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Journal of Electrical Engineering and Computer (JEECOM)
Published by Universitas Nurul Jadid
ISSN : 27150410     EISSN : 27156427     DOI : -
Core Subject : Science, Engineering,
Control & Systems Engineering Electrical & Electronics Engineering Energy
Journal of Electrical Engineering and Computer (JEECOM) is published by Engineering Faculty of Nurul Jadid University, Probolinggo, East Java, Indonesia. This journal encompasses research articles, original research report, : 1) Power Systems, 2) Signal, System, and Electronics, 3) Communication Systems, 4) Information Technology, etc.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 231 Documents
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Facial Expression Based Emotion Recognition Ibrahim, Muhammad; Ergen, Burhan
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.11069

Abstract

Human communication predominantly relies on spoken and written language; however, nonverbal cues, such as facial expressions, play a critical role in conveying emotions. This study details the development and evaluation of a deep learning model for Facial Emotion Recognition (FER) utilizing the VGG-16 architecture and the FER2013 dataset which includes over 35,000 facial images taken in natural settings, depicting seven emotions. The objective was to enhance recognition, accuracy and performance beyond the existing benchmarks in the literature. Transfer learning was employed by leveraging pre-trained VGG-16 weights, with the classification layers restructured and fine-tuned for emotion categorization. Comprehensive preprocessing, including normalization and data augmentation, was implemented to improve the model generalization and mitigate overfitting. The final model achieved an accuracy of 85.77%, surpassing several previous VGG-16-based FER models. The model performance was assessed using metrics such as accuracy, precision, recall, and F1-score, confirming the model's reliability. Integral to this success was the incorporation of hyperparameter tuning and regularization techniques, notably, dropout and early stopping. The model demonstrated the capability to extract salient features from low-resolution images, thereby supporting its robustness. Additionally,the potential use cases of the model in areas such as transportation safety, security systems, and customer interaction analysis can address in the Future study to enhance the model's real-world applicability by utilizing more diverse datasets and advanced architectures
Temporary Devider as an innovation tool in reducing operational losses of PT PLN (Persero) UP3 Sidoarjo Zaputra, Gaggah; Ayuni, Shazana Dhiya; Anshory, Izza; Falah, Agus Hayatal
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10810

Abstract

Temporary Devider is a new tool that was created in October 2024 by the PT PLN (PERSERO) UP3 SIDOARJO PDKB Team. Temporary Devider was created to help and solve problems with SUTM maintenance work that could not be carried out by the PDKB team due to high risk factors. The results of the study from 5 implementations in the PT PLN (Persero) UP3 Sidoarjo work area, local blackouts by utilizing the Temporary Devider as a new innovation tool with an investment value IDR 4,000,000 can reduce the difference in company losses by 89,376.08 kWh or Rp. 104,263,090 when compared to blacking out one feeder and 16,839.02 kWh or IDR 19,578,227 when compared to per-section outages. The use of Temporary Deviders has been proven to be able to reduce losses due to blackouts which result in Energy Not Supplied.
Sentiment Modeling of Instagram Users Towards Traditional and Modern Body Scrubs Using the Naive Bayes Algorithm Mardiana, Mardiana; Kusrini, Kusrini
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10175

Abstract

This study conducts sentiment analysis on Instagram comments related to traditional and modern body scrub products using the Naive Bayes algorithm. The aim of the research is to identify and compare consumer sentiments—positive, negative, or neutral—toward these two categories of skincare products. The results indicate that neutral sentiment dominates, followed by negative and positive sentiments. The Naive Bayes algorithm demonstrated strong performance, particularly in detecting negative and neutral sentiments, but exhibited a lower recall rate for positive sentiments. The findings reveal that consumers value traditional body scrubs for their natural ingredients and cultural significance, while modern body scrubs are appreciated for their innovation. These insights offer actionable recommendations for skincare brands, highlighting the need for tailored marketing strategies and deeper consumer engagement.
Startup Success Factors: Classifying 3H (Hustler, Hipster, Hacker) Framework using Simple Additive Weighting Susilowati, Qoriah Indah; Başçiftçi, Fatih
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.11072

Abstract

Nowadays, start-ups are heavily influenced by the character of their founders. The framework in this case is known as 3H which is an explanation of Hustler, Hipster and Hacker. In this study, a decision support system based on the Simple Additive Weighting (SAW) method was built that can determine the tendency of user characteristics to a category. This system is built in a web-based application with 25 closed questions recommended by experts. Each question has its own weight for each choice. Then this process continues to the answer normalisation stage and the total of this normalisation will be converted to a scale of 75 to determine the final category. Then the results will be validated by comparing the results done by the expert and the system. Based on testing conducted with 3 samples, the system managed to get 100% accuracy. However, there are research findings that show the Hustler character if implemented with a method like this research will only be taken if all answers are answers with minimum weight. But basically, this research shows that SAW is a fairly effective method in supporting classification decisions, it's just that improvements are needed on the expert side so that the weights can be done dynamically so that the results are more optimal.
Classification Of Direction Using Naive Bayes Classifier Method (Case Study Of Hidayatul Islam Leces Vocational School) Yanto, Dwi; Susanto, Heri; Rusdiana, Ninanesia; Zulkifli, Kiky
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.11160

Abstract

Abstract— Determining student majors is an important process in the world of education that can affect students' future. In this thesis, we conducted a study on determining student majors using the Naive Bayes Classifier algorithm at SMK Hidayatul Islam. The purpose of this study was to test the accuracy of the Naive Bayes Classifier algorithm in predicting student majors and to provide recommendations that can support decision making in determining student majors. This study uses historical data of SMK Hidayatul Islam students which includes various attributes such as academic grades, Mathematics, Science, Language, Science, and Average report card grades. The data was processed and trained on the Naive Bayes Classifier algorithm using machine learning methods. Furthermore, the algorithm was tested using separate test data. The results showed that the Naive Bayes Classifier algorithm provided an accuracy of 97.50% in determining student majors at SMK Hidayatul Islam. This shows a very good ability to predict student majors based on existing attributes. With high accuracy, this algorithm can be an effective tool in helping the student major decision-making process. However, it should be noted that the results of this study need to be considered in the specific context of SMK Hidayatul Islam and the characteristics of its students. Factors such as students' interests and talents, parents' views, and job market needs should also be important considerations in determining students' majors. Therefore, the Naive Bayes Classifier algorithm should be used as one component in a broader decision-making process, which involves consideration of these various factors.
Water Level Detection and Flood Early Warning System Using Image Processing Ilmi, Muhammad Akmal; Somawirata, I Komang; Ardita, Michael
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10851

Abstract

Image processing is a crucial method in modern technology, enabling computers to analyze and extract information from images or videos. This study focuses on the application of image processing technology to detect river water levels using CCTV cameras as part of a flood early warning system in a smart city. The YOLO (You Only Look Once) algorithm is utilized for real-time object detection, such as water levels, aiming to enhance prediction accuracy. This implementation is expected to provide richer visual data compared to traditional sensors. The study involves designing and testing a system that integrates hardware (CCTV cameras and high-spec computers) and software such as OpenCV and Python. Data in the form of river images is processed using image processing algorithms to analyze water levels in real-time. The system's performance is evaluated in terms of accuracy, precision, recall, and processing speed (FPS), as well as the environmental impact on detection results. The results indicate that the YOLO-based image processing system achieves high accuracy in detecting water levels. Additionally, the system is capable of sending early warnings via digital notifications, allowing more time for disaster mitigation. These findings suggest that image processing-based systems offer practical, efficient, and cost-effective solutions to support smart city technologies.
Development of Chili Grinding Machine with Hybrid System of Wind and Solar Energy Uddin, Ameer; Haqqy, Zetya Maulanal; Sulistiyanto, Sulistiyanto
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.11193

Abstract

This study aims to develop an efficient chili grinding machine that utilizes a hybrid system combining wind and solar energy as a sustainable solution to address the issue of dependence on conventional energy sources, which are often expensive, environmentally unfriendly, and limited in rural areas. The main challenge is how to provide a grinding machine that can operate independently in regions with limited electricity access and high energy costs. The primary objective of this research is to design a machine capable of providing reliable power in these areas. The research involved the design and assembly of a prototype, integrating wind and solar power systems to drive a DC motor for grinding chilies. Testing was conducted to measure the power output from each energy source, with results showing that the wind turbine generates an average power of 6.715 mW, while the photovoltaic (PV) system produces an average power of 14.77 W. Combined, these sources yield a total average power output of 16.466 W. However, observations revealed that the battery charging time was longer than the operational duration of the DC motor. This hybrid-powered chili grinding machine provides a practical application of renewable energy technology, particularly suited for rural areas, and supports broader efforts to reduce carbon emissions.
Implementation of the C4.5 Decision Tree Algorithm in Determining PIP Recipient Students Based on Poverty Susanto, Heri; Yanto, Dwi; Jamal, Jamal; Anam, Choirul; Nafisah, Thohirotun
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.11078

Abstract

The Program Indonesia Pintar (PIP) is a government assistance in the form of a certain amount of cash given directly to students who are vulnerable to poverty according to the established criteria. However, in its implementation, there are still many recipients of PIP funds who are still not on target. Several results of evaluations and ongoing studies on the implementation of PIP show weaknesses in this program, namely related to the accuracy of determining the target of PIP fund recipients, where it was found that there were still many non-poor households who received this PIP fund assistance. The purpose of this study is to produce a decision support system to determine students who are truly worthy of being recommended to receive PIP fund assistance. The method used in this study is the Decision Tree C4.5 algorithm. The data used were 300 datasets, by selecting several relevant attributes. For processing using the Rapidminer tool, one of the popular software used in data mining processing. Meanwhile, the evaluation method uses a confusion matrix by calculating the accuracy value. From the test results in determining PIP acceptance at SD Negeri Kedungjajang 02 using the C4.5 algorithm, an accuracy of 97.33% was obtained, with the accuracy criteria of good classification.
Design and Development of a Laboratory-Scale Wave Power Plant Using the Oscillating Water Column System Prabowo, Yuliyanto Agung; Tuapattinaja, Rendy Kevin; Perdana, Rizky; Putra, Johans Andika
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10939

Abstract

Renewable energy is one of the strategies promoted by the government to enhance national energy resilience and reduce dependence on fossil fuels. As an archipelagic country, Indonesia has great potential in utilizing ocean energy, particularly wave energy. This study aims to design and construct a laboratory-scale wave power plant using the Oscillating Water Column (OWC) system and to analyze the electrical voltage generated by the turbine under various test conditions. The method used is an experimental laboratory approach, involving a system composed of an oscillation tank, a DC motor as the wave-generating mechanism, and a DC turbine as the generator, tested both with and without a boost converter. The artificial waves generated by the pushing mechanism produce air pressure in the chamber, which rotates the turbine to generate electrical voltage. The experimental results show that optimal performance occurs at a water height of 26 cm and a wave height of 2 cm, with a wave period of 0.502 seconds. The maximum voltage output produced by the turbine was 3 V when connected to a boost converter. These results indicate that the OWC system is capable of effectively converting wave energy into electrical energy in a laboratory-scale setting.
Operational Analysis of Rooftop Solar Power Plant (PLTS) at GMIT Jemaat Paulus Kupang Mau, Viko Nobertus; Galla, Wellem; Likadja, Frans James
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10873

Abstract

Rooftop Solar Power Plant (PLTS) is one of the renewable energy solutions that support energy efficiency and environmental sustainability. This research is entitled “Operational Analysis of Rooftop Solar Power Plant (PLTS) at GMIT Jemaat Paulus Kupang” and was conducted for four months at GMIT Jemaat Paulus Kupang. The purpose of this research is to analyze the performance and effectiveness of the rooftop solar power system installed in the church. Measurements were made using tools such as Digital Multimeter and Ampere Pliers. This research uses descriptive and quantitative methods, including literature studies, interviews with PLTS management officers, and direct measurements in the field to obtain primary and secondary data related to geographical and weather conditions. The results showed that the performance of the rooftop solar power plant decreased significantly due to factors such as solar radiation intensity, ambient temperature, and the physical condition of the solar panels and inverters. During one week, GMIT Jemaat Paulus Kupang used a total of 561.396 kWh of electrical power to meet load requirements. Of this amount, PLTS supplied 499.2468 kWh of power, while the remaining 62.1492 kWh was supplied by PLN. The excess power generated by the PLTS, because it is greater than the total load demand, is exported back to the PLN network. 

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