Jurnal Jaringan Telekomunikasi (JJT)
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285 research outputs found
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Development of a Battery Maintenance and Charging System with a LoRa-based Ethernet Network (Study Case PT. KAI DAOP 8 Surabaya, Gubeng Station)
No full textGubeng Station under PT. KAI DAOP 8 Surabaya requires a backup power source, such as a backup battery as a replacement for the main battery, to ensure continuous operation of the station. So, regular maintenance is carried out for the backup battery by charging them. However, there is no monitoring system for battery charging because the internet access at a distance of ±37.92 meters via Ethernet and voltage data after charging has turned yellow making maintenance and monitoring of charging difficult. Therefore, this research aims to develop a battery charging monitoring system with a LoRa-based ethernet network. When testing this system by charging a 12 VDC 65 Ah battery, the system can monitor the voltage and charging current values using a voltage sensor and ACS712 recorded in real-time in the Android application with an ethernet-based LoRa module with a maximum distance between the sending and receiving devices of 97, 9 meters in non-LoS conditions. The system also succeeded in auto cut off and sent a notification in the application when charging was complete with a recorded voltage and current of 14.01 V -0.22 Amperes
Implementation of Wireless Sensor Network on Smart Trash Bins Using LoRa With AES128 Algorithm (Case Study: Mentari Waste Bank Panceng Gresik)
No full textWaste bank systems such as Bank Sampah Mentari (BSM), located in Prupuh, Panceng, Gresik Regency, were created as a method of reducing waste. In its operation, the BSM management still has several difficulties such as the need to check the resident’s shelters, to administrative problems that are still done manually. Based on these problems, the implementation of a wireless sensor network on a smart trash bin using LoRa with the AES128 algorithm was made. The way it works is that the node device sends sensor reading data to the gateway every hour. The gateway will describe the incoming data, then upload it to MySQL and firebase before being accessed in the application. The test shows that the system can run well according to the plan where the farthest distance of LoRa is 300 meters. The average RSSI generated by node 1 is -95.78 dBm, node 2 is -112.57 dBm, and node 3 is -117 dBm. HC-SR04 ultrasonic sensor testing has an error of 0.795% (accuracy of 99.205%), while the MAX17048 sensor has an error of 0.3% with accuracy of 99.7%
Design of Miniature Snack Vending Machine Based on Internet of Things
No full textAutomatic sales machines or vending machines that already exist in Indonesia generally only sell snacks and soft drinks. The lack of vending machines in hotels is due to the high cost of purchasing a vending machine. The average shopping center, hotel, office, and other places in Indonesia still use vending machines with paper money and coin payments. The use of RFID tag cards as a means of payment on snack vending machines is still vulnerable if not given a password or the like for security. The testing parameters in this study are fingerprint sensor accuracy, RFID Reader Visiting, Database connectivity testing on the website, ESP32 testing to the database, and testing the entire system. Fingerprint sensor accuracy testing is done by taking 10 fingerprint samples that have not been registered. The fingerprint sensor works well. RFID testing is done by measuring the maximum distance the RFID Reader can read RFID tags using 3D print barrier with a thickness of 1cm. RFID Reader can read RFID Tags with a maximum distance of 3cm. Database connectivity testing on the website is done to find out whether communication between the database and the web vending machine snack goes well. The results of testing esp32 to the database took 2 tests, namely buyer id testing and balance testing. In the esp32 test to the database the system runs well and correctly. Overall the miniature snack vending machine system runs correctly as designed
Design of Smart Door Lock System Based on VLC and Fire Monitoring in Space (Case Study: Chemical Laboratory of SMAN 1 Pacet)
No full textThe school chemistry laboratory is a public facility for all members. So, good room security system is needed, considering the room stores hazardous chemicals are flammable. Therefore, a solution is offered to development door security system and fire monitoring in space. The purpose of this research to create and design VLC (Visible Light Communication) based door security system and to design a fire monitoring system in space. ESP32 is used as a microcontroller, temperature sensor (DS18B20), MQ-2, photodiode module, and IR Flame Infrared. The result of this research is that the maximum distance for sending passwords that can be received by the receiver is 30cm, lux <123, tilt angle 165°-180°. IR Flame Infrared can detect fire <11cm away, lux < 200. DS18B20 has sensor reading accuracy 99.97%, MQ-2 detects gas more than 300ppm. The IR Flame Infrared sensor reads the wavelength value according to the light source, namely Infrared Spectrometer. Dot have error tolerance 7ms, while dashes are 7.6ms. Overall, the system can run well. The door can be opened in two ways, using smartphone flash from outside and button from inside the room. In addition, the system can also detect fire at temperatures >50°C, wavelength <1100nm, and gases >300pp
Weather Anomaly Early Warning System on Koi Fishpond’s Water Quality Using Telegram Bot
No full textKoi fish farming is a popular practice in Blitar Regency. Larger ponds are required for cultivating Koi fish seeds, and it is common to use areas such as rice fields for these ponds. However, monitoring water quality in Koi ponds can be challenging, especially during unpredictable weather conditions. To address these difficulties, a study was conducted to develop an early warning system using the ESP32 DEVKIT V1 Module. The system provides real-time monitoring of Koi Pond water quality data through the Telegram app, using sensors to measure temperature, pH, and TDS levels. The data is then transmitted to the Telegram app for display. If the parameters differ from the standard values, the system triggers audio alerts, notifications, and a red LED indicator in the app. The test results show that the system performs well, with maximum recorded values of 31°C for temperature, 306 ppm for TDS, and a pH level of 9.4. The calibration errors for the system are measured at 0.37% for temperature, 0.77% for TDS, and 1.03% for pH. Overall, the system is effective in detecting poor water quality, offering automated alerts and manual control through the Telegram bo
New Employee Admission Decision Support System at Bangraden Foods using The Web-based Fuzzy Tsukamoto Method
No full textCurrently, Bangraden Foods is having problems picking new employees by offering numerous criteria to identify the applicant's abilities and personality, the results are typically recorded and must be compared to make judgments, which takes a long time for the company. In this case, the researcher used the Tsukamoto fuzzy method to develop a decision support system because it is simple, flexible, data-tolerant, faster, and better suited for input from humans rather than robots. Based on black box testing, the web system performance results run 100% smoothly for all existing functions. Testing data on 5 new employee candidates obtained a system value difference of 0.001-0.02 with 100% data accuracy, and the system recognized the graduation of two prospective workers with a decision of 'pass' since it reached an average score of 75, according to HRD, and three candidates 'did not qualify' due to below-average grades. In addition to testing service quality, throughput of 16Kb/s is classed as 'bad', packet loss of 0.273594% as 'very good', and delay of 293ms as 'good'. As a result, Bangraden Foods management may use the system to make data processing quicker and provide advice for decisions on recruiting new personnel based on the company's needs
Smart Security System for Housing Using Website-Based MQTT
No full textThe housing security system is one of the aspects of implementing a security system in several house buildings which have several functions that work to secure assets in the building. Then in residential areas it is difficult to carry out intense security. This study designed a "Smart Security System in Housing Using Website-Based MQTT". This system is equipped with PIR sensors, LDR, ACS 712, and limit switches that are placed in each house. PIR sensors are used to detect human movement, limit switches are used to detect open doors, and LDR sensors are used to automate outside lights when homeowners activate outdoor mode. The ACS 712 sensor functions to give a warning of an anomaly in current usage. Using ESP8266 as a controller that sends data to the online MQTT broker "broker.mqtt-dashboard.com" which is equipped with the cloud. Home owners website programming using Node-RED installed on Raspi. Likewise with the security guard website using Node-RED as a website design. In monitoring at the security guard, you can monitor the security of the doors in each house. The results of the accuracy of the PIR sensor are only able to detect movement at a distance of less than 400 cm. The LDR sensor used in outdoor lighting automation with a voltage limit value above 2.56 V detects no light intensity. The accuracy of the ACS 712 current sensor in house 1 is 95% and house 2 is 94%
Painting Security System using TensorFlow Based Object Detection Method
No full textPainting is an art form that should be preserved. Raden Saleh, Affandi, Hendra Gunawan, and Nyoman Gunarsa's paintings are among those of outstanding artistic worth. The existence of paintings may be jeopardized if the painting protection system is poor. Several well-known examples of art theft include the theft of Affandi's paintings in 1973 and Raden Saleh's paintings in 2007. Apart from famous paintings, personal paintings, which are equally expensive, are frequently stolen. This, of course, concerns the general public, particularly private art collectors with minimal security. Based on these problems, specific management is needed through the "SI LUKAS" Painting Security System. Using the TensorFlow-Based Object Detection Method, a system innovation that can continuously monitor the whereabouts of artworks and send notifications via Telegram, can be accessed from anywhere and at any time using TensorFlow. Based on evaluating the system's delay in reading items at a distance, it is discovered that the system can detect all objects, specifically hands and paintings, within a distance of 50cm to 550cm, however the latency varies. The average accuracy of object detection from various angles was found to be 89.6% for hand objects and 96.4% for painting objects, placing them in the very high category. In other words, the SI LUKAS system is implementable
Elephas-SAM : segmentation performance of Sumatran Elephant in captivity with segment anything model
No full textSurabaya Zoo is one of the conservation institutions in Surabaya, which has Sumatran elephants as a collection of endemic Indonesian animals. The Indonesian government protects this animal because of its endangered status. Having CCTV cameras installed in captivity helped us to create Elephas-SAM by utilizing Segment Anything Model (SAM) technology as the initial foundation for developing a system for monitoring animals in captivity with artificial intelligence (AI). Our investigations differ from past research in that we utilize 60 exclusive images obtained from CCTV footage in an elephant enclosure at Surabaya Zoo over a 30-day period instead of using publicly available datasets. The image set was partitioned into 30 instances taken under low-light settings (01:00 WIB) and 30 instances taken under high-light conditions (15:00 WIB). We perform the evaluation of SAM's prediction scores using the SAM-Point Prompt and SAM-Box Prompt techniques. It was found that, on average, the segmentation prediction scores for 30 low-light images are higher when the SAM-Point prompt is used (0.941) instead of the SAM-Box prompt (0.939), which is only a 0.002 difference. For a set of 30 vivid images, the SAM-Point Prompt produces a higher average score (0.989) than the SAM-Box Prompt (0.968), indicating a difference of 0.021. The results emphasize the effectiveness of using a SAM-Point prompt instead of a SAM-Box question to accurately forecast segmentation scores for items of Sumatran elephants under different illumination situations
Design Build an Automatic Granulated Sugar Vending Tool Microcontroller Based
No full textTrader and distributor of 50 kg of cane sugar from Kebonagung in the District Batu Kota Batu will be packed again, then it will be re-sell to trader small or consumer direct in accordance with request order. Every order of sugar will be made per pack, namely 1 kg, 2 kg and 3 kg and the amount are according to request and there are also those who place orders online via WhatsApp. Sugar distributors are currently still using manual scales to pack the sugar and must measure the sugar to produce a scale according to the weight of the sugar. This study designed an automatic tool to overcome this problem by designing a Microcontroller-Based Automatic Sugar Vending Tool with a sugar capacity of 10kg and a load cell of 5 kg and a sugar ordering application . The resulting tools and applications are can produce tools selling granulated sugar automatically based on purchase weight, a minimum purchase of 500 grams while a maximum of 3 kg, based on a nominal amount of money (rupiah) a minimum purchase of IDR 7,000 while a maximum of IDR 42,000 and after weighing the sugar can be packaged directly using a sealer and the application can be used to place sugar orders between sellers and customers with orders of 1, 2, 3 kg, the quantity ordered, find out sugar orders and delivery costs. The success rate of measurement on the load cell is 10 times with a weight the percentage of success is 99.00%