Tanda tangan adalah salah satu biometrik yang banyak digunakan untuk autentikasi dan verifikasi dokumen penting. Keberadaan tanda tangan sebagai bentuk pengesahan dan persetujuan dalam dokumen-dokumen penting adalah hal yang wajib. Seiring perkembangan teknologi saat ini, proses penandatanganan dapat dilakukan dalam media digital seperti handphone maupun media lainnya. Kemampuan sistem untuk mengidentifikasi tanda tangan seseorang menjadi penting karena banyak pemalsuan yang terjadi. Penelitian ini bertujuan untuk mengimplementasikan metode deteksi tepi Laplacian dan jarak Euclidean untuk mengidentifikasi tanda tangan seseorang. Total citra yang digunakan yaitu 20 tanda tangan dari 10 orang yang berbeda dimana 15 tanda tangan sebagai data citra latih dan 5 tanda tangan sebagai data citra uji. Hasil penelitian ini menunjukkan bahwa metode deteksi tepi Laplacian dan jarak Euclidean memiliki akurasi sebesar 94% dengan 1 ketetanggaan, dengan 2 ketetanggaan memiliki akurasi sebesar 60%, dan memiliki akurasi sebesar 74% dengan 3 ketetanggaan.
Fever is one of the symptoms of a person with Covid-19. Body temperature must be checked e before entering crowded areas such as schools, offices, shops, and hospitals. It is a mandatory protocol that must be done. One of the tools that can be used to check body temperature is a thermal camera. Thermal cameras have the disadvantage of a high temperature reading error. This is because the thermal camera used has a low resolution. This study aims to reduce the value of the temperature reading error on the thermal camera using the linear regression method. The linear regression method is able to reduce the error rate of temperature readings by 5.27% at 36 ° C reading. The reduction in reading error also occurred by 5.27% at 37 ° C and 6.44% at 38 ° C. Based on the results obtained, this study shows that linear regression can be applied to thermal cameras and provides a decrease in the error rate of temperature readings on thermal cameras
Thermogun is non-contact thermometer to examine people whom body temperature above 37°C that is used to screening human body temperature while entering public areas such as schools, offices, and supermarkets. Thermo gun is widely used yet not effective because it measuring single point around body or face which cannot represent whole body. Thus, the development of thermal camera is important. This research focusing on development of low-cost and low-resolution thermal camera to replace thermo gun. Thermal camera measure 36°C, 37°C, 38°C object temperature and gives accuracy respectively 99.38%, 99.39% 99.41%. Therma camera not only give high accuracy but also high precision. The precision for same temperature respectively 35.01 ± 0.63 when measure 36°C object temperature, 36.55 ± 0.26 when measure 37°C object temperature, and 37.27 ± 0.49 when measure 38°C object temperature. This result is satisfied and good enough to examine human body temperature.
The dangers of bacteria can cause health problems or infections of the respiratory tract. This research is related to the design of an anti-bacterial smart room sterilization system based on the Internet of Things (IoT) using a Passive Infrared Receiver (PIR). This study aims to sterilize with a monitoring and security system with PIR sensors and Blynk platform. Tool testing is carried out by taking 7 data from 1 object with 3 scanario which are sterilization without an object, sterilization by detecting objects, sterilization by detecting objects which is back to the room. In this system each condition is monitored on the Blynk platform. The advantage of this system is managed and monitored safety sterilization process remotely by Blynk. This tool has also gone through measurement quality assurance testing by adopting ISO 17025 including sensitivity, selectivity, precision, working range , tool toughness, and measurement uncertainty. The quality of service (QoS) test in this system gets an average delay of 122 milliseconds, throughput of 1045 bit/s and packet loss of 0.06%. This sterilizer can be monitored and operated remotely and is equipped with a security system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.