The Impact of Color Space and Intensity Normalization to Face Detection Performance

In this study, human face detection have been widely conducted and it is still interesting to be research. In this research, strong impact of color space for face i.e., many and multi faces detection by using YIQ, YCbCr, HSV, HSL, CIELAB, and CIELUV are proposed. In this experiment, intensity normality method in one of the color space channel and tested the faces using Android based have been developed. The faces multi image datasets came from social media, mobile phone and digital camera. In this experiment, the color space YCbCr percentage value with the image initial value detection before processing are 67.15%, 75.00%, and 64.58% have been reached. Then, after the normalization process are 83.21%, 87.12%, and 80.21% have been increased. Furthermore, this study showed that color space of YCbCr have reached improvement percentag

Face Images Classification using VGG-CNN

Image classification is a fundamental problem in computer vision. In facial recognition, image classification can speed up the training process and also significantly improve accuracy. The use of deep learning methods in facial recognition has been commonly used. One of them is the Convolutional Neural Network (CNN) method which has high accuracy. Furthermore, this study aims to combine CNN for facial recognition and VGG for the classification process. The process begins by input the face image. Then, the preprocessor feature extractor method is used for transfer learning. This study uses a VGG-face model as an optimization model of transfer learning with a pre-trained model architecture. Specifically, the features extracted from an image can be numeric vectors. The model will use this vector to describe specific features in an image.  The face image is divided into two, 17% of data test and 83% of data train. The result shows that the value of accuracy validation (val_accuracy), loss, and loss validation (val_loss) are excellent. However, the best training results are images produced from digital cameras with modified classifications. Val_accuracy's result of val_accuracy is very high (99.84%), not too far from the accuracy value (94.69%). Those slight differences indicate an excellent model, since if the difference is too much will causes underfit. Other than that, if the accuracy value is higher than the accuracy validation value, then it will cause an overfit. Likewise, in the loss and val_loss, the two values are val_loss (0.69%) and loss value (10.41%)

Social Media Mining with Fuzzy Text Matching: A Knowledge Extraction on Tourism After COVID-19 Pandemic

Social media mining is an emerging technique for analyzing data to extract valuable knowledge related to various domains. However, traditional text matching techniques, such as exact matching, are not always suitable for social media data, which can contain spelling mistakes, abbreviations, and variations in the use of words. Fuzzy matching is a text matching technique that can handle such variations and identify similarities between two texts, even if there are differences in spelling or phrasing. The gap in existing research is the limited use of fuzzy matching in social media mining for tourism recovery analysis. By applying fuzzy matching to social media data related to COVID-19 and tourism recovery, this research seeks to bridge this gap and extract valuable insights related to the impact of the pandemic on tourism recovery. We manually retrieved 19,462 Twitter records and differentiated the data sources using four diver parameters to indicate data related to the impact of COVID-19 on the tourism industry, such as the economy, restrictions, government policies, and vaccination. We conducted text mining analysis on the collected 7,352 words and identified 25 highly recommended words that indicated COVID-19 recovery from a tourism perspective. We separated the four words representing the tourism perspective to perform fuzzy matching as a dataset. We then used the inbound dataset on the fuzzy matching process, with the 7,352-word data collected from the text mining process. The matching process resulted in 18 words representing COVID-19 recovery from a tourism perspective

PENGEMBANGAN JARINGAN INTERNET WIRELESS DENGAN WIFI OVERVIEW PADA OBYEK WISATA BLANGSINGA WATERFALL

Blangsinga Waterfall is one tourist attraction with very extreme geographical conditions, where the area has not covered GSM signals as a result tourists can not access the Internet network. The purpose of this research is to determine the spot of Wireless and Hotspot network infrastructure and then to measure signal strength for tourism area coverage. Based on field analysis determined 3 (three) points for network construction and placement of Access Point as Hotspot. Implementation begins with building a LAN network. Then for scanning channel and signal access point testing used Wifi Overview tool. Signal strength testing is performed around the area of ​​the resort by taking a distance of 5m, 10m, and 15m in all directions from the Access point is placed. The result is the establishment of internetworking for Blangsinga Waterfall tourism area. The next result is the internet access where all the tourist areas are covered wifi signal. With the development of internet infrastructure, tourists get easier communication access and management of tourist attractions can develop other facilities based on internet network that has been built.Blangsinga Waterfall merupakan salah satu objek wisata dengan kondisi geografis yang sangat ekstrim, Dimana area tersebut belum tercover sinyal GSM akibatnya wisatawan tidak bisa mengakses jaringan internet. Tujuan penelitian ini adalah menentukan spot infrastruktur jaringan Wireless serta Hotspot dan kemudian melakukan pengukuran kekuatan sinyal untuk coverage areal wisata. Berdasarkan analisa lapangan ditentukan 3 (tiga) titik untuk pembangunan jaringan dan penempatan Access Point sebagai Hotspot. Implementasi diawali dengan membangun jaringan LAN. Kemudian untuk scanning channel dan pengujian sinyal access point digunakan tools Wifi Overview. Pengujian kekuatan sinyal dilakukan di sekitar areal tempat wisata dengan mengambil jarak 5m, 10m, dan 15m  ke segala arah dari Access point ditempatkan. Hasil yang dicapai adalah terbangunnya internetworking untuk areal wisata Blangsinga Waterfall. Hasil berikutnya adalah adanya akses internet dimana semua areal wisata ter-cover sinyal wifi. Dengan terbangunnya infrastruktur internet, wisatawan mendapatkan akses komunikasi lebih mudah serta pengelola tempat wisata dapat mengembangkan fasilitas lain dengan berdasar jaringan internet yang sudah dibangun

Facemask detection using the YOLO-v5 algorithm: assessing dataset variation and resolutions

The Covid-19 pandemic has made it imperative to prioritize health standards in companies and public areas with a large number of people. Typically, officers oversee the usage of masks in public spaces; however, computer vision can be employed to facilitate this process. This study focuses on the detection of facemask usage utilizing the YOLO-v5 algorithm across various datasets and resolutions. Three datasets were employed: the face with mask dataset (M dataset), the synthetic dataset (S dataset), and the combined dataset (G dataset), with image resolutions of 320 pixels and 640 pixels, respectively. The objective of this study is to assess the accuracy of the YOLO-v5 algorithm in detecting whether an individual is wearing a mask or not. In addition, the algorithm was tested on a dataset comprising individuals wearing masks and a synthetic dataset. The training results indicate that higher resolutions lead to longer training times, but yield excellent prediction outcomes. The system test results demonstrate that face image detection using the YOLO-v5 method performs exceptionally well at a resolution of 640 pixels, achieving a detection rate of 99.2 percent for the G dataset, 98.5 percent for the S dataset, and 98.9 percent for the M dataset. These test results provide evidence that the YOLO-v5 algorithm is highly recommended for accurate detection of facemask usage

Visualisasi sistem 1nformasi jaringan distribusi listrik (Studi Kasus Kota Denpasar = A Visualisation of Information System for ElectricityDistribution Network(Case Study of Denpasar City)

A Visualization of Information System for Electricity Distribution Network (Case Study of Denpasar City) is an SIG-based information system using spatial and non spatial data model. The system can be used inventory management for electricity distribution networks and customers. It can display information on electricity distribution network based on selected object. It is expected that this information system is able to help PLN (National Electricity Company) with planning, operational, and monitoring to period better quality and professional of services. Describing information using spatial forms (maps) and non spatial data (text) make it easy to understand since it represents facts and descriptions. Keywords : information system, electric distribution networ

Comparison of RNN, LSTM, and GRU Methods on Forecasting Website Visitors

Forecasting is the best way to find out the number of website visitors. However, many researchers cannot determine which method is best used to solve the problem of forecasting website visitors. Several methods have been used in forecasting research. One of the best today is using deep learning methods. This study discusses forecasting website visitors using deep learning in one family, namely the RNN, LSTM, and GRU methods. The comparison made by these three methods can be used to get the best results in the field of forecasting. This study used two types of data: First Time Visits and Unique Visits. The test was carried out with epoch parameters starting from 1 to 500 at layers 1, 3, and 5. The test used first-time visit data and unique visit data. Although tested with different data, the test results obtained that the smallest MSE value is the LSTM method. The value of each MSE is 0.0125 for first-time visit data and 0.0265 for unique visit data. The contribution of this research has succeeded in showing the best performance of the three recurrent network methods with different MSE values

TKJ and Graphic Design Training for Student Strengthening Facing UKK at SMK PGRI Amlapura

The Vocational High School of the Indonesian Teachers Association (SMK PGRI) Amlapura is a vocational school at the upper middle level that has four majors namely, hospitality, catering, computer network and multimedia engineering. Located in Amlapura City, Karangasem Regency, Bali Province. Based on the vocational education that is carried out, all students studying in vocational schools are required to take the expertise competency test (UKK) of each field that is in demand in accordance with the majors they choose. This UKK is carried out nationally and is a national practical test. This is what distinguishes an educational model that exists at the high school level. As for facing the National Practice Examination, schools generally provide assistance for their students.Bali State Polytechnic in this case implementing Tri Dharma Higher Education such as teaching, research and service. One of the Tri Dharma of the tertiary institution is the Commander of the Commander, where the community service aims to play a role and participate in building the welfare of the community. This service activity is carried out in accordance with existing academic culture.Bali State Polytechnic Department of Electrical Engineering Information Management Study Program is willing to accompany the students of SMK PGRI Amlapura in terms of preparing themselves to take part in UKK. This mentoring activity is a service activity. Assistance provided specifically to UKK Computer Network Engineering Program and UKK Multimedia Program. Activities in the form of exposure in theory and direct practice. The continuation of assistance is also done using WhatsApp Group media

Implementation of Asynchronous Microservices Architecture on Smart Village Application

This paper discusses the implementation of microservices architecture in smart village applications. The smart village application is a village-based online marketplace that facilitates various business actors' buying and selling process in a village. This application manages five types of products: lodging reservations, tourist attraction tickets, culinary purchases, and purchasing knick-knacks show tickets. The complexity of processes, data, and high potential users requires that the system architecture is designed to produce a scalable, fault-tolerant system and easy to develop. Microservices architecture is one of the recommended architectures for building a scalable, fault-tolerant, and maintainable application. This architecture has several variations, ranging from variations in communication between services to the technology used. The suitability of applications with architectural variations and the complexity is a challenge in implementing this architecture. This paper describes how to implement the microservices architecture in smart village applications. Design and implementation of the microservices architecture in the smart village application was followed the WSIM or Web Services Implementation Methodology stage. The implementation results show that the application is easier to manage because it is divided into independent microservices. Implementing asynchronous communication and a choreographic approach to each service makes the client application response faster; besides, it did not affect other services if there is a problematic service