Ekstraksi Fitur Tekstur dan Warna pada Kulit Katak Menggunakan GLCM dan Momen Warna

Anura is an order in the Amphibian class consisting of frogs and toads. Anura is very important in the ecosystem, especially its role as part of the food chain. Anura's main role is to maintain the balance of the ecosystem and as a bioindicator agent for changing environmental conditions such as water pollution, habitat destruction, disease and parasites, and climate change. This research applies digital image processing technology which is expected to assist in detecting types of frogs based on color and texture. This research uses 5 types of frogs, namely kongkang gading, kongkang poison, striped trees, small trees and flying trees with 20 images of each type of frog. This research uses the color feature extraction methods such Color Moment and texture extraction GLCM (Gray Level Co-occurance Matrix), then classified using K-Star. The results of the K-Star performance evaluation to classify the 5 types of frogs obtained the Accuracy (Acc) value of 0.93, Precision (Prec) of 0.94, Recall (Rec) of 0.93 and F-measure of 0.93. So that the classification results of frog species on texture and color feature extraction using the GLCM method and the Color Moment with the K-Star classification method have high performance and can work well.

Job Satisfaction of Hospitality Managers of the Department of Tourism Accredited Hotels in Baguio City Philippines

Job satisfaction among managers in the hospitality industry has a direct correlation to the ability of the hotels to increase guest satisfaction and improve services. This study aimed to determine the level of job satisfaction of hospitality managers among accredited hotels according to the star classification, their level of management, assigned departments and personal factors. By determining the level of satisfaction of managers according to the identified factors, management and owners of hospitality businesses would be able to focus on sustaining the perceived essential factors and will increase the manager's level of performance. A descriptive survey was used to gather the result of the study involving 91 managers of 4-Star and 3-Star hotels. The findings showed that the managers of the Department of Tourism accredited hotels in Baguio City are very satisfied with their jobs. Managers of 3-Star hotels are very satisfied while those who are in 4-Star hotels are satisfied. Middle managers are satisfied with their jobs, while the top and lower-level managers are very satisfied with their jobs. Managers in the front offices have a higher level of satisfaction than the support departments. The varying levels of job satisfaction among managers are dictated by several factors other than the job. In the personal factors, Millennial managers are satisfied while the Baby Boomers and Generation X are very satisfied. In ranking the most dominant factor that affects the level of satisfaction of hospitality managers, salaries and wages, promotion chances, and company policies emerged as the top three factors.

Application of the Servqual method to analyze the satisfaction level of hotel services and facilities

With so many hotels and other accommodation facilities in the city of Medan. More and more people are coming and staying and using the facilities at each hotel. Whether it's rooms, meeting room facilities, facilities to hold events, and much more are available in every hotel. Every hotel wants to give satisfaction to guests who come to use the hotel facilities and services. Likewise with SwissbeliNN hotels which have a 3 (three) star classification. Therefore, the opinions of guests and complaints given are very useful to improve the quality of hotel services. To find out, we will look at the satisfaction level of each guest. In this case, the writer applies the servqual method to see the level of guest satisfaction that has been obtained. To find out what is still lacking in the services provided. The purpose of this research is to find out the shortcomings of the hotel for the services provided to hotel visitors, as well as to fulfill the complaints of each visitor to the hotel from the results of the research carried out, with the objectives described later to be able to provide solutions to hotel leaders to fulfill the research results. obtained. The research methods carried out include collecting data directly from the hotel related to the problems that arise to be researched, literature studies, analyzing the problems to be studied based on the data collection that has been obtained, designing applications to overcome problems that arise and making it easier to find out the level of satisfaction of visitors. against managed hotels, as well as testing applications that are made to test the level of success obtained from the application being built. Based on the research conducted, the average perceived service quality score was 3.54. This score is in the somewhat unsatisfactory category when compared with the average score of service quality score which is perceived to be lower than expected. This indicates a gap. The highest average score is given to responsiveness with a value of 3.62 while the lowest score is given to the dimension of empathy with a value of 3.44.

Measure by Measure, they touched the heaven

The measure of distances is a recurring theme in astrophysics. The interpretation of the light coming from a luminous object in the sky can be very different depending on the distance of the object. Two stars or galaxies may each have a different real brightness, although they may look similar. The correct measures were determined by women computers a century ago. Special mention is due to Williamina Fleming, who supervised an observatory for 30 years and worked on the first system to classify stars by spectrum. Antonia Maury helped locate the first double star and developed a new star classification system. Henrietta Leavitt determined a law to calculate stellar distances. The most famous of the Harvard computers was Annie Jump Cannon. An expert in photography, she catalogued over 350,000 stars and expanded the classification system used today, but it was Henrietta Leavitt who left an indelible mark by discovering a law for the determination of stellar distances. In the same period, Italian women computers began to collaborate in observatories, but their tracks are obfuscated.

Imbalance learning for variable star classification

ABSTRACT The accurate automated classification of variable stars into their respective subtypes is difficult. Machine learning–based solutions often fall foul of the imbalanced learning problem, which causes poor generalization performance in practice, especially on rare variable star subtypes. In previous work, we attempted to overcome such deficiencies via the development of a hierarchical machine learning classifier. This ‘algorithm-level’ approach to tackling imbalance yielded promising results on Catalina Real-Time Survey (CRTS) data, outperforming the binary and multiclass classification schemes previously applied in this area. In this work, we attempt to further improve hierarchical classification performance by applying ‘data-level’ approaches to directly augment the training data so that they better describe underrepresented classes. We apply and report results for three data augmentation methods in particular: Randomly Augmented Sampled Light curves from magnitude Error (RASLE), augmenting light curves with Gaussian Process modelling (GpFit) and the Synthetic Minority Oversampling Technique (SMOTE). When combining the ‘algorithm-level’ (i.e. the hierarchical scheme) together with the ‘data-level’ approach, we further improve variable star classification accuracy by 1–4 per cent. We found that a higher classification rate is obtained when using GpFit in the hierarchical model. Further improvement of the metric scores requires a better standard set of correctly identified variable stars, and perhaps enhanced features are needed.