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Infact: Jurnal Sains dan Komputer
Published by Universitas Kristen Immanuel
ISSN : 25278363     EISSN : 28290259     DOI : https://doi.org/10.61179/infact
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal sains dan komputer (INFACT) berisi artikel bidang informatika dengan scope:  Database Management,  Computer Networks,  Software Engineering,  Graphics and Multimedia,  Theory of Computation,  Web Technology,  Soft Computing,  Web Data Management,  Software Quality Testing,  Artificial Intelligence,  Robotics,  Augmented and Virtual Reality,  Mobile application development,  Cloud and Big Data,  Cyber security,  Data Mining,  Information Retrieval,  Multimedia Technology,  Mobile Computing,  Artificial Intelligence,  Computer Vision,  Image Processing, dan Internet of Things
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 73 Documents
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Iot-Based Early Fire Detection System Uses MQ-2 Smoke Sensor And DS18B20 Temperature Sensor Aulyah Zakilah Ifani; Muhammad Iqra Nur Fajar; Athaillah Aufa Badila
Infact: International Journal of Computers Vol. 10 No. 01 (2026): Journal of Science and Computers
Publisher : Universitas Kristen Immanuel

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61179/infact.v10i01.763

Abstract

Fire disasters remain a major threat in Indonesia, especially in dense housing, offices, and industrial zones. Delayed detection leads to heavy property losses and fatalities, since blazes are often noticed only after flames grow and smoke spreads. This study introduces an IoT early warning system combining an MQ-2 smoke sensor and a DS18B20 temperature sensor on a NodeMCU ESP8266. Using the ADDIE model—analysis, design, development, implementation, evaluation—the prototype was built and tested in laboratory simulations. Tests show the MQ-2 detects smoke at ?400 ppm, while the DS18B20 measures temperatures ?60 °C with ±0.5 °C precision. The dual-sensor setup delivers over 95 % accuracy, alerts within two minutes, and keeps false alarms below 5 %, providing an effective and economical tool for urban fire mitigation. Its low-cost components and Wi-Fi connectivity enable real-time alerts to smartphones or control rooms, facilitating response and scalable deployment in communities.
Intelligent Service Quality Asse Aspect-Based Sentiment and Emotion Analysis on Online Reviews Using DistilBERT Method for Service Quality Evaluation: Aspect-Based Sentiment and Emotion Analysis on Online Reviews Using DistilBERT Mika, Jatmika; Zebua, Yuwinda Hartati; Berutu, Sunneng Sandino
Infact: International Journal of Computers Vol. 10 No. 01 (2026): Journal of Science and Computers
Publisher : Universitas Kristen Immanuel

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61179/infact.v10i01.807

Abstract

The growth of online reviews on digital platforms has made consumer opinions an important source for understanding perceptions of service quality in businesses. This study aims to analyze aspect-based sentiment and emotion from consumer reviews using the Distilled Bidirectional Encoder Representation from Transformers (DistilBERT) method. Data were collected from Google Reviews and processed through text preprocessing, aspect extraction, sentiment and emotion labeling, and fine-tuning of the DistilBERT model. Sentiment analysis was classified into three classes (positive, negative, and neutral), while emotion analysis included five categories (happy, angry, disappointed, sad, and neutral). The evaluation results show that the DistilBERT model achieved excellent performance in sentiment classification with an accuracy of 95.00%, precision of 93.60%, recall of 95.00%, and F1-score of 94.22%. For emotion classification, the model achieved an accuracy of 94.00%, precision of 88.36%, recall of 94.00%, and F1-score of 91.09%. These findings indicate that a Transformer-based approach is effective in understanding the contextual meaning of consumer reviews despite the use of a relatively limited dataset. This study concludes that DistilBERT is capable of providing accurate and efficient aspect-based sentiment and emotion analysis, which can be utilized as a foundation for evaluating and improving service quality and digital business reputation.
Prototype of an Automated Item Sorting System Using a Barcode Scanner and Servo-Based Directional Control with Microcontroller julfanny, syarif rizal
Infact: International Journal of Computers Vol. 10 No. 01 (2026): Journal of Science and Computers
Publisher : Universitas Kristen Immanuel

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61179/infact.v10i01.821

Abstract

The increasing demand for efficiency in logistics and manufacturing highlights the limitations of manual sorting systems, which are prone to errors and inefficiency under high-volume conditions. Existing automated sorting systems often rely on multiple sensors or complex configurations, resulting in higher costs and system complexity. This study aims to develop a cost-effective and simplified automated sorting prototype using a single barcode scanner integrated with servo-based directional control. The system is designed using an Arduino Mega 2560 microcontroller, GM66 barcode scanner, infrared sensors, DC conveyor motors, and MG996R servo motors. The proposed method involves object detection, barcode identification, data processing, and directional sorting based on predefined servo angles. Experimental results show that the system successfully performs automated sorting with an overall success rate of 50%, demonstrating functional feasibility despite mechanical limitations. It can be concluded that the proposed system offers a practical and economical solution for prototype-scale automated sorting applications.

Page 8 of 8 | Total Record : 73

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