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Journal of Applied Information, Communication and Technology (JAICT)
Published by Politeknik Negeri Semarang
ISSN : 25416340     EISSN : 25416359     DOI : https://doi.org/10.32497/jaict
Core Subject : Engineering,
Engineering
Focus of JAICT: Journal of Applied Information and Communication Technologies is published twice per year and is committed to publishing high-quality articles that advance the practical applications of communication and information technologies. JAICT scope covers all aspects of theory, application and design of communication and information technologies, including (but not limited): Communication and Information Theory. Mobile and Wireless Communication, Cognitive Radio Networks. Ad Hoc, Mesh, Wireless Sensor Network, Distributed System and cloud computing Computer networking and IoT Optimization Algorithms, Artificial intelligence, Machine Learning, and Adaptive System.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 5 Documents
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Search results for , issue "Vol. 9 No. 1 (2024)" : 5 Documents clear
Quick Response Anti-Theft Measures in Jewelry Stores and Banks Utilizing the Internet of Things Widodo, Sarono; Bramantyo, Hutama Arif; Wardihani, Eni Dwi; Yulianto, Taufiq; Helmy, Helmy; Wasito, Endro; Daffa, Muhammad; Yuliana, Lutfi
JAICT Vol. 9 No. 1 (2024)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v9i1.5113

Abstract

The act of theft is a prevalent criminal activity within society, particularly observed in financial institutions and jewelry establishments, owing to the significant economic worth associated with valuable assets like currency, gold, and diamonds. Certain locations lack an integrated security system that interfaces with law enforcement, hence posing challenges for victims to report criminal incidents, particularly in cases involving armed or violent attackers. Hence, the purpose of this final project tool is to streamline and expedite theft reporting by leveraging the capabilities of the Internet of Things. This tool gathers empirical data in the form of visual representations, geographical coordinates, and temporal information pertaining to an incident. The development process employs the waterfall methodology, characterized by an average data transmission speed of 21.5 seconds and a database-to-telegram latency time of around 3.85 seconds. The complete duration encompassing the stages of detection and subsequent notification via telegram amounts to approximately 25.35 seconds. The test results indicate a location tolerance of around 5-10 meters relative to the test spot.
Implementation Of IoT In Nila Fish Cultivation With Bioflock System Wasito, Endro; Prahara, Tahan; Nursyahid, Arif; ., Dadi; Anggraeni K., Sri
JAICT Vol. 9 No. 1 (2024)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v9i1.5309

Abstract

In cultivating tilapia using the biofloc system, maintaining water quality (temperature, pH, turbidity) is not only for the health of the fish but also for the reproduction of the biofloc. So that water quality is known, sensors connected to IoT are installed. Sensor output data is processed by Arduino and sent to a data base server via the internet network so that water quality parameters can be monitored at any time via the internet network. This system was created in research entitled "Optimizing Tilapia Cultivation of Biofloc Systems with the Internet of Things". The pool has a diameter of 2m, height 1m, airator 500 liters/min, 4 airstones @ 30 liters/min. After the pond is assembled and the biofloc has grown (made from 375 ml multi-probiotic, 300 ml molasses, 150 gram dolomite, 60 gram nitrobacter), proceed with adding 150 tilapia fish seeds 5-6 cm long (weight 22.2 gr/fish). After 2 months the growth of the tilapia became 12-13 cm long (weighing 100 g/fish), with 2% mortality. The sensor measurement results displayed on the website are as follows: average pH values (5.6-7.5), temperature (27-29), turbidity (225-354) ppm, floc density (20-25) ml/liter. Hiprofit 781-3 feed is 13.4 kg. The research results show that IoT implementation can display the water quality of biofloc tilapia ponds in real time. pH fluctuations from 5.6-7.5 indicate that biofloc can function well.
Implementation Control And Monitoring System Water Quality of Koi Fish Ponds Based On the Internet Of Things Enriko, I Ketut Agung
JAICT Vol. 9 No. 1 (2024)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v9i1.5379

Abstract

Koi fish is one of the ornamental fish that is in great demand and has a fairly high price. Water quality plays an important role in the success of keeping koi fish. The quality of koi fish water must be at an ideal temperature of 25-30 °C and an acidity level or pH of 7-8 pH. The level of salt contained in water for koi fish must also be considered. A pond with a size of 200 x 50 x 100 cm requires a salt content of 1 to 2 ppm. Giving this salt is done to prevent the growth of bacteria in the koi pond which can come at any time. Ignorance of pond owners about the value and condition of water quality can disrupt the health of koi fish which can cause death. Based on these problems, the authors created a water quality control and monitoring system in koi fish ponds. The system created consists of a pH sensor, temperature sensor, and salinity sensor, and uses the Message Queuing Telemetry Transport (MQTT) protocol. The process of sending data to the IoT platform using a WiFi network. Based on the temperature sensor test, there is an average error of 1.4% with a sensor accuracy level of 98.6%. Testing the pH sensor and salinity sensor using the linear regression method. As for the pH sensor, the average error is 2% with an accuracy rate of 98%. The results of the salinity sensor test obtained an average error value of 7.6% with an accuracy rate of 92.3%. Then in the MQTT protocol, the parameters for delay and jitter have a bad category, while throughput has a moderate category, and packet loss has a very good category according to the TIPHON standard.  
Pomelo Orange Desease Detection Using CNN Based on Digital Image Processing Shaleh, Thariq Muhammad
JAICT Vol. 9 No. 1 (2024)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v9i1.5321

Abstract

Pomelo is one of the important fruits in the agricultural industry and has high commercial value. However, pomelos are susceptible to disease. Detecting diseases in pomelos is crucial for maintaining the quality and quantity of production. However, disease symptoms in pomelos are often complex and difficult to accurately detect through human visual observation. Therefore, image processing is a solution for detecting diseases in pomelos. Convolutional Neural Network (CNN) is a type of artificial neural network architecture that is highly effective in analyzing and predicting diseases. In this study, a model is designed and built to detect and classify diseases in pomelos based on their skin. The study uses a dataset obtained from self-documentation using a digital camera, which includes images of Diplodia/Blondok, Cancer, Fruit Fly, and healthy pomelos. In the preprocessing stage, the dataset is divided into training, validation, and testing data. Feature extraction is also performed using thresholding, contour detection, and bounding boxes. During the model processing stage, a model is created using training data, validation data, hyperparameters, and transfer learning. The results of the study show that the DensNet121 model achieved an accuracy of 92%.
Prototype Implementation of Exhaust Fan Control Using Mamdani Fuzzy Logic to Minimize LPG Concentration Hanafi, Mohamad Rizal; Adjhi, Dhimaz Purnama; Adiwilaga, Anugrah
JAICT Vol. 9 No. 1 (2024)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v9i1.5300

Abstract

This research aims to design and build a prototype of LPG gas leak detection system using fuzzy logic Mamdani method based on ESP32 with MQ-2 and DHT11 sensors as input and exhaust fan as output or action taken to prevent gas concentration. This research methodology includes literature study, identification and analysis, data collection, design implementation, software and hardware testing, and experiments to verify system performance. The results show that the system can detect LPG leaks and then provide preventive action by adjusting the speed and turning on the exhaust fan. This research is a prototype LPG gas leak detection system using fuzzy logic can be a solution to prevent hazards due to leaking gas. The contribution of this research is to provide alternative data processing methods that can improve the performance of gas sensors and provide responses that are in accordance with environmental conditions.

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