cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Khamdan Annas Fakhryza
Contact Email
khamdanannasfakhryza@gmail.com
Phone
+628985566531
Journal Mail Official
editor@pulsejeib.edu.eu.org
Editorial Address
Jl. Kartini No. 228, Kel. Ungaran, Kec. Ungaran Barat, Semarang 50511, Central Java, Indonesia
Location
Kab. semarang,
Jawa tengah
INDONESIA
PULSE — Journal of Energy, Informatics & Biomedicine (JEIB)
Published by PT Khamdan Karya Cipta
ISSN : 31235549     EISSN : 31235549     DOI : -
Core Subject :
Secara substansi JEIB menyatakan fokus pada: * energy systems; * informatics; * data science; * artificial intelligence; * biomedical engineering; * original research; * review articles; * applied studies; * practical, interdisciplinary, reproducible contributions.
Arjuna Subject : -
Articles 10 Documents
 1 
IMPLEMENTATION OF K NEAREST NEIGHBORS WITH CROSS VALIDATION AND EUCLIDEAN DISTANCE FOR ELECTRICITY MISUSE PREDICTION AT PLN UP3 DEMAK Retno Supiyanti; Efa Yumna Purwono
PULSE — Journal of Energy, Informatics & Biomedicine Vol 1 No 1 (2025): Inaugural Issue
Publisher : Khamdan Karya Cipta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/0sjskc45

Abstract

Electricity misuse is a critical issue that severely impacts both operational efficiency and revenue within utility companies, particularly in developing regions. This study presents the implementation of the K Nearest Neighbors (K NN) algorithm with cross validation and Euclidean distance metrics to predict electricity misuse in the PLN UP3 Demak area. The analysis focuses on the P2 and P3 customer segments, known for their diverse consumption patterns and higher risk of fraudulent activities. Given the inherent class imbalance in the dataset here instances of misuse are significantly outnumbered by legitimate consumption he Synthetic Minority Over sampling Technique (SMOTE) was applied to improve the model’s ability to detect minority class instances. Our findings reveal that applying SMOTE resulted in a substantial increase in the model’s accuracy, precision, and recall, demonstrating its effectiveness in balancing the dataset. Specifically, the application of K NN with SMOTE showed improved detection of irregular consumption patterns indicative of electricity misuse, which were less discernible in the original imbalanced dataset. The comparative analysis between models trained with and without SMOTE underscored the importance of addressing class imbalance to achieve reliable predictive performance. Furthermore, the study identified distinct behavioral patterns in P2 and P3 customers, which are critical for early detection of potential misuse. These findings were supported by the cross validation results, which confirmed the model's robustness and its capability to generalize well to unseen data. Overall, this research provides valuable insights for utility companies, highlighting the importance of implementing advanced machine learning techniques like K NN with SMOTE to enhance fraud detection capabilities. The study also emphasizes the necessity of continuous monitoring and analysis of customer consumption patterns to proactively identify and mitigate potential misuse
UTILIZATION OF CLUSTERING ALGORITHMS AND ANN IN ENERGY ABUSE DETECTION Sapta Adhi; Aditya Suryadharma
PULSE — Journal of Energy, Informatics & Biomedicine Vol 1 No 1 (2025): Inaugural Issue
Publisher : Khamdan Karya Cipta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/1axwk077

Abstract

Abstract—This research aims to detect energy abuse by utilizing clustering algorithms and Artificial Neural Networks (ANN). The dataset used consists of monthly energy consumption data from customers, which is processed using a combination of preprocessing techniques, clustering, and ANN models. The preprocessing step involves cleaning the data, normalization, and feature extraction to ensure the dataset is suitable for subsequent analysis. Clustering is carried out using the K-Means algorithm to group customers based on their consumption patterns, while the ANN model is used to classify and predict potential cases of energy abuse. The results indicate that the combination of the K-Means clustering algorithm and ANN provides a high level of accuracy in detecting suspicious energy consumption patterns. This approach effectively segments customers with similar consumption behaviors and identifies anomalies that may signify unauthorized energy use. The implementation of this methodology demonstrates its potential for energy providers to efficiently detect and reduce losses due to energy theft, ultimately contributing to improved energy management and distribution. The outcomes demonstrate the model’s scalability for broader deployment within energy distribution systems.
OPTIMIZATION OF 20 KV FEEDER NETWORKS USING THE GAUSS-SEIDEL METHOD TO REDUCE LOSSES AT PLN UP3 SEMARANG Febi Agus Rubiyanto; Khamdan Annas Fakhryza
PULSE — Journal of Energy, Informatics & Biomedicine Vol 1 No 1 (2025): Inaugural Issue
Publisher : Khamdan Karya Cipta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/sbgn6j83

Abstract

The rising demand for electrical energy, driven by population growth and technological advancements, presents challenges for PT PLN (Persero), Indonesia's main electricity provider. One key issue is reducing power losses in the distribution network, which affects both system efficiency and company revenue. This study explores the use of the Gauss-Seidel method for power flow analysis on the 20 kV distribution network at PLN UP3 Semarang, aiming to decrease losses and improve revenue. Using data on line impedance and load from PLN UP3 Semarang, the Gauss- Seidel method is applied via a Python script in Google Colab. The findings show that this method effectively reduces network losses, with potential financial benefits for PLN UP3 Semarang. This research also lays the groundwork for future network optimization strategies and contributes to the field of power flow analysis. The study is focused on the 20 kV network and does not compare the Gauss-Seidel method with other approaches. Growing demand for electricity and the need for reliable distribution motivate continuous improvement of power-flow analysis and loss-reduction strategies in Indonesia’s medium-voltage networks. This paper applies the classical Gauss–Seidel (GS) load-flow to the 20 kV feeders of PLN UP3 Semarang using field parameters (line R/X, substation data, and aggregated loads) and an open computational workflow in Python/Google Colab. We build a Ybus model, adopt the per-unit system, and implement standard GS updates for PQ buses with a practical convergence tolerance. The study evaluates baseline conditions and several optimization scenarios (e.g., modest R/X adjustments reflecting conductor upgrades, improved feeder balancing, and initial-voltage tuning). Results show consistent reduction of technical losses across representative ULPs and at the UP3 level; monthly loss percentages also trend downward during the observation horizon. Voltage profiles improve at non-slack buses while remaining within typical planning limits. The analysis highlights how low- complexity, data-driven GS studies can support day-to-day planning decisions for feeder reconfiguration and targeted reinforcement. We discuss implementation limits (data quality, simplifications, and scenario dependence) and outline follow-up steps, including PV-bus modeling, comparison with Newton–Raphson, and integration with economic screening curves. The findings strengthen the case for using GS-based what-if analyses as a lightweight decision aid for utilities operating medium- voltage distribution networks.
EVALUASI KINERJA BATERAI BERUSIA 10 TAHUN MENGGUNAKAN DATA PENGUKURAN DI GARDU INDUK 150 KV JEPARA Ahmad Shofa; Muhammad Rizky Adi
PULSE — Journal of Energy, Informatics & Biomedicine Vol 1 No 1 (2025): Inaugural Issue
Publisher : Khamdan Karya Cipta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/d05vgv81

Abstract

Batteries serve as a crucial backup direct current (DC) source in substations, especially during power outages (blackouts). The reliability and lifespan of these batteries are critical factors in ensuring the continuous operation of the system. This study analyzes the performance of 110 VDC NiCd (Nickel-Cadmium) alkaline batteries at the Jepara 150 kV Substation, which have been in operation for over 10 years. This research is relevant given that the replacement criteria for substation batteries typically range from 10-15 years. This study employs a comparative method using discharging data collected in 2018 and 2020. The results show that while the battery's efficiency remains stable at 99.41%—which is still considered good and above the standard (>80%)—several key parameters have degraded. The battery is still capable of supplying the load for 16.9 hours. However, its specific gravity value has decreased to 1.1305 kg/l, which is below the standard (1.17-1.19 kg/l). Furthermore, the total battery voltage in 2020 was measured at 85.8 V, a drop of 2.1 V from 2018. Further analysis found that this voltage drop was caused by the presence of "dropped" battery cells. In the 2018 discharge test, there were two cells with voltages below the minimum limit. This number increased to five cells in the 2020 test. If this condition is left unaddressed, it is predicted that the battery's voltage and efficiency will continue to decline in the coming years, which could impact the overall system reliability. Thus, although its efficiency remains good, the degradation of critical parameters such as specific gravity and cell voltage indicates that the battery's quality is beginning to decline.
AN ARDUINO-CONTROLLED SMART SYSTEM FOR EFFICIENT CARPET MOISTURE REDUCTION Narendra Ahmad
PULSE — Journal of Energy, Informatics & Biomedicine Vol 1 No 1 (2025): Inaugural Issue
Publisher : Khamdan Karya Cipta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/e8ba5a54

Abstract

In various sectors, the increasing demand for efficiency and innovation has made the development of technology to address daily challenges highly relevant. This study aims to design and construct an automated and eco-friendly carpet dryer prototype controlled by an Arduino Mega 2560 microcontroller. The system is specifically engineered to overcome the common issue of slow and inefficient carpet drying, particularly in densely populated urban environments. The research methodology involves both hardware design and software development. The hardware components include heating elements, a fan motor, and sensors for detecting temperature and humidity. The software was developed using the C++ programming language. The drying process is initiated by a DHT11 sensor that detects carpet moisture levels. If the humidity surpasses a predefined threshold, the system automatically activates the heating element and fan to accelerate the evaporation process. Once the desired moisture level is reached, the system will automatically shut down. Experimental results indicate that the prototype effectively reduces carpet humidity. The use of Arduino as the central controller enables the system to operate autonomously and respond dynamically to environmental conditions. Furthermore, its compact and energy-efficient design positions this prototype as a viable and sustainable solution. This research demonstrates that microcontroller technology can be effectively applied to create practical, efficient, and automated solutions for daily life.
ANALISIS PERFORMA SISTEM PELACAKAN ROBOT BERODA BERBASIS ROTARY ENCODER DENGAN MIKROKONTROLER ARDUINO Siratullah Ahmad
PULSE — Journal of Energy, Informatics & Biomedicine Vol 2 No 1 (2026): March 2026
Publisher : Khamdan Karya Cipta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/pulse-jeib.v2.i1.a6

Abstract

This study presents a performance analysis of a wheeled robot tracking system utilizing rotary encoders for position and orientation sensing. The system, built around an Arduino Uno microcontroller, is designed to provide real-time location mapping and trajectory tracking. The research addresses the challenge of accurate indoor robot navigation by integrating data from two rotary encoders mounted on the robot's wheels. The methodology involves developing an odometry algorithm to calculate the robot's position based on wheel rotations. The data, including distance, speed, and heading, is then transmitted to a computer for visualization and control via a LabVIEW graphical user interface. Experimental results demonstrate the system's ability to effectively track the robot's path, with detailed performance metrics analyzed to evaluate accuracy and precision under various movement conditions. The findings indicate that the system provides a reliable and cost-effective solution for basic mobile robot localization, laying the groundwork for more complex autonomous navigation applications.
OPTIMIZATION OF LIGHTNING PROTECTION SYSTEM DESIGN FOR MULTI-STORY BUILDINGS BASED ON COST AND PROTECTION COVERAGE ANALYSIS Ahmad Nasrul
PULSE — Journal of Energy, Informatics & Biomedicine Vol 2 No 1 (2026): March 2026
Publisher : Khamdan Karya Cipta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/pulse-jeib.v2.i1.a7

Abstract

The installation of a lightning protection system at SMK Bhakti Praja Jepara aims to safeguard the building from the hazards of lightning strikes. The building, which is 23 meters high with an area of ±3,716 m², currently lacks this protective system, making it susceptible to mechanical, thermal, and electrical damage. This study began by planning a lightning protection system in accordance with the PUIPP (General Regulations for Lightning Protection Installation) and SNI 03-7015-2004 standards. The research process involved collecting building data, measuring grounding resistance, and conducting a comparative analysis between two methods: conventional and electrostatic. The grounding resistance measurements yielded values of 3.88 Ohm, 1.39 Ohm, and 3.77 Ohm, all of which meet the SNI standards. The comparative analysis concluded that the conventional system, which requires four lightning rods, has an estimated cost of Rp 7,537,774.00. In contrast, the electrostatic system, due to its wider protection radius, only requires one lightning rod and is more cost-efficient, with an estimated budget of Rp 5,723,774.00. Based on these findings, it is concluded that the electrostatic lightning protection system is a more optimal solution in terms of both protection radius effectiveness and cost efficiency.
ANALYSIS OF BIOMEDICAL PHYSICS IN PULSE OXIMETERS: PRINCIPLES OF PHOTOPLETHYSMOGRAPHY, PHOTOELECTRIC SENSORS, AND SIGNAL PROCESSING Cahya Maulana
PULSE — Journal of Energy, Informatics & Biomedicine Vol 2 No 1 (2026): March 2026
Publisher : Khamdan Karya Cipta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/pulse-jeib.v2.i1.a8

Abstract

Pulse oximeter is a non-invasive biomedical device widely used to monitor arterial oxygen saturation (SpO₂) and pulse rate in clinical and ambulatory settings. This article presents a comprehensive review of the biomedical physics underlying pulse oximeter technology, emphasizing the integration of optical physics, electronic instrumentation, and digital signal processing. The discussion covers the principles of photoplethysmography (PPG), the application of the Beer–Lambert law to biological tissues, and the optical absorption characteristics of oxygenated and deoxygenated hemoglobin at wavelengths of 660 nm and 940 nm. Furthermore, the article analyzes the operation of key hardware components, including dual-wavelength light-emitting diodes (LEDs), silicon photodiodes, transimpedance amplifiers, analog filters, analog-to-digital converters, and digital signal processing algorithms based on the ratio-of-ratios method for SpO₂ estimation. The review also discusses signal acquisition, conditioning, and calibration processes required to improve measurement accuracy under various physiological conditions. In addition, the study examines technical limitations and clinical challenges such as motion artifacts, peripheral hypoperfusion, dysfunctional hemoglobin, ambient light interference, and skin pigmentation bias that may affect measurement reliability. Recent technological developments are also reviewed, including multi-wavelength pulse oximetry, wearable reflectance photoplethysmography, flexible biosensors, and artificial intelligence-based signal processing techniques that enhance measurement robustness and clinical applicability. Overall, this review highlights the multidisciplinary nature of pulse oximeter technology and demonstrates how advances in biomedical physics, optical sensing, electronics, and intelligent signal processing continue to improve the performance, reliability, and future development of non-invasive physiological monitoring systems.
ANALYSIS OF PHYSICAL PRINCIPLES AND ACCURACY FACTORS IN THERMOPILE-BASED INFRARED THERMOMETERS FOR ELECTROMEDICAL APPLICATIONS Gita cahyani
PULSE — Journal of Energy, Informatics & Biomedicine Vol 2 No 1 (2026): March 2026
Publisher : Khamdan Karya Cipta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/pulse-jeib.v2.i1.a9

Abstract

Infrared thermometers have become widely used in medical applications due to their ability to perform rapid, non-contact body temperature measurements while minimizing the risk of cross-contamination. This paper reviews the fundamental physical principles and electronic systems underlying the operation of infrared thermometers in electromedical applications. The discussion covers electromagnetic radiation, blackbody radiation, the Stefan–Boltzmann law, Wien’s displacement law, and the Seebeck effect, which forms the basis of thermopile sensor operation. Furthermore, the signal acquisition process, including optical focusing, low-noise amplification, analog-to-digital conversion, and microprocessor-based temperature estimation, is described to explain the complete measurement mechanism. The review also examines key factors affecting measurement accuracy, including emissivity, ambient temperature, measurement distance, sensor noise, and analog-to-digital converter resolution. Understanding the interaction between these physical phenomena and electronic subsystems is essential for improving the performance, reliability, and accuracy of infrared thermometers in clinical practice. This review provides a comprehensive reference for students, researchers, and practitioners in electromedical engineering to better understand the working principles and performance characteristics of non-contact infrared thermometers
A COMPREHENSIVE REVIEW OF PULSE OXIMETRY: OPTICAL PRINCIPLES, SIGNAL PROCESSING, AND CLINICAL APPLICATIONS Muhammad Faiq Syarifun Najih
PULSE — Journal of Energy, Informatics & Biomedicine Vol 2 No 1 (2026): March 2026
Publisher : Khamdan Karya Cipta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/pulse-jeib.v2.i1.a10

Abstract

Pulse oximetry has become one of the most widely used non-invasive technologies for monitoring arterial oxygen saturation (SpO₂) in clinical and home healthcare settings. Despite its widespread adoption, measurement accuracy is strongly influenced by the underlying optical principles, signal processing techniques, and physiological characteristics of the measured tissue. This study aims to comprehensively analyze the physical principles governing pulse oximetry from an electromedical physics perspective. A narrative literature review approach was employed by synthesizing recent scientific publications addressing optical absorption, the Beer–Lambert law, photoplethysmography (PPG), signal processing, and factors affecting measurement accuracy. The analysis demonstrates that pulse oximetry operates through the integration of differential light absorption at red (660 nm) and near-infrared (940 nm) wavelengths with pulsatile blood volume detection using photoplethysmography. The ratio-of-ratios algorithm enables non-invasive estimation of arterial oxygen saturation while minimizing the influence of tissue thickness and optical path variations. However, measurement performance remains susceptible to motion artifacts, ambient light interference, peripheral hypoperfusion, abnormal hemoglobin species, and skin pigmentation, which may introduce clinically significant bias. Recent technological developments, including multi-wavelength optical sensing, advanced digital signal processing, artificial intelligence, and Internet of Things (IoT)-based monitoring systems, provide promising approaches for improving measurement accuracy, robustness, and remote patient monitoring capabilities. In conclusion, a comprehensive understanding of optical physics and signal processing principles is essential for optimizing pulse oximeter performance and supporting the development of more accurate, reliable, and inclusive electromedical devices for future healthcare applications.

Page 1 of 1 | Total Record : 10

 1 

Filter by Year

2025 2026


Reset
Filter By Issues
All Issue Vol 2 No 1 (2026): March 2026 Vol 1 No 1 (2025): Inaugural Issue