Masked Face Images Based Gender Classification using Hybrid Bat Algorithm Optimized Bagging

The face is one of the biometrics utilized to learn information from a person, such as gender. Gender classification study is expanding daily as a result of how important it is and how many other sectors, like forensics, security, business, and others, employ it. However, in order to protect themselves and stop the spread of Covid-19 during this epidemic, everyone must wear a face mask. Because many crucial facial features that help determine a person's gender are obscured by masks, using one creates an issue for the gender classification system. To obtain optimal performance outcomes, suitable hyperparameters are also required. As a result, the objective of this study is to develop a gender categorization system based on mask-covered faces utilizing a novel technique that combines several features in the Gray Level Co-occurrence Matrix (GLCM), which is then fed into the Bagging classifier.A Hybrid Bat Algorithm (HBA) is used to optimize the bagging hyperparameters. With 97% accuracy, precision, recall, and f1-score values, the suggested model is demonstrated to have greater performance than before the hyperparameters were tuned using HBA. © 2023 IEEE.

Fishbone Diagram to Evaluate Causal Factors Affecting of Workload among MSMEs Employees during Covid-19 Pandemic

The existence of this workload is due to an imbalance between the capacity or ability of workers and the demands of the work that must be faced. As is the case with the conditions of workers in MSMEs, the demands of work are greater than the capacity of workers. Hence, the emergence of workload can not be avoided. Many studies on the workload of MSMEs have been carried out in Indonesia, however none of existing works has employes the Fishbone approach. This study evaluates the workload of three indicators, namely mental workload, physical workload, and Covid-19 pandemic. The novelty of this work is that, unlike the existing work that use different methods, we focus Fishbone method in our work. Furthermore, we used a large sample size of 341 respondents who are MSMEs employees in Malang, Indonesia, where the survey method was used for data collection. The results of the t-test analysis showed that the average mental workload score was not the same as the average physical workload score, the positive t-count results showed that the average physical workload score was higher than the mental workload. The results of the analysis with frequency describe that the response given to each indicator is mental workload in the underioad category, physical workload in the optimal category, and the Covid-19 in the overload category. The main factors causing the workload are the Covid-19 pandemic factor where respondents feel always bothered about the pandemic, the physical workload factor where respondents often feel tired, and the mental workload factor where respondents have personal problems that interfere with work. The workload for MSME workers is in line with previous predictions that the physical load is more dominant than the mental load. However, during this Covid-19 period, a higher workload is felt due to the impact of the government's restrictions on activities.

Indonesian Firms Information and Communication Technology Usage during Covid-19 Pandemic

Businesses relies on information technology to retrieve data and store data. The data is used for making business decisions at all levels of an organization. Due to the COVID-19 pandemic, the reliance on information technology has risen to help companies connect their employees and their supply chain partners. Since Indonesia emerging market is growing, there is a need to investigate the growing intention to adopt information and communication technology. The reason is that Indonesian companies' survivability relies on their competitiveness and sustainability in business during the COVID-19 pandemic. This study investigates intention to use information technology through user satisfaction, Confirmation, perceived ease of use, and perceived usefulness. Data were collected from 45 employees working in the industry. The findings show that there is a difference between before pandemic and during the pandemic. After benchmarking the result with the literature, perceived usefulness and satisfaction were not significant to adopting information technology. The reason is due to pandemic forced employees to embrace technology and change employees' work ethic. The result contributes to the literature extending the empirical evidence and providing future direction to investigate pre- and post-pandemic situations. Practically, companies should introduce information technology in phases so that it will not increase user dissatisfaction. © 2021 IEEE.

Sonia: An integrated indonesia online tourism system in new normal era

Indonesian travel and tourism have grown to become one of the largest economic sectors in the world. Tourists are the main source of income for gross domestic income in Indonesia. However, although Indonesia as a beautiful archipelago country has so much offer to foreign and local tourist, until now it fails to give their potential to the country. Furthermore, the COVID-19 situation made Indonesia tourism worse. Travelling is banned as a consequence of lockdown in Indonesia. Business and economic need to adjust into their new normal. Unfortunately, in the midst of the current era of Internet technology and new normal, Indonesia’s tourism promotion is considered to be uneven and unwell targeted. Many tourist destinations are very interesting and clean but not yet known by potential tourists both from domestic and abroad due to the lack of targeted promotions and re-branding of a safe place to visit. Seeing to this prob-lem, this study aims to propose an integrated tourism system called SONIA, by using a Service-Oriented Architecture (SOA) and an Artificial Intelligence (AI) model to build a personalized recommender system. Through this system integration model, a significant socio-economic benefit can be made for tourism sector in Indonesia. The results of the research will be exploited for the tourism industry and Indonesia’s participation in the global tourism competition market. © 2020, ICIC International. All rights reserved.