Journal of Electrical Engineering and Computer (JEECOM)
Journal of Electrical Engineering and Computer (JEECOM) is a peer-reviewed and open-access scientific journal published by the Lembaga Penerbitan, Penelitian, dan Pengabdian kepada Masyarakat (LP3M) of Nurul Jadid University, Probolinggo, East Java, Indonesia. This journal publishes original research articles, reviews, and technical reports in the fields of Electrical Engineering and Computer Sciences. It aims to provide a platform for scholars and practitioners to exchange ideas, findings, and innovations that advance science and technology in these domains. The journal’s coverage includes topics in power and energy systems, such as power generation, distribution, conversion, protection, and electrical materials. It also welcomes studies in signal, systems, and electronics, including digital signal and image processing, robotics, control, and embedded systems, as well as communication systems encompassing telecommunications, wireless communications, and computer networks. The journal features research in information technology and computing, focusing on software engineering, data mining, multimedia, mobile and distributed computing, artificial intelligence, computer graphics, AR/VR, and geographic information systems (GIS). Through these areas, the journal seeks to foster innovation and interdisciplinary collaboration across electrical and computing technologies. P-ISSN : 2715-0410 E-ISSN: 2715-6427 Indexed By : <a href="https://doaj.org/toc/2715-6427?source=%7B%22query%22%3A%7B%22filtered%22%3A%7B%22filter%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22terms%22%3A%7B%22index.issn.exact%22%3A%5B%222715-0410%22%2C%222715-6427%22%5D%7D%7D%5D%7D%7D%2C%22query%22%3A%7B%22match_all%22%3A%7B%7D%7D%7D%7D%2C%22size%22%3A100%2C%22sort%22%3A%5B%7B%22created_date%22%3A%7B%22order%22%3A%22desc%22%7D%7D%5D%2C%22_source%22%3A%7B%7D%7D" target="_blank">
Authors who publish in Journal of Electrical Engineering and Computer (JEECOM) agree to the following terms: 1. Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal. 2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal. 3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
Improving Tomato Ripeness Classification Using Knowledge Distillation and Hyperparameter Optimization with Optuna
Automatic classification of tomato ripeness plays a crucial role in ensuring post-harvest quality and efficiency in the horticultural industry. This study proposes a combined strategy of Knowledge Distillation (KD) and hyperparameter optimization using Optuna to improve the accuracy of the ResNet50 student model by leveraging the performance of a MobileNetV2 teacher model.We used a publicly available Kaggle dataset containing 8,540 images, categorized into four ripeness levels (green, red, ripe, and rotten), comprising 7,157 training images and 1,383 validation images.Each image was resized to 224×224 pixels; light augmentation techniques (random rotation, brightness–contrast adjustment, flipping, and Gaussian blur) were applied only to the training set to prevent overfitting while maintaining consistency during evaluation.The MobileNetV2 teacher model was initially fine-tuned on the last 20 layers using manual hyperparameters (freeze_until = 20, dropout = 0.6), achieving an accuracy of 85.8%.Subsequent tuning via Optuna identified the optimal configuration (freeze_until = 91, dropout_rate = 0.5055), which improved the teacher’s performance to 89.6%.The resulting teacher model was then used to distill knowledge into the ResNet50 student: under manual settings, the student’s accuracy improved from 55.24% to 73.25%; when the student model was also optimized using Optuna, its accuracy surged to 85.54% nearly matching the teacher.Further evaluation using a confusion matrix and ROC curves revealed an increase in per-class AUC to the range of 0.91–0.99 in the KD + Optuna student model, confirming that this method effectively closes the performance gap between student and teacher.These findings demonstrate that combining KD with Optuna-based hyperparameter optimization is an effective approach for producing a lightweight, fast, and highly accurate tomato ripeness classification model ready for deployment in field applications to support post-harvest decision-making.
Copyright (c) 2025 Iasya Sholihin https://creativecommons.org/licenses/by-nc-sa/4.0
Public Street Lighting Planning (PJU) Using New and Renewable Energy in Tanjung Gusta Village, Hamlet III, Sunggal District
Indonesia has great potential in renewable energy, especially solar energy, due to its geographical location in the tropics. This research aims to plan an efficient and sustainable Public Street Lighting (PJU) system in Tanjung Gusta Village, Sunggal District, by utilizing new and renewable energy (NRE). Tanjung Gusta Village has a need for adequate street lighting to improve the safety, mobility, and quality of life of the community. The research method includes field surveys to analyze conditions, calculation of lighting needs based on applicable standards, and PJU system design using NRE. The results of the study show that the PJU system with solar power is the most suitable solution for Tanjung Gusta Village, taking into account the availability of resources. The planning of this solar PJU system includes the selection of the type of lamp to be used, determining the capacity of the solar panel and battery, and calculating the optimal layout and height of the light pole.
Copyright (c) 2025 ilyasa ramadhan https://creativecommons.org/licenses/by-sa/4.0
Analysis of Cybersecurity Awareness Among Social Media Users Among Teenagers Using Exploratory Factor Analysis (EFA) & Confirmatory Factor Analysis (CFA) Methods
Nowadays, security awareness is very important for social media users, especially teenagers. Many users become victims of cybercrime due to the lack of education about cybersecurity awareness. This case began with many complaints submitted by teenagers from SMP Negeri 2 Ngoro, one of whom was a victim of cybercrime on Instagram social media whose account was hijacked by unknown individuals. This also happens on WhatsApp social media where there are criminals who steal someone's identity to be used as a victim and commit fraudulent money transfers, credit and other fraud. The purpose of this study was to assess and ensure the level of cybersecurity awareness among the three most significant social media platforms in Indonesia, namely WhatsApp, Instagram, and TikTok. The Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) methods were used to analyze the online survey data set. The EFA results obtained were 6.67% insignificant in one of the factors contained in the knowledge variable and 93.33% EFA results stated significant. Meanwhile, the CFA calculation results obtained 80% results which were stated as Fit, indicating that the model accurately represented the data, 20% of the CFA calculation results stated Moderate Fit because they reflected values that were almost close to the fit value.
Copyright (c) 2025 sofia angela https://creativecommons.org/licenses/by-sa/4.0
Automatic Safe Security System Using Pin Code And Fingerprint Based On Microcontroller With Telegram Notification
The primary purpose of a security system is to protect valuable and important items. A safe is a medium for storing valuables, adjusted to the size of the safe compartment. Therefore, a proper security system is needed to ensure the owner does not worry about the loss or theft of the contents. This security system is adapted to the current era of advanced and modern technology. The sensors and microcontroller used include the NodeMCU ESP8266, fingerprint sensor, keypad, and LED indicator lights. Telegram notifications or alerts via the application can be received through an internet connection. This security system is implemented to secure the safe and can be accessed via an Android smartphone with the Telegram app installed. It enables the owner to receive access notifications indicating whether an attempt was successful or failed. This research was conducted using an experimental method by building a device to enhance the safety of the safe, providing peace of mind about the stored items. The experiment was carried out at a residence located in Bendosari Village, Ngantru District, Tulungagung Regency. Based on the results, it can be concluded that the development of an automatic safe using a pin code and fingerprint based on a microcontroller with Telegram notifications has successfully met the research objectives. All sensors and components within the safe function properly, ensuring the protection of valuables inside and offering peace of mind to the owner.
Copyright (c) 2025 Achmad Yahya Chanifudin https://creativecommons.org/licenses/by-sa/4.0
Analysis Of The Performance Of Solar Power Plants (Plts) On The Electrical Energy Needs Of Mosques
The need for electrical energy continues to increase, including in public facilities such as mosques. Solar energy is an environmentally friendly and sustainable solution because it is a source of renewable energy. This study aims to analyze the feasibility of implementing a rooftop Solar Power Plant (PLTS) system at Al-Hakim Mosque, Mabar Hilir Village, which has high sunlight intensity and minimal vegetation obstructions. The methods used include direct observation and interviews. The data collected included location identification, energy needs, and calculations of the solar power system. The results show that the mosque requires a daily power of 7,860 Wh, which can be met with 16 100 Wp solar panels and 9 12V 100Ah LiFePO₄ batteries. The research concluded that the location of the Al-Hakim Mosque is suitable for the implementation of the solar power system, while supporting the renewable energy transition and government policies towards energy sustainability in Indonesia
Copyright (c) 2025 ilhan hafit https://creativecommons.org/licenses/by-sa/4.0
Study of Potential Scalability Development of Palm Oil Mill Effluent-based Gas-fired Power Plant
Indonesia, as the world's largest producer of palm oil, generates a large amount of liquid waste that has the potential to be a renewable energy source. The main problem of liquid waste originated from palm oil industry, apart from its nature, is its potential long-term usability, especially when improvements in biogas-based power generating technologies are put into consideration. Based on these problems, the main purpose of this research is to compare the economical, technical, and environmental scalability between palm oil mill effluent (POME)-based biogas power generation and older, existing diesel-based power generation and analyzing their scalability potential in long term, in aim to increase the utilization of renewable energy portion in Indonesia. This research is conducted by observing an actual palm oil mill facility and its power generation system. Data are analyzed by qualitative and quantitative method by means of computer simulation before being compared with diesel-based power generation system. Based on simulations and comparative analysis, POME-based biogas can be utilized as a fuel source for power generation using gas-fired power generating technology, due to its methane content. With these characteristics, it is possible to analyze the scalability potential of POME-based biogas power plants in the diversification of new and renewable energy sources. Studies on potential development show that biogas power plants are more efficient and have a linear correlation with the volume of liquid waste, and can be adapted in lieu of power generating-related technology advancements. As a result, energy derived from POME can support energy independence and contribute to the growth of clean energy.
Copyright (c) 2025 Ishananta Alfian Widanarko https://creativecommons.org/licenses/by-nc-sa/4.0
Deep Learning Models For Youtube Sentiment Analysis: A Comparative Study Of Bert And Gru In Danantara Indonesia
This study aims to analyse public sentiment toward Danantara Indonesia through YouTube comments and compare the performance of two deep learning models, BERT and GRU, in sentiment classification. The dataset consists of 1,065 comments collected through scraping techniques, which were pre-processed and classified into three sentiment categories: positive, neutral, and negative. The results indicate that the IndoBERT model achieved 100% accuracy, with perfect precision, recall, and F1-score for all sentiment classes. In contrast, the GRU model only achieved 60% accuracy, showing a tendency to classify almost all comments as negative sentiment. Sentiment distribution analysis reveals that the majority of comments (60%) express negative sentiment, followed by positive sentiment (25%) and neutral sentiment (15%). The dominance of negative sentiment suggests public distrust and criticism regarding the policies and transparency of Danantara Indonesia. These findings demonstrate that BERT is a more accurate model for sentiment analysis of Indonesian-language texts. Furthermore, this study recommends further evaluation to address data imbalance and improve the model’s generalization across various social contexts in digital media.
Copyright (c) 2025 Ema Utami https://creativecommons.org/licenses/by-sa/4.0
Monitoring Design on PV and Battery PLTS for Power Regulation on Water Pump
The increasing use of solar energy as a source of electrical energy encourages the use of remote monitoring systems to determine the performance of solar panels. The purpose of this study is to conduct a monitoring system for solar panel (PV) and battery output for water pump loads. The method used is to design a monitoring system using the microcontroller NodeMCU ESP8266 and sensor INA219. The first step is to determine the capacity of the PV, battery, and water pump. Then do microcontroller programming and field testing. The INA219 sensor measures the operating voltage and current in real time, the voltage, power, and current of the PV connected to the circuit. Experimental investigations that have been carried out to verify the effectiveness of the proposed monitoring system have shown that proper examination of the collected data allows the monitoring system to be enlarged. The monitoring system is able to perform measurements well for 3 months. The results of monitoring measurements in this study are also influenced by the intensity of solar radiation.
Copyright (c) 2025 sri - sukamta, ulfah mediaty arief https://creativecommons.org/licenses/by-sa/4.0
Utilization of a Pressure Sensor as a Pressure Regulator in an Autoclave Machine for Medical Equipment Sterilization and IoT-Based Monitoring
An autoclave is a sterilization device that operates using high-pressure steam to eliminate microorganisms. However, in conventional systems, pressure regulation is still performed manually, which can lead to inconsistencies in the sterilization process and reduced effectiveness. This study developed an automatic pressure control system based on a digital pressure sensor, controlled by an Arduino Uno microcontroller and equipped with an ESP8266 module for real-time monitoring via the Internet of Things (IoT). The system also utilizes a MAX6675 temperature sensor, a solenoid valve as a pressure actuator, and an LCD as a local interface. Testing was conducted at three pressure settings (10, 15, and 25 psi) for a duration of 15 minutes. The results showed that the system was able to maintain pressure with a fluctuation tolerance of ±0.3 psi and successfully transmitted temperature and pressure data to a cloud dashboard in real-time. This system is considered effective in improving the efficiency, accuracy, and safety of the sterilization process, and has the potential to be implemented in medical and laboratory facilities.
Copyright (c) 2025 mohammad saickoni, mohammad saickoni https://creativecommons.org/licenses/by-sa/4.0
Implementation of Blockchain for Integrated Civil Service Statistical Data (Case Study: Civil Service and Human Resource Development Agency of Madiun Regency, East Java Province)
Digital transformation in personnel data management demands a transparent, secure, and integrated system to support data-driven decision-making and enhance accountability in personnel services. An integrated information system and personnel statistical data are necessary to assist leaders in analyzing staffing needs and making more accurate and efficient data-based policies, while also strengthening the principles of good governance through improved transparency and accountability. Therefore, the Personnel and Human Resource Development Agency of the Government of Madiun Regency, East Java, requires technology capable of effectively managing personnel information by offering security, transparency, and data integrity through a decentralized mechanism. Blockchain, as a distributed ledger technology, provides an innovative solution for maintaining data integrity and increasing public trust through permanent, encrypted, and validated transaction records within a decentralized network. The implementation of blockchain in the management of personnel statistical data remains limited, despite the technology’s ability to support real-time audit trails and reliable interactive data visualization. This study proposes a framework for integrating a relational database with smart contracts on the Ethereum network, by recording the hash of statistical data in the smart contract as proof of data authenticity. Data is retrieved from the database, hashed, and the hash is stored in the smart contract to ensure its integrity, with the results visualized in interactive charts. This framework is expected to improve transparency, accountability, and trust in personnel statistical data to support more accurate and efficient strategic decision-making.
Copyright (c) 2025 SYAIFUL SYAIFUL HUDA https://creativecommons.org/licenses/by-sa/4.0
Currency Exchange Rate Prediction Using Gated Recurrent Unit (GRU) with Historical Data and Economic Factor
This study presents a currency exchange rate prediction model using a Gated Recurrent Unit (GRU) with historical price data and selected economic factors. Historical data, including Open, High, Low, and Close (OHLC) prices, were obtained from Yahoo Finance. Economic factor data, including Non-Farm Payrolls (NFP), Gross Domestic Product (GDP), Purchasing Managers Index (PMI), Retail Sales, and Durable Goods Orders, were collected from Trading View. Data preprocessing involved chronological sorting, missing value handling, feature scaling, and sequence generation. Multiple experiment cases were evaluated: historical data alone, historical data combined with all economic factors, and historical data combined with each individual factor. The GRU model achieved its best performance when incorporating historical data with Durable Goods Orders, indicating that this economic indicator provides significant predictive value, as reflected by the lowest RMSE (0.0076) and MAPE (0.0054), and the highest R² (0.9764) indicating that this economic factor provides significant predictive value. These findings highlight the importance of integrating selected economic factors into exchange rate prediction models to enhance forecasting accuracy.
Copyright (c) 2025 Muhammad Azmi Adhani, Kusrini Kusrini https://creativecommons.org/licenses/by-sa/4.0
Health Risk Level Prediction for Hajj Pilgrims Using Random Forest and Bayesian Optimization (Case Study: Hajj Pilgrims of Balikpapan Embarkation)
The Hajj pilgrimage is one of the largest religious rituals in the world, involving millions of pilgrims from various countries. The physical condition and health of pilgrims are crucial factors in ensuring the smooth execution of the Hajj. Data from the Ministry of Health indicates that the mortality risk among Hajj pilgrims tends to increase annually, particularly in the elderly age group and among pilgrims with a history of certain diseases, such as hypertension, diabetes, and heart disease. This study aims to compare the performance of a Random Forest model optimized with Bayesian optimization against a Random Forest model without any optimization in predicting the health risk level of Hajj pilgrims at the Balikpapan Embarkation. The research findings show that the Random Forest model optimized with Bayesian Optimization provides superior performance compared to the non-optimized model, using K-Fold Cross-Validation for data splitting to avoid imbalance. The optimized model achieved an average Accuracy of 88.25% and an F1 Score of 88.19%, higher than the standard model which recorded 87.99% and 87.95% on the same metrics. Although their AUC scores were nearly identical (95.46% vs. 95.47%), the improvement in accuracy and F1 Score indicates that Bayesian Optimization can produce a more balanced and accurate classification model. In conclusion, the application of Bayesian Optimization to Random Forest is proven effective for enhancing the predictive accuracy of Hajj pilgrims' health risks, potentially supporting more proactive Hajj healthcare services.
Copyright (c) 2025 luthfi bhaktiawan husag https://creativecommons.org/licenses/by-sa/4.0
Sentiment Analysis of User Reviews on the NU Online Application Using the Long Short-Term Memory (LSTM) Model
This study aims to analyze user sentiment toward the NU Online application by applying a Long Short-Term Memory (LSTM) model. The research was based on 13,576 user reviews collected from the Google Play Store, which underwent preprocessing, sentiment labeling, and Exploratory Data Analysis (EDA). To ensure balanced classification, undersampling was used, resulting in 6,612 reviews equally divided into positive and negative classes. The text data was processed using tokenization and padding before being input into the LSTM model. Model training involved the use of binary crossentropy, Adam optimizer, EarlyStopping, and ReduceLROnPlateau techniques. The model achieved 93% precision, recall, and F1-score, with low error rates and strong generalization ability. EDA results showed that positive feedback mainly focused on worship features like salat schedules, while negative reviews addressed technical issues such as the azan sound. User review peaks occurred during religious periods and major updates. A Gradio-based web interface was also developed to display results and enable user-friendly access to visual sentiment insights. This implementation proves the practical potential of integrating LSTM with an interactive platform for effective sentiment analysis
Copyright (c) 2025 Atik Muthmainnah, Wahab Syaroni, Ratri Enggar Pawening https://creativecommons.org/licenses/by-sa/4.0
Implementation of The Behaviorally Anchored Rating Scale Method for Employee Performance Evaluation of MSMEs in Surabaya City Based on Information Technology
Micro, Small, and Medium Enterprises (MSMEs) in Surabaya encounter persistent challenges in conducting objective evaluations of employee performance. To address this issue, the present study introduces the application of the Behaviorally Anchored Rating Scale (BARS), employing both qualitative and quantitative approaches supported by Information Technology (IT). BARS enables performance appraisal based on specific and observable work behaviors, thereby mitigating subjectivity and enhancing the fairness of evaluations. The integration of IT further streamlines data collection processes while reducing administrative complexity. In this study, an open-source web-based application was developed and customized to align with the operational requirements of MSMEs. The primary objective is to design and implement a performance evaluation system grounded in BARS and IT, supporting MSMEs in the formulation of realistic performance benchmarks and more effective human resource management practices. The research methodology adopts the ADDIE Research and Development model, encompassing the phases of analysis, design, development, implementation, and evaluation. System reliability was assessed through black box testing, with results indicating validity and consistency across all scenarios. The findings confirm the successful deployment of a multi-user web application capability in facilitating efficient, accurate, and systematic employee performance evaluations within MSMEs
Copyright (c) 2025 Erwin - Dhaniswara https://creativecommons.org/licenses/by-sa/4.0
Android-Based Monitoring of 110 Volt DC System in Substations within PLN UIT JBM Region to Improve Maintenance Efficiency
The DC 110 Volt system is a critical component in substations, serving to support the operation of control and protection devices. Instability in voltage or current within this system can result in serious failures in overall substation performance. Therefore, “Monitoring of the DC 110 Volt System in Substations within PLN UIT JBM Region Based on Android to Improve Maintenance Efficiency” in real time becomes crucial. This research aims to design and implement an Android-based monitoring system supported by Internet of Things (IoT) technology using the Blynk application. The main parameters monitored in the DC system are total DC voltage (positive and negative) within a range of 80–125 VDC and current within a range of 0–100 A, integrated with a microcontroller that transmits data to the Android application via data communication protocols. The data received by the application can be analyzed in real time, providing critical information regarding parameter deviations from operational standards. In addition, the system is equipped with an early warning feature that enables technicians to respond to potential disturbances before they affect substation operations. Based on sampling inspections of the DC system conducted by five personnel at five substations within the PLN UIT JBM region, the results show that using the DC monitoring system is more effective than manual measurements, with a time difference of 10–15 minutes. This demonstrates that the system can improve monitoring efficiency and reduce operational risks in substations. With the application of this technology, disturbances in the DC system can be detected earlier, allowing preventive actions to be carried out quickly and accurately.
Copyright (c) 2025 Erwin Dhaniswara https://creativecommons.org/licenses/by-sa/4.0
Digitization of Employee Attendance Processes Through a Web-Based QR Code System at MA Nurul Wahid al Wahyuni
The manual attendance process at MA Nurul Wahid al Wahyuni often causes various problems, such as late recording, inaccurate data, and potential fraud. Therefore, this study aims to design and implement a web-based employee attendance system by utilizing QR Code technology as a more efficient and accurate digital solution. The methodology used in developing this system is the Waterfall method, which consists of the stages of needs analysis, system design, implementation, testing, and maintenance. This system allows each employee to take attendance by scanning a QR Code via a mobile device, which automatically records the time and user identity into the database. The test results show that this system is able to increase the efficiency and accuracy of attendance recording, namely this system is proven to be able to speed up the attendance process and cannot be changed by ordinary users, as well as facilitate the management of attendance data by the administration department. With the implementation of this system, it is expected that the attendance process at MA Nurul Wahid al Wahyuni will become more modern, transparent, and integrated
Copyright (c) 2025 Abdul Karim https://creativecommons.org/licenses/by-sa/4.0
Designing a Solar Power Plant Emergency Box for Rapid Disaster Response in Bucor Wetan Village
The growing pursuit of sustainable agricultural development has driven efforts to combine renewable energy systems with Internet of Things (IoT) technology to improve efficiency and productivity in farming operations. This research focuses on the design and realization of a smart farming system powered primarily by solar energy. IoT-based sensing devices are integrated to continuously monitor parameters such as soil moisture, ambient temperature, and humidity, enabling automated irrigation management that conserves both water and energy resources. The photovoltaic (PV) module supplies stable electrical power, while collected data are transmitted to a cloud platform for remote access through a mobile interface. Experimental evaluation indicates that the proposed system decreases energy usage by approximately 35%, improves irrigation precision by 28%, and boosts crop yield by 20%. These outcomes demonstrate that the synergy between solar power and IoT technology plays a vital role in achieving sustainable agricultural systems and advancing the global objectives of energy transition and climate change mitigation.
Copyright (c) 2025 yanto wicaksono, Muhammad Jesen IsroAfifi, Ahmad Fulqin AlBasyi https://creativecommons.org/licenses/by-sa/4.0
Design and Evaluation of a Web-Based Geographic Information System for PPDB Promotion Zoning Based on Student-Origin Distributions
Advances in information technology have accelerated the digitalization of educational services, including Indonesia’s student admission process (PPDB). This study designs and evaluates a web-based Geographic Information System (GIS) to map student-origin distributions and construct promotion zones that guide PPDB outreach strategies. The system was built with CodeIgniter and Leaflet for interactive mapping, while applicant addresses/school origins were processed via geocoding. Outputs include point maps, density heatmaps, administrative-area aggregation (urban village/sub-district), and simple distance buffers (e.g., 1–3 km) to derive rule-based priority promotion zones (thresholds on density and proximity to the school). Evaluation comprised functional testing (black box) and user assessments using questionnaires (Likert/SUS). Results indicate that the system expedites registration, reduces the risk of data loss, simplifies data summarization, and provides promotion-zoning maps that help committees target outreach more effectively. The contributions are: (1) a PPDB web-GIS model that combines origin mapping with rule-based promotion zoning, (2) a replicable operational workflow, and (3) recommendations for future work, including advanced analytics dashboards and automated notifications
Copyright (c) 2025 Riko Muhammad Suri https://creativecommons.org/licenses/by-sa/4.0
Hybrid ViT–CNN Model for Automatic Monkeypox Skin Lesion Diagnosis
Monkeypox is a re-emerging zoonotic disease that presents with skin lesions resembling other dermatological conditions, which complicates reliable diagnosis. This study introduces a hybrid deep learning framework that integrates Vision Transformers (ViT) with Convolutional Neural Networks (CNN) for automatic classification of monkeypox lesions. Three hybrid scenarios were evaluated: ViT + DenseNet121, ViT + ResNet50, and ViT + InceptionV3. A combined dataset of PAD-UFES-20 and the Monkeypox Skin Lesion Dataset (MSLD), containing more than 2,500 dermoscopic images resized to 224×224 pixels, was used to train all models from scratch. Unlike prior works that relied on transfer learning and extensive augmentation, this study establishes a reproducible baseline without such enhancements. Model performance was assessed using accuracy, precision, recall, F1-score, and ROC-AUC, as well as computational efficiency metrics including training time and inference speed. The results show that hybrid ViT–CNN architectures achieved consistently better performance than single networks. Among the three scenarios, ViT + InceptionV3 provided the most balanced outcome, This approach combines reliable diagnostic accuracy with efficient inference. These findings demonstrate the value of integrating CNN-based local feature extraction with the global contextual modeling capacity of ViTs. This study establishes an experimental benchmark for monkeypox lesion classification and identifies hybrid architectures as a viable direction for future development. The framework can be extended with transfer learning, advanced augmentation, and lightweight optimization techniques, supporting potential deployment in resource-limited healthcare environments.
Copyright (c) 2025 Aji Triwerdaya https://creativecommons.org/licenses/by-sa/4.0
Raw Material Management Information System at D'Fans Coffee Using Web-Based Buffer Stock and FEFO Methods
Manajemen stok dan bahan baku yang efisien sangat penting untuk menjaga kelancaran operasional bisnis di industri minuman. Ketidakmampuan mengelola stok dapat menyebabkan kekurangan bahan baku, pemborosan, dan tingginya biaya operasional. Untuk mengatasi permasalahan tersebut, digunakan metode buffer stock untuk menyimpan cadangan stok tambahan yang dapat menghindari gangguan dalam proses produksi, sekalipun terjadi perubahan pasokan maupun permintaan. Selain itu, penerapan strategi First Expired First Out (FEFO) diperlukan untuk memantau kualitas bahan baku yang memiliki masa simpan terbatas, guna menghindari kerugian akibat produk kedaluwarsa. Perkembangan teknologi informasi memberikan dampak yang signifikan terhadap manajemen inventaris bagi Usaha Mikro, Kecil, dan Menengah (UMKM). Dengan beralih ke sistem digital, pemantauan stok dapat dilakukan secara akurat dan real time, sehingga memudahkan pemilik usaha untuk mengelola stok secara lebih fleksibel dan responsif terhadap perubahan permintaan pasar. D'Fans Coffee, salah satu UMKM di Medan, masih mengandalkan pencatatan manual yang berisiko terjadi kesalahan, terutama ketika volume transaksi tinggi. Kesalahan pencatatan ini dapat mengakibatkan perbedaan antara data yang tercatat dan kondisi aktual di gudang, sehingga mengganggu kelancaran operasional. Untuk itu, diperlukan sistem informasi inventaris yang mengintegrasikan metode FEFO dan Reorder Point (ROP) untuk menentukan waktu yang tepat untuk melakukan pemesanan ulang. Dengan penerapan sistem terintegrasi ini,
Copyright (c) 2025 Bayu Fadhli Erlangga Lubis, Muhamad Alda https://creativecommons.org/licenses/by-sa/4.0
A Product Recommendation-Based E-Commerce Application Using Collaborative Filtering at Izra Fashion Store
Digital transformation in the world of trade has shifted to E-Commerce in order to increase market share and efficiency. Izra Fashion Store, which is engaged in selling hijab, currently still relies on social media for marketing and interaction with customers. Although this method is quite effective, a more structured solution is needed so that the sales process can run more optimally. The use of a marketplace platform such as Shopee is actually an option, but tight competition, the number of similar stores, and the difficulty of getting positive reviews in a short time make it difficult for small stores to build customer trust. Therefore, this study aims to build a website-based e-commerce equipped with a product recommendation feature using the Collaborative Filtering method. Researching it using quantitative methods with the help of a descriptive approach. Data was collected through data collection and analysis of user needs, which were then used to implement the Collaborative Filtering algorithm in the product recommendation system. This system is assisted by the PHP programming language and MySQL database. The research findings show that the system built is able to improve the customer shopping experience by providing product recommendations that are more in line with their preferences. In addition, this system also helps business owners manage product and transaction data in a more organized manner. Through the existence of this e-commerce platform.
Copyright (c) 2025 Nurul Amanda Khairani Lubis, Samsudin Samsudin https://creativecommons.org/licenses/by-sa/4.0
Implementation of Smart Onion Counting and Environmental Sensing System with ESP32 MCU
The rapid development of embedded system technology in recent decades has had a significant impact, this advancement has contributed to an increase in production capacity with real-time monitoring trough embedded system MCU ESP32. The process of manufacturing onion products, such as fried shallots and garlic. The objective of this research is to develop a low-cost automatic onion counting system that utilizes an embedded system MCU ESP32 with integration of infrared sensors, temperature and humidity sensors to monitor production quality conditions in real-time for small scale Industry. Using the engineering design method, where the TCRT5000 sensor is employed to detect objects based on infrared light interruption, and environmental conditions are measured with the DHT22 sensor to maintain production quality. The internet connection for wireless communication for transmitting data to a mobile device through google firebase. Analysis was performed to evaluate performance such as, data transmission response time, and environmental sensor precision. The results obtained demonstrate that the system attained counting accuracy rates of 98.2% for garlic and 98.55% for shallots. with average data transmission response times of 1.51 seconds and 1.89 seconds, respectively, achieving a success rate of 97.15%. The environmental monitoring sensors demonstrated a high degree of accuracy, with a margin of error of 0.18 °C for temperature and 0.3% for humidity. The results show that this system works effectively in automating onion counting and monitoring, with an accuracy rate of over 98% and a response time of less than 2 seconds, making it suitable for small-scale automated production.
Copyright (c) 2025 Titiek Suheta, Andy Suryowinoto, Novian Patria Uman, Choirul Anam https://creativecommons.org/licenses/by-sa/4.0
Prototype of Automatic Plant Watering Control Based on Internet of Things Using Blynk App
Ornamental plants can grow both indoors and outdoors and can also be used for room decoration. Problems arise when plants don't get the water they need, resulting in insufficient or excessive watering, which can lead to poor growth. Therefore, the purpose of this research is to create a prototype automatic plant watering system to meet plant water needs. An automatic plant watering control system uses an on-off solenoid valve. This automatic plant watering system utilizes a monitoring method that can be remotely monitored using the Blynk IoT (Internet of Things) application in real time to determine soil moisture levels and indicators.Test results showed an average error value for ultrasonic sensor measurements of 0.65%. In soil moisture testing, the soil was dry at less than 38% humidity, damp at 38%-65% humidity, and wet at more than 65% humidity. The test results showed that the DC motor pump output will operate to flow water to the water storage tank if the ultrasonic sensor in the water tank measures the water level below the set point of 10 cm. The solenoid valve will be activated to flow water for the plant watering process if the soil moisture sensor detects a soil moisture value of less than 38%, then the solenoid will be activated until the soil moisture indicator value reaches 65%.
Copyright (c) 2025 Delila Permatasari https://creativecommons.org/licenses/by-sa/4.0
Application of Backpropagation Artificial Neural Networks for Optimizing Corn Production Prediction in Karo Regency
Corn production in Karo Regency, North Sumatra, plays a crucial role in supporting regional food security and the local economy. However, fluctuations in production caused by unpredictable environmental conditions and limited data-driven forecasting methods have made it difficult for policymakers and farmers to plan effectively. This study aims to address this problem by developing a model to predict corn production using the Backpropagation Neural Network (BPNN) method. The study utilized 302 cleaned datasets, with Planted Area and Harvested Area as input variables, and Production as the output variable. The dataset was divided into 70% for training and 30% for testing. Five BPNN architectures (ranging from 2-4-1 to 2-12-1) were tested using three activation functions (Sigmoid, ReLU, and Tanh), with a maximum of 200 iterations and a learning rate of 0.01. The best results were achieved by the 2-12-1 architecture with the Tanh activation function, obtaining an R-squared value of 94.86% and a Mean Squared Error (MSE) of 0.0039. These findings demonstrate that the Backpropagation Neural Network is effective for forecasting corn production and can serve as a valuable decision-support tool for sustainable agricultural planning in the region.
Copyright (c) 2025 Anjasmara Tarigan https://creativecommons.org/licenses/by-sa/4.0
Designing a Web-Based Digital Financial System for Islamic Boarding Schools with Payment Gateway Integration
Financial management in Islamic boarding schools still faces various fundamental problems, particularly due to dependence on manual recording and simple applications. This management pattern often causes delays in report preparation, increases the potential for recording errors, and reduces transparency. This condition impacts the trust of students' guardians and stakeholders. In addition, the diversity of student guardians, including those from outside the region, further complicates the payment process due to limited access to remote transaction services. This situation highlights the urgency of developing a web-based digital financial system that can effectively integrate modern payment technology and adapt to the needs of Islamic boarding schools. This study aims to design and implement a digital financial system for Islamic boarding schools by integrating the Midtrans payment gateway to improve financial management's efficiency, transparency, and accountability. The method used is a model consisting of three main stages: data collection through observation and interviews with financial managers, system design using use case diagrams, activity diagrams, and class diagrams, and system testing with internal and external black box testing approaches. The system implementation utilizes the Laravel framework, MySQL database, and web-based interface with Login, Dashboard, student data, payment, and financial reporting features. The results show that the developed System can comprehensively address the financial management needs of Islamic boarding schools. External testing using a Likert scale questionnaire obtained a rating of Good-Very Good with an achievement of up to 86%, thus confirming the feasibility of the system implementation. This System has been proven to facilitate online payments, accelerate the report preparation process, and improve access to information for student guardians. Thus, a web-based digital financial system integrated with a payment gateway can be a strategic solution for enhancing the transparency and accountability of pesantren finances. Further research is recommended to strengthen data security, expand coverage to multiple pesantren, and conduct continuous testing on a broader scale
Copyright (c) 2025 ahmad hudawi https://creativecommons.org/licenses/by-sa/4.0
Solar Cell Energy Utilization Using SEPIC Converter with Fuzzy Logic Control for Electric Stove
In this modern era, most household appliances require electrical energy as an energy source. The use of energy in large and sustainable amounts will cause an energy crisis. Where fossil fuels will run out and cannot be renewed. Therefore, renewable alternative energy is needed that can be used as an energy substitute for one of the solutions. One of the alternative energies is solar cell energy that to supply the energy needs of electric stoves. This study discusses photovoltaic system that use 10 solar cells each with a power of 100 WP and 90 VDC. The electrical energy generated from the solar cell is 1000 WP. From the solar cell, the voltage is increased using a Single-Ended Primary-Inductor Converter (SEPIC) converter and controlled using Fuzzy Logic Control (FLC). The output voltage is used to meet the power needs of an electric stove with a maximum power of 650 W which has an average efficiency of 93%.
Copyright (c) 2025 Ahmad Firyal Adila https://creativecommons.org/licenses/by-sa/4.0
Fleet Management Information System Design PT. Bagus Amelia Jaya Uses the User Method Web-Based Centered Design
This study discusses the design of a Fleet Management Information System at PT. Bagus Amelia Jaya using a User Centered Design (UCD) approach and developed as a web-based application with the Laravel framework. The company's main problems include manual recording, the lack of a structured fleet maintenance schedule, limited visibility of fleet and driver data, and minimal support for operational decision-making. The methodology used combines Research & Development (R&D) with the UCD cycle: understanding the context of use, determining user needs, generating design solutions, and conducting iterative evaluations through usability testing. The research results are a system design that provides fleet data modules, service schedules, operational expenses, role-based user management, and structured reporting. The UCD approach ensures the interface design is aligned with the company's workflow and reduces the learning curve for internal users. This research is expected to fill the gap in previous research that predominantly focuses on technical aspects without comprehensive user involvement.
Copyright (c) 2025 Bagus Rizki Lubis https://creativecommons.org/licenses/by-sa/4.0
MADM Method for Flower Type Selection in Ornamental Plant Watering Based on Microcontroller and Solar Panels
This research aims to develop an automatic watering system based on a microcontroller and solar panels, using the Multi-Attribute Decision Making (MADM) method to determine the type of flower that is suitable for the watering system. Solar panels are used as the main energy source to increase the efficiency and sustainability of the system. The Multi-Attribute Decision Making ( MADM) method with the SAW technique uses the highest ranking calculation. The types of ornamental plants are Bougainvillea, Monstera, Peace Lily (Spathiphyllum) and pothos. The highest ranking for the type of flower is the monstera flower with a weight value of 11.95. With this system, ornamental plant owners can more easily determine plants and care for their plants without the need for regular manual watering. In addition, the use of solar panels makes this system more energy efficient and environmentally friendly. The owner of the flower shop really welcomed this control system tool because it can save Rp. 36,000 per month for electricity costs for watering ornamental plants because all power can be generated by solar panels, namely 250 Watts per day with a panel size of 120 WP. The total power usage of the ornamental plant watering control system is 35.25 Watts. Solar panels produce less power in the morning, at 9-10 watts, and 96-99 watts in the afternoon. During hot weather, solar panels produce more power
Copyright (c) 2025 Tijaniyah Tijaniyah https://creativecommons.org/licenses/by-sa/4.0
Digital Transformation of Sugarcane Sales Administration at CV Al Ameen: Integration of Payment Automation and Visual Analytics for Distribution Optimization
The sales administration of sugarcane at CV Al Ameen, Jember, is still managed manually, resulting in risks such as inaccurate records, delays in shipment monitoring, and irregular fund disbursement. The lack of a centralized system hinders real-time transaction recapitulation and creates opportunities for fraud, particularly duplicate payment claims. These inefficiencies not only threaten financial accuracy but also undermine the reliability of business reporting. To address these issues, this study proposes a digital administration system that automates transaction recording, verifies payment claims, and improves distribution monitoring accuracy. The system integrates a Telegram Bot for payment automation and interactive visual analytics to monitor both distribution and financial transactions in real time. It is initially implemented as an offline local application to ensure accessibility, with the potential for future adaptation to web- or cloud-based platforms. Key features include automatic transaction recap, Telegram-based notifications, and periodic reporting to business stakeholders without the need for manual record-keeping. The Telegram Bot employs unique delivery identifiers to validate claims, ensuring that each payment request is processed only once, thereby reducing the risk of fraudulent activity. System communication is achieved through the Telegram API and webhook mechanism, enabling automated updates on new transactions, shipment status, and fund disbursement. Furthermore, the bot supports user queries for transaction summaries and payment reminders. The system development follows the Agile Model, which allows iterative design and continuous refinement in line with business partner requirements. The findings demonstrate that the integration of automation and analytics significantly enhances accuracy, efficiency, and transparency in sugarcane sales administration.
Copyright (c) 2025 Faiz Firdausi, Nely Supeni, Ferry Wiranto, Muhamat Abdul Rohim, Riza Bahtiar Sulistyan https://creativecommons.org/licenses/by-sa/4.0
Implementation of VLAN and ACL for Network Security at SDIT Ibnu Hajar Bekasi
In the age of modern technology, network security is essential to ensure that educational institutions operate properly. The purpose of this research is to improve the network security of SDIT Ibnu Hajar Bekasi City by applying technologies such as Virtual Local Area Network and Access Control List. This research uses the Network Development Life Cycle (NDLC) approach, which consists of the stages of initiation, planning, design, implementation, testing, and maintenance. By using vlan network segmentation, data traffic is divided into specific groups, such as administration, computer labs, instructors, and students. For now, Acls are used to set access rights between network segments according to user needs and authorization. Simulation testing on Cisco Packet Tracer shows that the implementation of vlans and acls improves network stability and security, reduces average latency, and decreases broadcast traffic. The acl configuration results show that students cannot access the teacher and administration networks. However, teachers can still access administration and laboratories. This study shows that the use of vlans and acls can improve the security and effectiveness of network management in schools.
Copyright (c) 2025 Taufik Rahman, Qori Aprianto https://creativecommons.org/licenses/by-sa/4.0