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Jurnal E-Komtek
Published by Politeknik Piksi Ganesha Indonesia
ISSN : 25803719     EISSN : 26223066     DOI : https://doi.org/10.37339/e-komtek.v4i2.269
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal E-Komtek (Elektro-Komputer-Teknik) is a Journal that contains scientific articles in the form of research results, analytical studies, application of theory, and discussion of various problems relating to Electrical, Computer, and Automotive Mechanical Engineering.
Arjuna Subject : Ilmu Komputer (semua kategori) - Visi Komputer dan Pengenalan Pola
Articles 31 Documents
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Search results for , issue "Vol 9 No 1 (2025)" : 31 Documents clear
Design of Automatic Fish Feeding Device Based on Arduino With RTC and Servo Motor in Ornamental Fish Pond Maulana, Rifki; Ardelia Astriany Rizki
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.1980

Abstract

Ornamental fish care requires regular feeding, but the owner's busy schedule is often an obstacle. This study aims to design an Arduino-based automatic fish feeder, using an RTC (Real Time Clock) module for time scheduling and a servo motor to drive the feeding mechanism. This system is designed to ensure that feed is given at the right time without manual intervention. The prototype of this tool was tested in an ornamental fish pond and showed satisfactory results. This tool is able to provide feed accurately according to a predetermined schedule, and the servo motor functions well in controlling feed distribution. The use of RTC has proven effective in maintaining time accuracy, ensuring that fish eating patterns remain consistent. This tool is also efficient in energy use and provides convenience for ornamental fish owners, reducing the risk of missed or excessive feeding. The results of this study indicate that this automatic feeding system can be a practical solution in ornamental fish care, with the potential to be further developed through the integration of IoT technology.
Design and Implementation of a Touch-Free Door Lock System Based on Arduino Susilo, Sidik; Muhamad Nurdin Latif; Erny Listijorini; Shofiatul Ula; Dewi Utami
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2161

Abstract

This study focuses on designing a touch-free door lock system based on Arduino, utilizing ultrasonic sensors, sound sensors, magnetic switches, and slot locks, following the Pahl and Beitz design methodology. The aim is to develop a reliable system that enhances convenience and reduces the need for physical contact with door locks. The results indicate that the ultrasonic sensor performs effectively in detecting distances, while the magnetic switch operates within a maximum reading range of 10 mm. However, the sound sensor demonstrated low accuracy, requiring multiple claps for successful detection. The findings suggest that the developed product functions as intended, though the limitations of the sound sensor highlight the need for further improvements to optimize precision and responsiveness.
Daily Container Volume Throughput Forecasting at Container Terminal Using Long-Short Term Memory (LSTM) Recurrent Neural Network Kasanah, Yulinda Uswatun; Miftahol Arifin; Famila Dwi Winati; Fatbayani
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2214

Abstract

Container throughput is an important indicator for measuring the efficiency of a kontainer terminal. Kontainers that enter and exit are those transported to and from the terminal, respectively. Kontainers are stacked in the kontainer yard before they leave the terminal. Handling these kontainers accounts for a major workload at the terminal. Therefore, accurate short-term forecasting of daily kontainer gate-in and Gate-Out at a kontainer terminal is crucial for operational planning. While most forecasts are made at the strategic level of overall kontainer throughput, this study focuses on the daily kontainer gate-in and Gate-Out quantities with a case study at the TPKNM Makassar Kontainer Terminal. The study results show that the Epoch for each training set and performance metrics for each feature are 10, 50, and 100. Based on this, the difference in prediction performance with different epoch sizes is quite significant. The larger the Epoch, the smaller the MSE level.
Optimization of Gamification Type Selection in Pop-Up Campaigns to Enhance Customer Engagement on E-Commerce Platform XYZ Using the Analytical Hierarchy Process Method Kesy Apriansyah; Hakim, Dimara Kusuma; Feri Wibowo; Supriyono
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2265

Abstract

One of the key success factors in the e-commerce industry is the increase in consumer engagement. High engagement has been proven to drive sales growth and customer loyalty. To achieve this goal, the application of gamification in marketing campaigns has been shown to have a significant impact on customer engagement in e-commerce. This study aims to optimize the selection of gamification types in pop-up campaigns to enhance consumer engagement on the XYZ e-commerce platform. The selection of the right type of gamification is crucial, but it is often influenced by subjectivity in assessment. To that end, this research uses the Analytic Hierarchy Process (AHP) method, which integrates historical data as a reference in filling alternatives based on criteria to reduce the subjectivity of the AHP method in determining the most effective type of gamification based on the criteria of Click-Through Rate (CTR), Conversion Rate (CR), and Impression. The research results show that the Memory Card type of gamification is the most effective type with the potential to increase consumer engagement. This approach is expected to serve as a reference for e-commerce platforms in designing more effective and data-driven gamification strategies.
The Application of Smart Contracts in Cybersecurity for Threat Detection and Response Prasetyo, Stefanus Eko; Wijaya, Gautama; ., Kennedi
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2285

Abstract

Cybersecurity is becoming an increasingly important issue in the digital era due to the rise in threats and attacks on information systems. One innovative technology with great potential to enhance cybersecurity is smart contracts. This article discusses the application of smart contracts in detecting and responding to cybersecurity threats. With their automatic, transparent, and immutable nature, smart contracts can be used to manage threat responses in real-time, improve attack detection efficiency, and minimize the risk of human error. This study also explores use cases such as secure data access management, blockchain-based anomaly detection, and incident response automation. Furthermore, implementation challenges such as scalability, interoperability, and smart contract code vulnerabilities are also addressed to provide a comprehensive overview. Through the integration of smart contracts into cybersecurity, this article concludes that this technology holds great potential to strengthen information systems' resilience against increasingly complex and dynamic threats.
Comparative Analysis of the Accuracy of Multiple Linear Regression Method and Ridge Regression Method in Predicting Dengue Fever Cases in South Tangerang City Dina Aulia; Herman Bedi Agtriadi; Luqman
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2292

Abstract

One of the main health issues in South Tangerang City is dengue fever (DBD). This study aims to compare the accuracy of Multiple Linear Regression and Ridge Regression methods in predicting the number of DBD cases using weather data such as temperature, humidity, and average rainfall. The data used is monthly data from South Tangerang City. The analysis process includes preprocessing, splitting the dataset into training and testing data, and applying both regression methods. To determine the prediction error rate, model accuracy is evaluated using the Mean Absolute Percentage Error (MAPE) metric. The results indicate that Ridge Regression performs better for datasets with high multicollinearity, yielding a MAPE value of 20.12%, while Multiple Linear Regression is more effective for datasets with low feature correlation, showing a MAPE value of 44.6%. This study provides important insights into selecting predictive techniques based on the characteristics of the analyzed dataset. It is hoped that this research can improve mitigation and planning for DHF cases in South Tangerang City by choosing the appropriate approach.
Analysis of Long Short-Term Memory (LSTM) and Extreme Gradient Boosting (XGBoost) Algorithms to Predict the Number of Airplane Passengers at Makassar Sultan Hasanuddin International Airport : Systematic Literature Review Ainul Idham; Efy Yosrita
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2298

Abstract

This study compares the performance of Long Short-Term Memory (LSTM), Extreme Gradient Boosting (XGBoost), and hybrid techniques to forecast the number of aircraft passengers. This analysis was carried out utilizing the Systematic Literature Review (SLR) method and the PRISMA approach. Only 11 of the 44,564 items filtered during the initial round met the inclusion requirements. The LSTM model performed well in capturing time series patterns, however XGBoost was more robust when employed on data with noise and outliers. The hybrid model (LSTM + XGBoost) performed the best, with an average accuracy of 96%, RMSE of 0.015, and MAPE of 2.45%. This demonstrates that the hybrid technique is quite good in predicting the number of airplane passengers, particularly for complicated, dynamic, and seasonal time series data. These findings are recommended for the development of machine learning-based prediction systems for airports.
Literature Study: Prediction of the Type of Company where Students Work Using Naïve Bayes and Neural Network Algorithms Saputra, Angga; Luqman; Herman Bedi Agtriadi
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2314

Abstract

Research was conducted to evaluate the effectiveness of various machine learning algorithms, such as Naive Bayes, Support Vector Machine, Random Forest, and Artificial Neural Network (ANN), in predicting and classifying data. Naive Bayes proved to be efficient and accurate in structured data classification, such as predicting alumni's waiting time to get a job (94%) and vocational school students' job readiness (96.95%). On the other hand, neural network methods such as ANN and GRNN are superior in handling non-linear regression problems, such as house price prediction or college students' study period, although there is still room to improve accuracy. Random Forest is more suitable for complex data, while Naive Bayes is more effective for simple data. This research emphasizes the importance of selecting relevant variables, such as gender, major, and GPA, to improve model performance. Therefore, the selection of machine learning methods should be tailored to the type of data and the purpose of the analysis, as each algorithm has its own advantages and disadvantages.
Design and Implementation of a QR Code-Based Attendance Application at SMA Negeri 1 Cangkringan Muhammad Hilmiawan Sulthoni; Vikky Aprelia Windarni; Surya Tri Atmaja; Dewi Anisa Istiqomah; Fiyas Mahananing Puri
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2392

Abstract

The manual attendance system at SMA Negeri 1 Cangkringan still faces various obstacles, such as the time-consuming recording process, the risk of data loss, and the possibility of manipulating student attendance. Overcome these problems, a web-based student attendance application was developed using the Waterfall method. The method used in completing this system is the waterfall method, which consists of needs analysis, system planning, development, and testing. The system is designed using web technology, which allows better accessibility for teachers and administrative staff in recording attendance in real-time. The result of the user-friendly application design, allows teachers to record student attendance quickly and accurately. The system is also a report feature that can be accessed easily, making it easier to make decisions regarding student attendance. It is expected that the administration process at SMA N 1 Cangkringan can be more efficient, transparent, and reliable.
Optimization of Double Exponential Smoothing Model for Daily Earth Temperature Forecasting in Dayeuhluhur, Cilacap Ridzna Asep Purwanto; Hakim, Dimara Kusuma; Supriyono; Harjono
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2396

Abstract

Global warming has caused an increase in the Earth's surface temperature, which has a significant impact on the environment and human life. This study aims to predict the daily surface temperature in Dayeuhluhur District, Cilacap, for the next one year using the Double Exponential Smoothing (DES) method. The data used comes from the NASA POWER platform with a time span of 2015 to 2025, including three main variables: earth surface temperature (TS), solar radiation (ALLSKY_SFC_SW_DWN), and maximum 10-meter wind speed (WS10M_MAX). Preprocessing was done by removing February 29 in leap years and applying annual differencing (lag 365) to stabilize the seasonal pattern. Smoothing parameters α and β were optimized based on Mean Absolute Percentage Error (MAPE) values. Results show a moderate and consistent increasing trend in temperature, with the best accuracy in the temperature variable (MAPE 2.41%), followed by solar radiation (21.56%) and wind speed (30.18%). This method proves effective in forecasting temperature with clear seasonal patterns and contributes to supporting data-driven climate change mitigation policies.

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