Majalah Ilmiah Teknologi Elektro (MITE) is peer review journal, published twice a year by the Study Program of Magister Electrical Engineering, Faculty of Engineering, Universitas Udayana. This journal discusses the scientific works containing results of research in the field of electrical, include power systems, telecommunications, informatics, and electronics. Authors are expected to include original scientific papers in accordance with the scope of the discussion of this journal including all aspects of the theory and practice are used.
Study Program of Magister Electrical Engineering
Jurnal MITE 1 (Majalah Ilmiah Teknologi Elektro) Universitas Udayana menggunakan lisensi akses terbuka Creative Commons Attribution 4.0 International (CC BY 4.0 International).
Cover MITE Vol 25 No 1 (jan-juni) 2026
Copyright (c) 2026 lie Jasa (Author) https://creativecommons.org/licenses/by/4.0
Reliability Analysis of a 20 kV Distribution System Using the Failure Mode and Effect Analysis (FMEA) Method on MKN02 and MKN12 Feeders at UP3 Surakarta
The reliability of electric power distribution systems is a critical factor in ensuring service continuity to customers. A reliable distribution system is capable of minimizing both the frequency and duration of interruptions, thereby maintaining the quality of electricity delivery. The MKN02 and MKN12 feeders at Mangkunegara Substation, UP3 Surakarta, are part of a 20 kV distribution network that serves a relatively large load, making them susceptible to disturbances that may affect the quality and continuity of power supply. This study aims to analyze the reliability level of the 20 kV distribution system on the MKN02 and MKN12 feeders using the Failure Mode and Effect Analysis (FMEA) method. FMEA is employed to identify potential failure modes in distribution system components and to evaluate their impacts on system performance and reliability. Failure analysis is conducted by calculating component failure rates based on reliability standards, namely SPLN No. 59 of 1985 and IEEE Std 1366. The research methodology includes a literature review, collection of technical network data, identification of components and failure modes through FMEA tables, and calculation of reliability indices, including SAIDI, SAIFI, CAIDI, ASAI, and ASUI. The results of this study are expected to provide an overview of the reliability level of the analyzed feeders and serve as a basis for improving the reliability of the 20 kV distribution network at Mangkunegara Substation.
Copyright (c) 2026 Fitri Puspasari, Kristina Wulandari (Author) https://creativecommons.org/licenses/by/4.0
Rancang Bangun Prototipe Sistem Pengusir Burung Cerdas (Smart Bird Deterrent) di Area Airside Bandara Internasional I Gusti Ngurah Rai, Kabupaten Badung, Bali
Bird strike incidents in airport airside areas pose a high-risk safety threat. Current conventional mitigation efforts rely on open-loop acoustic alarm devices that operate continuously for 24 hours. This method causes massive electrical energy waste and triggers habituation phenomena in target wildlife. This research aims to design a smart bird deterrent system prototype based on artificial intelligence utilizing a closed-loop control architecture. The methodology integrates the YOLOv8 Nano computer vision algorithm as a visual feedback sensor unit, deployed on low-end Edge AI computing (Intel Celeron N3350). To prevent CPU computational bottlenecks, the model is optimized into an Intermediate Representation format using Intel OpenVINO. The audio actuator trigger signal is strictly executed only when the bird detection accuracy exceeds a 0.5 confidence threshold. Test results indicate that the algorithm dynamically responds to wildlife presence, precisely halting audio emissions when the area is clear, effectively solving the habituation problem. The OpenVINO framework optimization successfully accelerated the image processing computational rate from 0.80 FPS to a stable 1.30 FPS. The system proved reliable with a 0.77-second response latency, offering an innovative control engineering output for energy efficiency in aviation facilities.
Copyright (c) 2026 I Kadek Rika Artawan, Lie Jasa (Author) https://creativecommons.org/licenses/by/4.0
Pemanfaatan Local Large Language Model dalam Software Effort Estimation Menggunakan Metode LOOCV
Software Effort Estimation (SEE) in the early stages of a project is generally confronted with minimal technical specifications and high ambiguity in requirement documents. Large Language Models (LLMs) offer the potential to automate information extraction from unstructured natural language text. This exploratory study evaluates the standalone performance of a local LLM (Phi-3 Mini architecture) in predicting man-days effort using a within-company historical dataset from a local digital agency. The experiment was conducted using the Leave-One-Out Cross-Validation (LOOCV) method to ensure objective evaluation within a limited data population. Model optimization utilized Chain-of-Thought (CoT) prompt engineering combined with a methodological strategy of few-shot selection based on boundary distribution (Min, Median, Max) to serve as cognitive anchors. Qualitative analysis proves that the LLM possesses high semantic intelligence in evaluating relative project complexity. However, quantitative evaluation using MMRE, PRED(25), and Coefficient of Determination (R-squared) indicates fundamental limitations in standalone mathematical regression. The model achieved an MMRE of 0.6963 and a PRED(25) of 0.25, performing below the Mean Baseline (MMRE 0.44) with a negative R-squared of -2.038. These results confirm that while LLMs are proficient in understanding context, they struggle with precise numerical interpolation. Consequently, this study recommends a hybrid estimation framework for future research, positioning the LLM purely as a qualitative feature extractor for conventional Machine Learning algorithms to produce robust and precise estimation accuracy.
Copyright (c) 2026 Diyan Sueka Buana Putra, Dewa Wiharta, Widyadi Setiawan, Ida Bagus Gede Manuaba (Author) https://creativecommons.org/licenses/by/4.0
Model Validasi Lokasi Multi-Lapisan Berbasis QR Code dan Geotagging pada Sistem Perjalanan Dinas Mobile
This study proposes a multi-layer location validation model based on QR Code and geotagging for mobile-based official travel systems to address the limitations of single-parameter validation approaches that are vulnerable to location manipulation. The proposed model integrates spatial validation through geotagging, temporal validation through timestamp recording, device integrity validation through mock location detection, and final-state validation using QR Code as a data encapsulation mechanism. The system was implemented in the ePerjadin mobile application within the BMKG environment and evaluated using functional suitability, security, and performance efficiency testing. The results show that all functional components operated successfully with a 100% success rate, while the system effectively detected location spoofing attempts through mock location validation. Performance evaluation indicates that the average GPS acquisition time was 4.03 seconds, QR Code generation required 2.39 seconds, and QR scanning was completed in 0.11 seconds. These findings demonstrate that the proposed multi-layer validation model can improve the reliability, security, and accountability of mobile-based official travel verification without introducing significant performance overhead, making it suitable for high-mobility operational environments.
Copyright (c) 2026 Setiya Purnawan, Gede Sukadarmika, Ngurah Indra ER (Author) https://creativecommons.org/licenses/by/4.0
Implementasi Fuzzy PID untuk Pengendalian Sudut Pitch pada Pesawat Tanpa Awak
Kestabilan sikap terbang (attitude control) pada pesawat tanpa awak (Unmanned Aerial Vehicle/UAV), khususnya pada sumbu pitch, merupakan aspek penting yang menentukan keberhasilan sistem penerbangan. Pengendali Proportional Integral Derivative (PID) konvensional dengan parameter tetap memiliki keterbatasan dalam menghadapi karakteristik sistem yang bersifat nonlinier dan gangguan eksternal, sehingga berpotensi menghasilkan respons yang lambat, overshoot, dan osilasi. Penelitian ini bertujuan mengimplementasikan pengendali Fuzzy PID berbasis inferensi Mamdani untuk melakukan penalaan (auto-tuning) parameter <!-- [if gte msEquation 12]><m:oMath><m:sSub><m:sSubPr><m:ctrlPr></m:ctrlPr></m:sSubPr><m:e><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="bi"/></m:rPr>K</m:r></m:e><m:sub><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="bi"/></m:rPr>p</m:r></m:sub></m:sSub></m:oMath><![endif]--> <span lang="EN-AU" style="font-size: 12.0pt; line-height: 115%; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: 'Times New Roman'; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; position: relative; top: 3.0pt; mso-text-raise: -3.0pt; mso-ansi-language: EN-AU; mso-fareast-language: EN-ID; mso-bidi-language: AR-SA;"> , <!-- [if gte msEquation 12]><m:oMath><m:sSub><m:sSubPr><m:ctrlPr></m:ctrlPr></m:sSubPr><m:e><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="bi"/></m:rPr>K</m:r></m:e><m:sub><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="bi"/></m:rPr>i</m:r></m:sub></m:sSub></m:oMath><![endif]--> <span lang="EN-AU" style="font-size: 12.0pt; line-height: 115%; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: 'Times New Roman'; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; position: relative; top: 2.5pt; mso-text-raise: -2.5pt; mso-ansi-language: EN-AU; mso-fareast-language: EN-ID; mso-bidi-language: AR-SA;"> , dan <!-- [if gte msEquation 12]><m:oMath><m:sSub><m:sSubPr><m:ctrlPr></m:ctrlPr></m:sSubPr><m:e><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="bi"/></m:rPr>K</m:r></m:e><m:sub><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="bi"/></m:rPr>d</m:r></m:sub></m:sSub></m:oMath><![endif]--> <span lang="EN-AU" style="font-size: 12.0pt; line-height: 115%; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: 'Times New Roman'; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; position: relative; top: 2.5pt; mso-text-raise: -2.5pt; mso-ansi-language: EN-AU; mso-fareast-language: EN-ID; mso-bidi-language: AR-SA;"> secara adaptif pada sistem kendali sudut pitch pesawat tanpa awak tipe FT-Explorer. Sistem diimplementasikan menggunakan mikrokontroler Teensy 3.5 dengan masukan berupa error dan delta error, serta menggunakan basis aturan (rule base) sebanyak 49 aturan (7x7) dan metode weighted average pada proses defuzzifikasi. Evaluasi dilakukan melalui pengujian terbang dan dibandingkan dengan pengendali PID konvensional berdasarkan parameter overshoot, rise time, settling time, dan steady-state error. Hasil pengujian menunjukkan bahwa pengendali Fuzzy PID menghasilkan rise time sebesar 0,8 detik, overshoot sebesar 3,14°, settling time sebesar 3,3 detik, dan steady-state error sebesar 0,24°, lebih baik dibandingkan PID konvensional yang menghasilkan rise time 2,5 detik, overshoot 5,19°, settling time 7,7 detik, dan steady-state error −0,90°. Hasil tersebut menunjukkan bahwa Fuzzy PID mampu meningkatkan kecepatan respons, kestabilan, dan kemampuan adaptasi sistem sehingga lebih efektif diterapkan pada pengendalian sudut pitch pesawat tanpa awak. .
Copyright (c) 2026 Try Susanto, Jihad Caesar Pratama (Author) https://creativecommons.org/licenses/by/4.0
Design and Development of an IoT-Based Seaweed Drying Prototype with a Hybrid Solar PV and Grid Power System for Seaweed Farmers at Geger Beach, Nusa Dua, Bali
Seaweed (Eucheuma cottonii) is one of Indonesia’s leading aquaculture commodities with high economic value. However, the post-harvest drying process still relies on conventional sun-drying methods, making production highly dependent on weather conditions and requiring a long drying duration. This study aims to design and develop a prototype seaweed dryer based on the Internet of Things (IoT) integrated with a hybrid energy system combining Solar Power Plants (PV) and the utility grid (PLN). The system utilizes an ESP32 microcontroller, DHT22 sensor, soil moisture sensor, and Automatic Transfer Switch (ATS) to ensure continuous operation. Monitoring data are displayed through Blynk, LCD, and Google Spreadsheet in real time. The prototype has a maximum capacity of 250 grams of wet seaweed. Experimental results show that the drying chamber temperature can be maintained within the range of 58–59°C while reducing air humidity from 45% to 30%. The drying process successfully reduced the seaweed weight from 250 grams to approximately 41 grams within 4 hours until reaching the target moisture content of 35%. The hybrid energy system employing a 120 Wp solar panel and a 100 Ah battery provided stable power supply during operation. The proposed system offers an effective solution to improve drying efficiency, maintain product quality, and reduce dependence on weather conditions for coastal seaweed farmers.
Copyright (c) 2026 Ve Mas Danuarta, Imam Anshari, I Putu Bagus Putra Pratama, Cokorde Gede Indra Partha, Lie Jasa (Author) https://creativecommons.org/licenses/by/4.0
A Decision Support System for Credit Granting Using the Simple Additive Weighting (SAW) Method
CodeArtisan Auto Finance is a rural savings and loan institution whose creditworthiness assessment process is still performed manually through document verification, field surveys, and subjective evaluation. This process requires one to five days and increases the risk of human error. This study applies the Simple Additive Weighting (SAW) method within a Decision Support System (DSS) to improve the speed and accuracy of credit decision-making. The proposed system evaluates prospective customers based on ten criteria: collateral, loan term, domicile status, employment status, social obligations, relationship with savings products, loan amount, expenditure-to-income ratio, planned installment-to-income ratio, and credit history. Evaluation on 37 historical customer records achieved an accuracy of 81.08%, precision of 90.32%, and recall of 87.50%, demonstrating that the SAW method provides objective and consistent creditworthiness recommendations. Therefore, the implementation of the SAW method can support faster, more transparent, and reliable credit decision-making at CodeArtisan Auto Finance.
Copyright (c) 2026 Adi Panca Saputra Iskandar, Anak Agung Gede Oka Kessawa Adnyana, Lely Meilina (Author) https://creativecommons.org/licenses/by/4.0
Beta Wave Responses in T3 and T4 EEG Channels to Product Packaging Visualization in Neuromarketing
Abstract— Conventional marketing research often suffers from bias. While neuromarketing offers a solution using Electroencephalography (EEG), existing studies typically evaluate product packaging as a holistic stimulus and have not yet unraveled the neural processes behind each design element. This study aims to analyze the functional asymmetry of the temporal lobes (channels T3 and T4) and the involvement of Beta waves 12–30 Hz when consumers evaluate packaging. Using an Ultracortex Mark IV headset, brain activity from 25 participants was recorded while viewing packaging images categorized as "attractive" or "unattractive," which were validated through an initial questionnaire of 60 respondents. Data were extracted using the Python-based Power Spectral Density (PSD) method. The quantitative results showed that attractive packaging consistently triggered the highest surge in average Beta-band PSD across both channels. A clear functional asymmetry emerged through the dominance of the T4 channel (Right Temporal), which reached 0.251 μV2/Hz as the right brain processes non-verbal information, aesthetics, colors, logos, and graphic layouts. Concurrently, the T3 channel (Left Temporal) was active at 0.201 μV2/Hz to support logical-verbal processing when digesting textual product information. The output of this study proves that attractive packaging increases the reconstruction of spatial visualization in the consumer's mind through a recurrent feedback mechanism before a decision is made.
Copyright (c) 2026 Jauzaa Maylia Suhendro, Ni Wayan Nanik Suaryani Taro Putri, I Gede Putu Krisna Juliharta, Ni Putu Noviyanti Kusuma (Author) https://creativecommons.org/licenses/by/4.0
CASCARA (Clean Aquatic Surface Collector And Robotic Assistant) with Solar Panel Utilization and Remote Control System Equipped with Conveyor
Floating inorganic waste in surface waters such as rivers, lakes, and reservoirs remains a challenging environmental problem. This study aims to design and evaluate CASCARA (Clean Aquatic Surface Collector and Robot Asistant) as a surface waste collection boat utilizing solar panels and a remote control system. The research method includes a literature review, boat design and fabrication, system integration, and operational testing. The boat is equipped with a conveyor for waste collection, a load cell sensor to monitor waste load, a TDS sensor to observe water quality, and a remote control system for operation. Testing was conducted in calm lake conditions and reservoir areas with low water flow. The results show that the boat can accommodate waste loads up to 20 kg, while the load cell sensor achieved an average error of 0.59% with R² = 0.9998, the TDS sensor produced stable readings with an average of 317.4 ppm, and the LiFePO₄ battery system operated for 138 minutes with 94.3% efficiency. Furthermore, the boat achieved a stable RF control range of 82 m, maximum range of 105 m, travel distance of approximately 5.1 km per charging cycle, and real-time IoT monitoring accuracy of 99.4%, indicating that CASCARA can operate effectively and sustainably for low-flow aquatic waste cleaning applications.
Copyright (c) 2026 Mawarita Salsabila, Muhammad Sanda Prayoga, Rifki Hadi Purnama, Mochammad Wirangga Syahputra, Albert Gifson Hutajulu (Author) https://creativecommons.org/licenses/by/4.0
Studi Susut Daya dan Tegangan pada Penyulang Rijali Kota Ambon
Sistem distribusi tenaga listrik memegang peranan penting dalam menjaga kualitas penyaluran energi listrik kepada konsumen. Salah satu parameter utama yang menentukan kualitas sistem distribusi adalah besarnya rugi daya dan susut tegangan pada jaringan distribusi primer. Penelitian ini bertujuan untuk menganalisis rugi daya, rugi tegangan, serta Metode penelitian menggunakan pendekatan analisis perhitungan teoritis berbasis parameter impedansi saluran, meliputi tahanan, reaktansi, panjang penghantar, arus beban, dan faktor daya pada setiap segmen penyulang. Penelitian ini juga mengevaluasi profil tegangan jaringan dan tingkat efisiensi penyaluran berdasarkan standar SPLN 72:1987. Data penelitian diperoleh dari dokumentasi teknis dan data operasi PLN UP3 Ambon. Hasil penelitian menunjukkan bahwa total rugi daya semu pada penyulang OG_RIJALI sebesar 91,35 kVA, rugi daya aktif sebesar 50,01 kW, dan rugi daya reaktif sebesar 76,44 kVAr dengan total daya tersalur sebesar 8.112 kVA. Persentase rugi daya aktif terhadap total daya hanya sebesar 0,77%, sedangkan rugi daya semu sebesar 1,13% dan rugi daya reaktif sebesar 1,57%, yang masih berada di bawah batas rugi teknis jaringan distribusi menurut standar SPLN. Penurunan tegangan terbesar terjadi pada segmen awal penyulang akibat arus beban yang tinggi, namun profil tegangan seluruh bus masih berada pada batas toleransi ±5% dari tegangan nominal 20 kV. Penelitian ini memberikan kontribusi berupa evaluasi efisiensi distribusi berbasis profil rugi daya aktual pada jaringan distribusi Kota Ambon serta rekomendasi teknis untuk peningkatan efisiensi jaringan melalui optimalisasi penampang konduktor, penyeimbangan beban antar fasa, dan kompensasi daya reaktif [20].
Copyright (c) 2026 Vicky Salamena, Soleman Sesa, Pelpinus Sinay (Author) https://creativecommons.org/licenses/by/4.0
Classification Of Kidung Dewa Yadnya Using A Combination Of MFCC And KNN Methods
Kidung Dewa Yadnya is a sacred Balinese vocal art that plays a vital role in Hindu religious ceremonies. However, its existence faces serious challenges in the modern era. Globalization and the dominance of popular culture among the younger generation tend to shift their attention away from local music and traditions due to a preference for modern genres better known through digital media. This puts traditional culture at risk of declining interest and sustainability without appropriate documentation or revitalization strategies. Therefore, this study aims to develop a classification system for Kidung Dewa Yadnya using digital signal processing and artificial intelligence approaches. The Mel-Frequency Cepstral Coefficients (MFCC) method is used to extract acoustic characteristics from sound signals because of its ability to represent human auditory perception. The MFCC process includes pre-emphasis, framing, windowing, fast fourier transform, mel filter bank, discrete cosine-transform, and cepstral lifting stages. The extracted feature vectors are used as input for the K-Nearest Neighbor (KNN) algorithm for classification. The research data were obtained from voice recordings of Kidung Dewa Yadnya singers in .wav format. The test results showed the highest accuracy of 81.25% at k = 1 and k = 2, with an average accuracy above 78%. This value indicates that the combination of MFCC and KNN methods is effective in recognizing the acoustic patterns of kidung. This research is expected to support the preservation of Balinese culture through the digitization of kidung and serve as a basis for the development of an artificial intelligence-based traditional music classification system.
Copyright (c) 2026 Prawira Adhisastra, Gede Sukadarmika , Fajar Purnama (Author) https://creativecommons.org/licenses/by/4.0
Sistem Deteksi Lokasi Kebocoran Pipa Distribusi Air Menggunakan Analisis Pola Aliran Multi-Node Berbasis Protokol MQTT
This preliminary study presents a prototype of an Internet of Things (IoT)-based leak detection system for water distribution pipelines. Water loss in conventional networks can reach 20–50% due to delayed response. This research aims to design a prototype that monitors flow rate patterns from multiple pipeline points to identify leak locations based on deviations from normal flow. The system integrates ESP32 microcontrollers and flow sensors across four nodes, transmitting data in real-time to a PHP-based graphical interface via the MQTT protocol. Controlled experiments were conducted using a small-scale prototype with two simulated leak points. Unlike conventional systems that solely rely on monitoring, this architecture implements a closed-loop control mechanism for automated mitigation. Test results show the system successfully localized leaks with a 100% success rate across 13 simulated scenarios without any false positives. Hydraulic anomalies, characterized by increased flow at the sensor before the leak point (due to pump compensation) and a drastic flow reduction at the sensor after the leak point, proved to be effective localization parameters. Communication system evaluation recorded data transmission operating with <1-second latency and 0% data loss. Furthermore, the automated mechanism successfully executed the pump shutdown command (relay off) within 1-2 seconds after a leak was detected. These results confirm the reliability of the proposed architecture in rapidly minimizing water loss. Future research will focus on field testing, sensor optimization, and the development of predictive models.
Copyright (c) 2026 Diky Zakaria, Mahmudah Salwa Gianti, Hanif Aidil Rachman, Muhamad Rifai Ayatulloh, Farah Aulia Kirana, Aulia Aufa Zahron (Author) https://creativecommons.org/licenses/by/4.0
Copyright (c) 2026 Majalah Ilmiah Teknologi Elektro https://creativecommons.org/licenses/by/4.0
Analisis Akurasi Sensor PZEM-004T dalam Pengukuran Tegangan dan Arus Listrik pada Sistem ATS-AMF Berbasis IoT
Energi listrik merupakan kebutuhan vital dalam mendukung operasional sistem berbasis Internet of Things (IoT), khususnya pada sistem monitoring dan pengalihan sumber daya listrik seperti Automatic Transfer Switch–Automatic Main Failure (ATS-AMF). Akurasi pengukuran parameter listrik, terutama tegangan dan arus, menjadi faktor penting untuk menjamin kestabilan sistem, keamanan perangkat, serta efisiensi penggunaan energi. Penelitian ini bertujuan untuk menganalisis tingkat akurasi sensor PZEM-004T dalam mengukur tegangan dan arus listrik pada sistem monitoring berbasis IoT. Metode penelitian dilakukan dengan membandingkan hasil pembacaan sensor PZEM-004T terhadap alat ukur konvensional berupa AVO meter digital pada berbagai kondisi beban operasional di lingkungan perkantoran. Sensor diintegrasikan dengan mikrokontroler Wemos D1 R32 dan sistem monitoring berbasis aplikasi Blynk untuk memperoleh data secara real-time. Pengujian dilakukan pada dua sumber daya listrik, yaitu PLN dan genset, dengan pengambilan data secara berulang untuk memperoleh nilai deviasi dan persentase error pengukuran. Hasil pengujian menunjukkan bahwa rata-rata pengukuran tegangan menggunakan sensor PZEM-004T sebesar 224,34 V, sedangkan alat ukur konvensional menunjukkan 224,82 V dengan rata-rata error sebesar 0,214%. Pada pengukuran arus, sensor mencatat nilai maksimum sebesar 11,3 A, sementara alat ukur konvensional mencatat 11,8 A, dengan rata-rata error sebesar 3,84% dan error tertinggi sebesar 4,55%. Nilai error tersebut masih berada dalam batas toleransi untuk aplikasi monitoring non-industri. Berdasarkan hasil tersebut, sensor PZEM-004T dinyatakan cukup andal untuk digunakan pada sistem monitoring kelistrikan berbasis IoT, khususnya pada aplikasi rumah tangga hingga skala menengah, meskipun kalibrasi tambahan tetap diperlukan untuk aplikasi dengan tuntutan presisi tinggi.
Copyright (c) 2026 Prananda Suni Veda, I Gede Dyana Arjana, I Made Suartika, Anak Agung Gede Maharta Pemayun (Author) https://creativecommons.org/licenses/by/4.0
Rancang Bangun Perangkat Otonom, Detektor Mutu, dan Pisau Ganda Berbasis IoT untuk Optimalisasi Kinerja Traktor Roda Dua Konvensional
The issue of limited human resources in the agricultural sector, particularly in terms of labor availability, has led to increased operational costs and decreased harvesting efficiency. On the other hand, existing IoT-based tractors are generally large-scale and expensive, making them inaccessible to smallholder farmers. To address this challenge, this study proposes the development of a modular attachment for conventional two-wheeled tractors. The device is designed to be efficient, affordable, and capable of minimizing dependence on human labor without requiring the replacement of the main tractor unit. The proposed solution includes a dual blade system (for both tilling and harvesting), a harvest quality detection system, and IoT-based autonomous navigation. All components are integrated into a single functional module that can be attached to existing two-wheeled tractors owned by farmers. This approach eliminates the need to purchase a new tractor, as the innovation enhances the functionality of equipment already in use. Additional advantages include the installation of a mechanical counterweight to stabilize the tractor during operation and the integration of quality detection capabilities, which improve efficiency by enabling simultaneous harvesting and quality monitoring. This study demonstrates that transforming conventional tractors into semi-autonomous systems can significantly enhance labor efficiency, harvesting precision, and reduce operational costs. The innovation offers a sustainable approach to agricultural modernization through the integration of modular technology and IoT, tailored for small to medium-scale farming.
Alat Pendeteksi Gangguan Dini Berbasis Suhu Pada Marshalling Kiosk Di Gardu Induk Menggunakan Media Informasi SMS
Pada Gardu Induk terdapat Marshalling Kiosk yang berfungsi sebagai kontrol peralatan di Gardu Induk apabila dispatcher dan kontrol lokal gagal melakukan manuver, karena pada panel ini terdapat banyak sambungan serta komponen yang digunakan sebagai kontrol berpotensi terjadi overheat pada panel karena disipasi panas ataupun sistem pendingin rusak dimana berdasarkan IEC 61439 batas ambient temperatur yang diizinkan ialah 40°C, dan dapat terjadi gangguan lain berupa api yang dapat diakibatkan High Resistance Connection (HRC) karena sambungan longgar, gangguan – gangguan tersebut dapat menggangu saat manuver peralatan. Saat ini PT PLN belum memiliki alat yang mampu mendeteksi adanya gangguan pada panel Marshalling Kiosk oleh sebab itu pada penelitian ini dibuat alat yang mampu mendeteksi adanya gangguan berupa suhu menggunakan LM35, api menggunakan sensor api 5 channel, dan asap menggunakan sensor MQ2 pada Marshalling Kiosk dengan media informasi SMS dan lampu indikator sebagai penunjuk jenis gangguan serta buzzer sebagai alarm.
Copyright (c) 2026 Putu Agus Mahadi Putra, Moch. Reza Naufal Ifandar, Kadek Amerta Yasa, I Made Purbhawa, Farid Dwi Murdianto Murdianto, Andhik Ampuh Yunanto, Luki Septya Mahendra, Mochammad Machmud Rifadil (Author) https://creativecommons.org/licenses/by/4.0
Evaluasi Aplikasi Blynk Dalam Monitoring Perpindahan Suplai Daya dan Logging Tegangan Berbasis IoT Pada Sistem ATS-AMF
Reliability of electricity supply is crucial for ensuring the continuity of company operations, particularly for server systems. This research designed a prototype IoT-based Automatic Transfer Switch (ATS) and Automatic Main Failure (AMF) system integrated with the Blynk application. The goal was to test whether the Blynk application could monitor power supply switching and automatically store voltage data using the Blynk Cloud Data Logger. This system was developed using a WeMos D1 R32 microcontroller and a PZEM-004T sensor to measure voltage and current from two sources: the state electricity company (PLN) and a generator. Measurement data was displayed in real time in the Blynk application and recorded to the cloud. Testing was conducted over 14 days at one-hour intervals, during which the system was tested under both automatic and manual switching conditions. The results showed that the Blynk application could display power supply switching status with a fast response and accurately log voltage data. This demonstrates the effectiveness of Blynk as a cloud-based monitoring and data logging tool in the IoT-based ATS-AMF power supply system
Rancang Bangun Sistem Monitoring Kecepatan Pada Kapal Trimaran Menggunakan Pixhawk
Indonesia as a maritime nation with vast and strategic oceanic territory, continues to develop efficient and innovative ship technologies. This research focuses on the design and construction of a speed monitoring system for a trimaran vessel using the Pixhawk controller. The system integrates a Pixhawk autopilot unit as the main controller, an STM32 microcontroller for processing, dual BLDC motors, an internal combustion engine (ICE), and a remote control system. The Internet of Things (IoT) platform is employed for real-time data logging and monitoring. Experimental tests were conducted on five reference speed levels slow patrol, reconnaissance, medium patrol, cruising, and chase modes. Quantitative results show that the system achieved rapid response times at medium speeds, with stable operation and an average delay below 0.5 seconds. At high speeds, however, stability decreased by 15–20% due to environmental and load variations. Remote control communication maintained stable performance up to 210 meters with obstructions and 280 meters without obstacles. The results demonstrate that the system effectively supports real-time speed monitoring for trimaran vessels. The novelty of this study lies in the integration of hybrid propulsion and adaptive control within an IoT-based Pixhawk monitoring system, contributing to advancements in smart maritime technology.
Review on Impact of Artificial Intelligent on Efficiency and Productivity in Industrial Automation
As Industry 4.0 technologies evolve, the application of Artificial Intelligence (AI) in the manufacturing sector has become a major factor in improving operational efficiency, optimizing production processes, and reducing costs, enabling predictive analytics, data-driven maintenance, and automation of tasks that previously required human intervention. This study conducts a systematic literature review (SLR) on various AI methods applied in industrial automation, evaluates the effectiveness of their implementation, and identifies key challenges in their adoption. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Population, Intervention, Comparison, Outcome, Context (PICOC) approaches are adopted. The sources used to search the literature included four electronic databases, comprising ScienceDirect, Taylor & Francis, Scopus, and Emerald Insight, resulting in 33 selected articles. The result shows that AI contributes significantly to improving production efficiency, but it still faces challenges in system integration, implementation costs, and workforce readiness. This study provides a comprehensive overview of the effectiveness of AI implementation in industrial automation and the challenges that need to be overcome to optimize competitiveness and production efficiency
Copyright (c) 2025 Majalah Ilmiah Teknologi Elektro https://creativecommons.org/licenses/by/4.0
Pemanfaatan Simulasi Jaringan Komunikasi Vehicle-to-Everything(V2X) untuk Sistem Transportasi Cerdas: Literature Review
The increasing number of vehicles has led to several complex challenges, such as traffic congestion, air pollution, and safety driving issues. These challenges also result in economic losses. Fortunately, with the advance in technologies today, we can utilize Intelligent Transportation Systems (ITS) to establish a system that is more efficient, safer, and environmentally friendly. Specifically, the concept of Vehicle-to-Everything (V2X) has emerged as a potential solution to address various road-related challenges. However, the real-world implementation of V2X still faces numerous obstacles, particularly in terms of cost and safety concerns. Deploying V2X on a large scale requires significant investments due to the need for communication infrastructure and hardware development. Therefore, simulation can serve as an initial solution to tackle these challenges. Simulations make it possible to set up different communication network protocols and architectures and to model different traffic conditions without the risks that come with testing in the real world. In this review paper, we aim to give a clearer insight into the trends, challenges, and opportunities of V2X simulations in various traffic environments.
Smart Vertical Farming: The Role of IoT in Achieving Sustainability and Resource Efficiency
The rapid growth of population and urbanization poses significant challenges to global food security, particularly in urban areas. The conversion of agricultural land into residential and infrastructure zones reduces local food production capacity, while climate change exacerbates uncertainties in crop yields. To address these challenges, IoT-based vertical farming has emerged as an innovative solution to enhance efficiency and sustainability in food production systems. IoT technology enables vertical farming systems to monitor and control environmental variables such as temperature, humidity, lighting, and nutrient levels in real-time through sensors connected to artificial intelligence. The collected data is analyzed to optimize plant growth, minimize resource waste, and maximize crop yields while reducing energy consumption. Additionally, integrating IoT with automated irrigation systems and energy-efficient LED lighting further enhances water and electricity efficiency. From a sustainability perspective, IoT-based vertical farming allows for year-round food production without relying on vast land areas or favorable weather conditions. This research further explores how IoT contributes to improving resource efficiency, environmental sustainability, and the economic and social impacts of vertical farming. . Based on the research findings, the implementation of IoT in vertical farming has proven to be highly beneficial in enhancing sustainability and resource efficiency in urban food production. Through real-time monitoring and automated control systems, IoT enables precise regulation of key environmental factors such as temperature, humidity, lighting, and nutrient levels, ensuring optimal plant growth with minimal resource wastage.
Literature Review: Challenges and Technologies in the Development of Advanced Metering Infrastructure (AMI)
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.
Design and Construction of a Micro-Hydroelectric Power Plant (PLTMH) Prototype Using an Irrigation Channel as a Case Study in Medewi Village, Pekutatan District, Jembrana Regency
Micro Hydro Power (MHP) is a small power plant that uses water to generate electricity. It can be found in irrigation canals, rivers, or waterfalls. The amount of water and head height are important factors in determining the power output. The irrigation canal in Medewi Village is being used as a research location for MHP. Researchers will use the data to perform calculations and design a prototype. They will also conduct an economic analysis of the MHP to determine its feasibility. The discharge at the research location is 0.23 m3/s, and the waterfall is 2.24 m high. Through the calculation results, the researchers determined that the turbine is a crossflow turbine. The turbine power is 3.9 kW, the generator power is 4.375 kVA, and the turbine power in the homer software is 4.195 kW. The cost of building the MHP in the irrigation canals in Medewi Village is IDR20.391.899,26. With a 6% discount rate, the BCR is 1,51, the NPV value is IDR30.827.069, the IRR is 12,3%, and the BEP result per unit The payback period is 1 year 5 months and 2 weeks. Selling 46.585,056 kWh results in an LCC of IDR44.598.314. Using MHP throughout its economic life results in a cost that is less than the price paid to PLN.
Peningkatan Kualitas Sinyal Photoplethysmography (PPG) melalui Pendekatan Pra-pemrosesan Multitahap
Photoplethysmography (PPG) is a non-invasive technique for measuring various physiological parameters, including blood glucose levels. However, PPG signals are often affected by noise and artefacts that reduce the accuracy of analysis and prediction. Therefore, an effective noise filtering method is needed to make the signal quality and ready for feature extraction for blood glucose estimation. This study offers a solution to the problem of noise in PPG signals through the application of appropriate pre-processing methods. This study aims to select quality PPG signals through three pre-processing methods: detrend, smoothing, and 0.5-5 Hz bandpass filter. The effectiveness of the three methods was evaluated through ADF test to measure the stationarity of the signal, frequency spectrum analysis to observe the distribution of frequency components, and SNR test to assess the signal to noise ratio. Based on the analysis of 67 data samples, the p-value <0.05 was obtained, indicating that the signal has reached a stationary condition. In addition, the average test statistic of men is higher than that of women, indicating that men's signals are more stationary after detrend. Meanwhile, 36 samples (54%) had SNR ≥ 20 dB indicating that more than half of the data were of good enough quality for further analysis. The results show that multi-stage pre-processing improves the quality of PPG signals, validated through quantitative tests of stationarity and SNR values. Thus, the preprocessed and improved quality PPG signals are considered feasible for use in the development of estimation models for various physiological parameters, including blood glucose levels.
Design and Construction of an Off-grid Solar Power Plant to Power the Dragon Fruit Garden Lighting in Yosomulyo Village
The sunlight intensity level requirement for dragon fruit plants is more than 90%, which is essential for the photosynthesis process and the morphological development of the plant. This plant is classified as long-day plant, meaning that it requires at least 12 hours or more of sunlight to reproduce. Dragon fruit farmers utilize artificial lighting as an alternative to sunlight to support the plant's biological processes at night. The energy source is conventional electricity from grid (PLN). The design of an off-grid PV system at the Yosomulyo dragon fruit farm is carried out to support the farm's daily electricity needs. The design begins with field observations to obtain geographic data of the farm, daily electrical load profile data with amperes, calculating the PV system capacity, determining PV system components, and testing the performance of the design with PVSyst simulation. The simulation results of the PLTS design are 70.9% with an inverter variation of 6500 W, solar modules of 550 Wp, batteries of 200 Ah 12 V at a system voltage of 48 VDC, and an autonomy day of 1.
Three Phase Sinusoide Output Voltage of Multi Carrier for Nine Level Cascade H-Bridge Inverter with DC Fuel Cell
This paper discusses a cascade inverter 9 three-phase power system using a Cascade H Bridge inverter type with a DC Fuel Cell voltage source. The goal is to reduce the Total Harmonic Distrotion (THD) content in the output waveform in accordance with IEEE 519 standards below 5%. At each level the inverter is supplied by the fuel cell as a DC source and in series with the next level inverter circuit to get 9 output voltage levels. The switch performance of each level is controlled by PWM pulses at the level of different amplitudes but the same frequency. Unlike conventional approaches that rely solely on low-level inverters or fixed DC sources, this study proposes the implementation of a nine-level cascade H-Bridge inverter topology powered by a DC fuel cell with three-phase multi-carrier modulation technique to produce high-quality sinusoidal voltage. This system shows increased efficiency, harmonic reduction, and more optimal utilization of green energy. Simulation results show that the output voltage form of each phase inverter is a 9-level ladder wave with a THD of 13.67%. By installing a low pass filter, the output voltage waveform changes to sinusoidal with and THD can be reduced to 2.92%. The power system with this THD value can still be tolerated to occur in an electric power system
Rancang Bangun Prototype Monitoring Instalasi Pengolahan Air Limbah (IPAL) Di Suwung Berbasis Internet of Things
Wastewater management is a critical component of environmental sustainability, particularly in regions undergoing rapid industrial development such as Bali. The Wastewater Treatment Plant (IPAL) in Suwung plays an essential role in ensuring that effluents meet environmental quality standards mandated by regional and national regulations. However, current monitoring practices at the facility are conducted manually, resulting in potential delays in pollution detection and timely decision-making. This study proposes the design and implementation of an Internet of Things (IoT)-based prototype for real time wastewater quality monitoring. The system integrates multiple sensors-including pH, temperature, turbidity, and water level sensors-controlled by an arduino UNO microcontroller and ESP 32 module. Measurement data are transmitted to Blynk and ThingSpeak platforms in real time, stored in a data logger for further analysis, and made accessible via a web-based monitoring interface. The results demonstrate that the system is capable of delivering accurate and real time data, which can support more efficient monitoring and facilitate timely environmental management decisions. This prototype offers a reliable and scalable solution for digitizing wastewater monitoring processes in treatment facilities
Deteksi Adaptif Titik Kunci Sinyal Photoplethysmography (PPG) dengan Pemodelan Gradien untuk Identifikasi Pola Fisiologis
Abstract— Photoplethysmography (PPG) is a non-invasive optical technique for cardiovascular health monitoring, such as blood pressure estimation and arterial stiffness analysis. However, detecting fiducial points in PPG signals such as the onset, systolic peak, dicrotic notch, and diastolic peak is often hindered by noise, baseline wander, and physiological variability. Although various methods have been proposed, such as time-frequency domain analysis and machine learning algorithms, these approaches still have limitations, including high computational complexity and susceptibility to noise. This study proposes a gradient-based analysis approach to improve the accuracy of fiducial point detection in PPG signals. The gradient method is used to detect local maxima and minima in the PPG signal. By incorporating validation and correction modules based on temporal order and amplitude ratios, the approach achieves 100% detection accuracy after initial error correction (initial error rate: 58% for the dicrotic notch). The results demonstrate that this method effectively identifies all fiducial points (onset, systolic peak, dicrotic notch, diastolic peak) in 50 out of 50 datasets, with robust performance against noise and physiological variability. This study confirms that the gradient-based method is suitable for cost-efficient, portable diagnostic applications.