Amid the current Covid-19 pandemic, all MSMEs (Micro, Small and Medium Enterprises) around the world, including our beloved country Indonesia, are experiencing a downturn and even bankruptcy, only creative and innovative MSMEs can survive and thrive amid the current pandemic. Geographic Information System can be defined as a unit or component unit consisting of geographic data, hardware, software and human resources that work together to enter, store, update, improve, manage, manipulate, integrate, analyze and display data in geographic-based information. The current Covid-19 pandemic affects the contribution of MSMEs to the national economy. Based on the existing problems and previous research, a web-based geographic information system can be designed for mapping micro, small and medium enterprises. The result of this research is a web-based geographic information system for mapping micro, small and medium enterprises in Bengkalis Regency which consists of three actors, namely users, MSMEs owners and admins. The resulting Web-Based Mapping can search MSMEs based on business names and addresses, able to perform crud data, able to add location coordinates by shifting pins on the map, verify accounts via email and the web is responsive.

Construction projects are defined as development projects that have a significant impact on the basic infrastructure due to the money, time and human effort they invest. It is also defined as a set of sequential, overlapping and simultaneous activities carried out by a large number of individuals, equipment and materials during a specified period of time in which the contractor develops a plan. Where the research aims to study the real reasons that disrupt construction projects at the local level and the resulting waste of economic resources and social consequences affecting many parties. It is also important to assess the feasibility of public spending in two strategic sectors, especially since the housing and public equipment sectors. The current study has examined the common effects of delays in construction projects in IRAQ. Five effects of delays in construction projects have been explored to effectively achieve the aim of the study. They include: times overrun, cost overrun, dispute/disagreement between parties, complete abandonment and legal action/law suit.

The success of Natural Language Processing tasks generally depends on data representation. Representational learning incorporated in predictive models is the trend of deep learning models. Learning sentence representation with full semantics of document is a challenge in natural language processing problems. Because if the semantic representation vector of the sentence is good, it will increase the performance of finding similar question problems. In this paper, we propose to implement a series of LSTM models with different ways of extracting sentence representations and apply them to question retrieval for the purpose of exploiting hidden semantics of sentences. These methods give sentence representation from hidden layers of the LSTM model. The techniques consist using the last hidden layer of LSTM, Max pooling and Mean pooling. The results show that the technique using a combination of both Maxpooling and Meanpooling gives the highest results on the 2017 semeval dataset for the problem of finding similarity questions.

The study compared Harmonic, Geometric and Arithmetic means using sum of square error criterion. The study proposed Minimum Error Estimation Principle Criterion (MEEPC). The criterion states that the mean having the minimum error among all the errors or having the least deviation among all the deviations is the best estimate of the mean of the data. It was observed that Harmonic mean proves to be the best, this result further affirms that, actually, Harmonic Mean is best when applied for constant distance and varying speed and time, followed by the Geometric Mean.