<p>Online learning has become a model, learning strategies, and the preferred channel in education around the world because it is not restricted by time and place. The development of online learning in supporting the success of health education programs for early detection of cervical cancer is the right solution to improve health workers knowledge. To measure user acceptance of the online learning applications, the study used Technology Acceptance Model (TAM) approach. Data collected from questionnaires then analyzed by calculating the frequency (proportion) of the total value, the interpretation of a score by looking for index% and interval. The final result of the calculation shows that all respondents agreed and strongly agreed with all four factors measured. The conclusions are the users believe that the use of learning online applications can reduce the task effort, improve job performance, give positive idea to use the technology, and consciously and expressed desire to run the online learning process in the future.<strong></strong></p>

Abstract-Information and communication technology continues to grow and affects many areas of life, including the field of health, especially cancer. The development of health knowledge can be disseminated by utilizing mobile application based learning technology as media. Many things have been done by the government through special programs, among others, carried out breast cancer awareness campaign through breast self-screening program. The positive impact of this effort has led to mobile applications for learning about early detection of cancer in Indonesia. The development of mobile learning is a continuation of previous online learning to help the process of early detection of cervical cancer. Data collection methods used observation, interview, and questionnaire techniques, while instructional designs use the ADDIE (Analysis Design Development Implementation Evaluations) model and methods for developing object-oriented programming systems using Unified Modeling Language (UML). The resulting output is the application of early detection of cancer-based mobile learning which is the virtue of this study.

In building management, energy optimization is one of the main concern that needs to be automated. For automation, an intelligent system needs to be developed. However, an intelligent system needs to be trained in a large dataset before it can be used reliably. In this paper, we present a transfer learning scheme to develop an intelligent system for smart building management system. Specifically, the intelligent system is able to count human inside a room, which can be utilized to adaptively adjust energy usage in a room. The transfer learning scheme employs a deep learning model that is pretrained on ImageNet dataset. To enable the human counting capability, the model is trained on a dataset specifically collected for human counting case.

This research wanted to show the development of e-commerce transaction brought something new to organizations to accelerate their business through online sales. The presence of online marketplace also gave positive impacts for organizations to run online sales. It was undeniable that e-commerce positively contributes to people’s lives, besides the negative side that most people are still reluctant to use it. Online-to-offline (O2O) was a strategy to direct online users to do offline activities in physical stores. With O2O, customers could buy products from the store after researching online, paying online, and picking up product from the store. The research aimed to find out more about factors that influence consumer trust level to do a transaction in online media, as well as to measure the effectiveness of O2O strategy on e-commerce. Furthermore, this research used a quantitative correlation data analysis method on critical factors that influence customer decision in doing ecommerce transaction, with non-experimental research. The research outcome is the overview of the effectiveness feature and O2O strategy that is provided by the online shopping provider in giving a positive influence for consumers to make purchases in e-commerce. This research also reflects how the people respond to the existence of a marketplace that complements its place with O2O service.

Audit delay is the lag in completing an audit report by the auditor. Audit delay causes financial statements to be inhibited for publication. This causes the users of financial statements to wait longer to be able to use financial statements as a tool in decision making. The purpose of this research is to empirically examine the effect of company size, liquidity, profitability, solvability, and audit firm size towards audit delay on property and real estate companies that listed on Indonesia Stock Exchange (IDX) in 2014-2018. This research is a quantitative study that tests the hypothesis, whether there is the influence of independent variables on the dependent variable. This study uses the ordinary least square method Statistical test used is the coefficient of determination test, partial t test and simultaneous f test. The selection of research samples using purposive sampling method. The sample of this research consists of 46 companies with 5 years of research so total of the research objects amounting 230 data. The data analysis method used in this research is panel data regression analysis using E-views version 10. Based on the results of partial test, profitability and audit firm size have significant effect on audit delay. Company size, liquidity, and solvency do not have a significant effect on audit delay. Simultaneous test result showed that company size, liquidity, profitability, solvability, and audit firm size simultaneously affect audit delay. The results of this study indicate that if the auditor wants to minimize audit delay, they must pay more attention to clients' profitability and consider the size of the company, the size of the audit's scope of work