cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Dyah Palupiningtyas
Contact Email
2025100044@widyakarya.ac.id
Phone
+628812995758
Journal Mail Official
jurnallpkd@gmail.com
Editorial Address
Perum. Bumi Pucang Gading, Jl. Watu Nganten 1 No. 1-6 Desa Batursari Kec. Mranggen, Jawa Tengah
Location
Kota semarang,
Jawa tengah
INDONESIA
Jurnal Informatika Dan Tekonologi Komputer
Published by Pusat Riset dan Inovasi Nasional
ISSN : 28099249     EISSN : 28099230     DOI : https://doi.org/10.55606/jitek.v5i1
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Other
Jurnal Informatika dan Teknologi Komputer (JITEK), dan P-ISSN:2809-9249 (Cetak) dan E-ISSN:2809-9230 (Online). Jurnal JITEK diterbitkan Pusat Riset dan Inovasi Nasional, terbit setahun Tiga kali (Maret, Juli dan November) menerapkan proses peer-review dalam memilih artikel berkualitas berdasarkan penelitian ilmiah dan teoritis.Jurnal ini terakreditasi SINTA 4 (Surat Keputusan Direktur Jenderal Pendidikan Tinggi, Riset, dan Teknologi Nomor 10/C/C3/DT.05.00/2025 tanggal 21 Maret 2025 tentang Peringkat Akreditasi Jurnal Ilmiah Periode I Tahun 2025) dimulai dari Volume 2 Nomor 2 Tahun 2022 sampai Volume 7 Nomor 1 Tahun 2027. JITEK diterbitkan untuk mengembangkan dan memperkaya diskusi ilmiah bagi para sarjana dan penulis yang menaruh minat pada isu-isu Teknologi dan penerapannya. Redaksi menerima artikel berbasis teori dan penelitian. Cakupan keilmuan Jurnal ini mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 141 Documents
 9   10   11   12   13 
SmartElectra: Sistem Cerdas Pengendali Aliran Listrik Berbasis Android untuk Otomasi Rumah Modern
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i2.6220

Abstract

In the digital transformation era, the demand for automation in household electrical systems continues to grow to improve energy efficiency and user convenience. Traditional manual control of electrical devices is considered inefficient and lacks integration with current smart technologies. This research addresses the problem by designing a smart electrical control system, SmartElectra, which allows users to remotely monitor and control the flow of electricity using an Android-based application. The system integrates the ESP32 microcontroller, a relay module, and a Wi-Fi network to receive and execute commands from the mobile application. The Android interface was developed using MIT App Inventor, enabling seamless wireless communication with the hardware. Testing was conducted to evaluate the system’s responsiveness, control accuracy, and communication range in a typical residential setting. Results show that SmartElectra effectively controls electrical loads with an average response time of 1.2 seconds and reliable operation within a 20-meter range. With its dual-core processing power and built-in wireless capabilities, the ESP32 provides a robust and scalable foundation for smart home applications. This system presents a cost-effective, user-friendly solution that enhances energy management and remote control in modern households.
Optimasi Pembangkit Hybrid Energi Terbarukan Pada Kampus Vokasi ATS Menggunakan Metode Wild Horse Optimization (WHO)
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i2.6322

Abstract

The use of renewable energy sources has become widespread throughout the world as a step to reduce dependence on fossil energy. Hybrid electric power systems that use renewable energy as their base have been adopted as a solution to produce energy efficiently. In this paper, the hybrid system discussed is hybrid PV, wind turbine and battery storage. This hybrid design system is very dependent on the load profile, potential energy sources, and geographical location of the research location. This research discusses the technical design and capital costs of a hybrid electric power system which will be implemented as a practicum alternative energy source on the ATS campus, Sorowako. Irradiance, temperature, average wind speed and component sizing are the main parameters discussed. Design technical and economic analysis (capital cost) using MATLAB software with the wild horse optimization (WHO) algorithm. The results of the WHO analysis will be compared with the analysis of a common optimization method, namely PSO. And the results obtained from the WHO and PSO analyzes are not much different, but the WHO analysis reaches its convergence value faster, namely in the 20th iteration, while the PSO analysis reaches its convergence value in the 40th iteration. The capital cost value obtained by the WHO analysis is $ 198,363.05 with a total of 772 PV units, a total of 1 unit of WT, and a total of 54 batteries.
SmartBin Medis Berbasis AI dan Edge Computing untuk Manajemen Limbah Klinis yang Higienis
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i2.6385

Abstract

Medical waste presents a serious threat to health and the environment if not properly managed, especially in clinical facilities that require high hygiene standards. Manual waste disposal is still commonly practiced, which increases the risk of cross-contamination and reduces operational efficiency. This research aims to design and develop an automated and hygienic SmartBin system for medical waste using Artificial Intelligence (AI) and edge computing technologies without relying on internet connectivity. The system employs distance and weight sensors controlled by an Arduino Uno R3 microcontroller, along with a local image recognition module to classify medical waste based on type. All classification and system responses are processed locally to ensure fast and independent operation. A notification feature using visual and audio indicators is included to alert staff when the bin is full or when hazardous waste is detected. Testing conducted in a simulated clinical environment demonstrated a classification accuracy rate of 92% and reduced direct human contact by up to 85%. This study concludes that the SmartBin system, powered by AI and edge computing and supported by the Arduino Uno R3, offers an effective solution for improving hygiene and safety in medical waste management.
Sistem Jemuran Otomatis Berbasis Deteksi Visual dan Sensor Hujan dengan ESP32
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i2.6597

Abstract

Unpredictable weather in tropical regions often disrupts clothes drying activities, as sudden rain can cause clothes to become wet again. To address this issue, this study developed an automatic clothes drying system based on ESP32-CAM that can detect weather conditions using two main methods: sky image analysis and rain sensors. The system periodically captures sky images using the ESP32-CAM camera, then analyzes the brightness and contrast of the images to determine weather conditions, with brightness thresholds < 100 and contrast > 30 indicating cloudy weather. Data from the rain sensor is used as additional verification to enhance system accuracy. The decision-making logic combines both data sources to determine whether the clothesline should be retracted or left open. Offline image classification results show an accuracy of 93.67%, while direct testing against 10 weather scenarios yields a system accuracy of 100%. With its high performance and adaptive response to weather changes, this system demonstrates significant potential for implementation as an Internet of Things (IoT)-based home automation solution.
Pengembangan Aplikasi Web untuk Pemantauan Konsumsi Energi Listrik
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i2.6619

Abstract

The need for an efficient electrical energy consumption monitoring system is increasingly urgent in the digital era, especially to overcome power wastage due to the large number of electronic devices used. This research aims to develop a web application. The method used in this research is the experimental method with a system engineering approach, through the user interface. The application was built using PHP, HTML, CSS, and MySQL, and integrated in the XAMPP environment. The test results show that the application is able to display energy data interactively, both in graphical and tabular form, and provide reports in PDF and Excel formats. The system also provides the feature of controlling devices such as lights and fans through the dashboard, thus increasing efficiency and user convenience in managing energy consumption. With its comprehensive features and user-friendly interface, this application is expected to be an effective solution in supporting energy savings.
Prototipe Sensor Pendeteksi Kebakaran Hutan Berbasis Transmisi LoRa dan Solar Panel
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i2.6745

Abstract

Forest fires are a frequent disaster in Indonesia, especially during the dry season, which has serious impacts on ecosystems, public health, and economic conditions. This research aims to design a prototype Internet of Things (IoT)-based forest fire early detection system supported by LoRa transmission technology and Thingspeak cloud storage platform. The system uses DHT22 sensors to measure temperature and humidity, MQ-2 sensors to detect the presence of gas and smoke, and solar panels as the main power source to support energy efficiency in the field. LoRa was chosen as the communication medium due to its ability to transmit data over long distances with low power consumption. Data read by the sensors is regularly sent to ThingSpeak and displayed graphically with an average transmission delay of 15 seconds. Tests have shown that the system is able to accurately recognize potential fires and send out early warnings quickly. In this way, the system can be an efficient and energy-saving solution for remote forest areas. Overall, this prototype has successfully demonstrated its potential as a reliable and innovative forest fire mitigation tool.
Analisis Sentimen Ulasan Pengguna Aplikasi Threads di Google Play Menggunakan Algoritma XGBoost Dengan Penguatan SMOTE
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i2.6832

Abstract

Threads is a text-based social media application developed by Meta that has gained significant popularity since its launch. However, user reviews on the Google Play Store reveal an imbalanced sentiment distribution, with a dominance of positive sentiment, potentially reducing the accuracy of sentiment classification models. This study aims to evaluate the effectiveness of combining the Extreme Gradient Boosting (XGBoost) algorithm with the Synthetic Minority Over-sampling Technique (SMOTE) to address the data imbalance in user reviews of the Threads application. The dataset consists of 1,000 user reviews, which underwent preprocessing steps including case folding, cleaning, tokenization, stopword removal, and stemming. The data were then represented using the TF-IDF weighting method and analyzed using XGBoost, both before and after applying SMOTE. Results show that without SMOTE, the model achieved an accuracy of 87.60%, with a low recall for the negative class (0.69). After applying SMOTE, accuracy improved to 97.49%, and recall for the negative class reached 0.99, with balanced F1-scores for both positive and negative classes (0.98 and 0.97, respectively). These findings demonstrate that SMOTE is effective in handling class imbalance and enhancing model performance. In conclusion, the integration of XGBoost and SMOTE significantly improves fairness and accuracy in sentiment classification of app reviews, offering valuable insights for the application of machine learning in user opinion analysis. Future research is recommended to use larger datasets and consider deep learning models such as BERT.
Pengembangan Sistem Keamanan berbasis Cloud dengan Analisis Efek Avalanche pada Jaringan Perusahaan yang Mengadopsi Infrastruktur Cloud
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i2.6913

Abstract

By adding cloud infrastructure to the company's network, there are new challenges for data security, especially related to the increasing possibility of complex cyberattacks.The main weakness of traditional systems is their inability to detect small changes in data, which can lead to data breaches.The purpose of this article is to build a cloud-based network defense system that utilizes avalanche effect analysis to enhance anomaly detection.Cryptographic algorithms with high avalanche effects are used in the simulation of cloud-based corporate networks in this study.After simulating attacks on the tested system, data is collected and then analyzed to evaluate the effectiveness and sensitivity of detection.To conduct validation tests, metrics such as detection accuracy and response time are used to compare the system's performance with conventional methods.The research results show that the use of algorithms with significant avalanche effects can enhance the system's ability to detect small suspicious changes in data, thereby reducing the likelihood of hidden attacks.The results show that adding avalanche features to the cloud defense system can enhance the company's network defense against current threats.Additionally, it has been proven that the developed system enhances operational efficiency without compromising network performance.To enhance adaptation to new attack patterns and test the system on a real implementation scale, further research must be conducted.
Implementasi AR dan LMS untuk Meningkatkan Kompetensi Siswa SMK : Studi Kasus Jurusan Perhotelan
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i2.7062

Abstract

This study examines the effectiveness of the integration of Augmented Reality (AR) technology and Learning Management System (LMS) on improving the skills of vocational high school students majoring in hospitality and culinary arts. Qualitative findings show time efficiency, technical challenges, and training needs. This study recommends the integration of WebXR-based AR to overcome the limitations of device specifications in vocational high schools. Objective: To assess the effectiveness of AR and LMS in improving practical skills and learning management in vocational high schools. Method: Mixed-method research with quasi-experimental (30 hospitality students, 30 culinary students) and LMS analysis using log activity data from Moodle. Results: AR improves the understanding of housekeeping practices by 28% (paired sample t-test, p<0.05), while LMS reduces teacher administration time by 40%. Conclusion: AR-LMS integration has the potential to be a cost-effective solution for vocational high schools.
Klasifikasi Konten Thumbnail TikTok untuk Deteksi Kata Kasar Menggunakan Support Vector Machine (SVM)
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i2.7091

Abstract

The rapid growth of the social media platform TikTok has introduced new challenges in content moderation, particularly in detecting offensive language that appears not only in text form but also in visual elements such as video thumbnails. This study aims to develop a classification model capable of detecting offensive content in TikTok thumbnails using the Support Vector Machine (SVM) algorithm. Data were collected through web scraping of 4,153 TikTok videos containing offensive elements, which were then processed and manually labeled into 24 classes of offensive words. The dataset was divided into training and testing sets with a ratio of 20:80. Model performance was evaluated using AUC, accuracy, precision, recall, F1-Score, and Matthews Correlation Coefficient (MCC). The results show that the SVM model achieved an AUC of 0.791, indicating a reasonably good ability to distinguish between classes. However, accuracy (0.340), precision (0.293), recall (0.340), F1-Score (0.298), and MCC (0.264) indicate that the classification performance remains low. These findings suggest the need to improve Preprocessing quality, select more representative visual features, and develop more advanced classification methods. This research contributes to expanding the detection approach of harmful content from text-based to visual-based domains and lays the groundwork for more comprehensive automated content moderation systems in the future.

Page 11 of 15 | Total Record : 141

 9   10   11   12   13 

Filter by Year

2021 2025


Reset
Filter By Issues
All Issue Vol. 5 No. 3 (2025): November : Jurnal Informatika dan Tekonologi Komputer Vol. 5 No. 2 (2025): Juli : Jurnal Informatika dan Tekonologi Komputer Vol. 5 No. 1 (2025): Maret : Jurnal Informatika dan Tekonologi Komputer Vol. 4 No. 3 (2024): November: Jurnal Informatika dan Teknologi Komputer (JITEK) Vol. 4 No. 1 (2024): Maret : Jurnal Informatika dan Tekonologi Komputer Vol. 3 No. 3 (2023): November : Jurnal Informatika dan Tekonologi Komputer Vol. 3 No. 2 (2023): Juli : Jurnal Informatika dan Teknologi Komputer Vol. 3 No. 1 (2023): Maret : Jurnal Informatika dan Tekonologi Komputer Vol. 2 No. 3 (2022): November : Jurnal Informatika dan Teknologi Komputer Vol. 2 No. 2 (2022): Juli : Jurnal Informatika dan Teknologi Komputer Vol. 2 No. 1 (2022): Maret : Jurnal Informatika dan Teknologi Komputer Vol. 1 No. 3 (2021): November : Jurnal Informatika dan Teknologi Komputer Vol. 1 No. 2 (2021): Juli : Jurnal Informatika dan Teknologi Komputer Vol. 1 No. 1 (2021): Maret : Jurnal Informatika dan Teknologi Komputer More Issue