ini memberikan tinjauan komprehensif tentang beberapa algoritma MPPT berbasis optimasi dengan menyoroti kemampuan setiap metode dalam hal kecepatan, stabilitas, dan efisiensi di bawah kondisi PSC.
Penerapan Metode Extreme Programming pada Rancang Bangun Sistem Analisis Sentimen Portal Berita Premana Putra, I Gede Bagus; Sudarma, Made; Manuaba, Ida Bagus Gede
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 6: Desember 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023106904

Abstract

Berita dalam bentuk portal online di era globalisasi menjadi suatu wadah yang dapat digunakan oleh setiap individu untuk menyampaikan informasi tentang seorang individu ataupun organisasi, yang didalamnya terdapat penyampaian nilai emosional pribadi, baik itu bersifat negatif, netral, ataupun positif (atau lebih dikenal dengan sentimen). Keberadaan berita tersebut menciptakan suatu peluang untuk pengembangan sistem analisis sentimen terdapat informasi yang telah disampaikan dalam portal berita. Sistem analisis sentimen tersebut dapat dikembangan dengan dengan berbagai teknik dan layanan, salah satunya adalah dengan mengintegrasikan antara sistem dan layanan Google NLP, yang telah memiliki service untuk menentukan score sentimen dari setiap kalimat yang diberikan, serta penerapan teknik web scrapping sebagai metode untuk pengambilan data. Sistem dikembangan dengan framework Laravel dengan metode pengembangan Extreme Programming yang mendukung pengembangan sistem dalam waktu singkat. Pemilihan website sebagai base sistem dengan tujuan agar sistem bisa diakses dari berbagai device baik itu mobile maupun desktop. Keberadaan sistem analisis sentimen bisa dijadikan sebagai alternatif solusi bagi individu dan organisasi untuk melakukan analisis sentimen, sehingga mampu membantu dalam proses pengambilan keputusan maupun evaluasi kinerja.   Abstract News of online portals in the era of globalization has become a forum can be used by every individual to convey information about individual or organization, in which there’s the delivery of personal emotional value, negative, neutral or positive (or better known as sentiment). The existence of news creates an opportunity for development of a sentiment analysis system based on information that has been submitted in the news portal. The sentiment analysis system can be developed using various techniques and services, one of which’s by integrating the Google NLP system and service, which already has a service to determine the sentiment score of each given sentence, as well as the application of a web scrapping techniques as a method for data collection. The system was developed using the Laravel framework with the Extreme Programming development method which supports system development in short time. Selection of the website as the base system with aim that can be accessed from various devices, both mobile and desktop. The existence of a sentiment analysis system can be used as an alternative solution for individuals and organizations to carry out sentiment analysis, so that it can assist in the decision-making a process and performance evaluation.
Analisis Total Harmonic Distortion Terhadap Penambahan Filter Aktif Pada Modified Buck-Boost Inverter Untuk Mengurangi Common Mode Voltage Pada Motor Induksi M, I Gede Mahardika; Pratama, I Putu Indra; Manuaba, Ida Bagus Gede; Partha, Cokorde Gede Indra; Wijaya, I Wayan Arta
Jurnal Ilmiah Wahana Pendidikan Vol 10 No 2 (2024): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.10491842

Abstract

Buck-boost inverter is one tool that can convert Direct Current (DC) voltage into Alternating Current (AC) voltage while simultaneously increasing and decreasing the output voltage. On the other hand, there is a problem with induction motors, namely the presence of Common Mode Voltage (CMV) or the voltage between the neutral point of the motor and ground which can accelerate wear on the bearings and damage to the motor. One method that can reduce CMV is by using an active filter. Another problem due to the use of inverters is that there are harmonics due to the switching process. This research will examine the effect of adding modified BBI plus an active filter to a three-phase induction motor on CMV and THDv. This research process begins with designing a circuit simulation in the MATLAB application, then simulation testing is carried out to see its effect on CMV and THDv values. BBI simulation test results after the addition of active filters with conventional inverter circuit CMV worth 250V with THD worth 6744.45%, while the BBI circuit coupled with active filters worth 22V and THDv worth 114.53%. As well as the BBI circuit plus an active filter, CMV is worth 2.6V with THDv worth 65.30%.
A Systematic Literature Review of Machine Learning for Endurance Running Performance Prediction Solang, Efraim William; Linawati, Linawati; Manuaba, Ida Bagus Gede; Setiawan, I Nyoman
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15743

Abstract

This study systematically reviews the application of machine learning methods for predicting running performance, with particular emphasis on short-middle distance events such as the 5 km. Although machine learning based performance prediction has been widely explored in endurance sports, a comprehensive review synthesizing models, predictors, and pipelines across running distances remains limited. The review followed the PRISMA 2020 framework. Articles published between 2020 and 2025 were retrieved from ScienceDirect, Google Scholar, and PubMed using predefined keyword combinations related to machine learning and running performance. Studies were included if they focused on running (excluding cycling, triathlon, or other sports), applied predictive modeling, and reported model evaluation metrics. A total of 26 studies met the inclusion criteria and were assessed using quality appraisal criteria inspired by TRIPOD and QUADAS-2. The analysis identified four main research themes: (1) application of machine learning models for running performance prediction, (2) physiological and anthropometric predictors, (3) non-physiological and contextual factors, and (4) personalized athlete training and monitoring. Ensemble learning models (Random Forest, XGBoost, LightGBM) consistently outperformed traditional linear regression by capturing non-linear interactions, while deep learning approaches (LSTM, GRU) demonstrated strong capability in modeling temporal training dynamics. A generalized machine learning pipeline for running performance prediction was also synthesized. This review contributes a structured framework that integrates modeling approaches, predictor categories, and evaluation strategies, and highlights research opportunities for explainable and personalized prediction systems, particularly for 5 km running performance.
Co-Authors Agus Dharma Brahmananda, A.A. Ngurah Agung Satria Dewi Wirastuti, Ni Made Ary Esta Herlambang, Amanda Austin I Gusti Agung Gede Arya Kadyanan I Nyoman Gunantara I Nyoman Setiawan I Wayan Arta Wijaya Lie Jasa Linawati Linawati M, I Gede Mahardika Made Sudarma Muzhaffar, Raihan Faishal Pandawani, Anak Agung Istri Pratama, I Putu Indra Premana Putra, I Gede Bagus Putra, I Wayan Sri Atma Saputra, Komang Oka Solang, Efraim William Suryadewi, Dwi Tjok Gede Indra Partha