The Effects of the Communicative Approach and the Use of Information Technology on Students' Motivation and Achievement in Indonesian Language Learning

-This study aimed to explain the structural influence of the implementation of the communicative approach and the use of information technology in Indonesian language learning on students motivation and learning achievement. This research was conducted in Blitar, Indonesia, and 186 students were chosen as the samples. An explanatory research design was used in this research. The data collection techniques used questionnaires and documentation, while data analysis techniques used descriptive statistics and structural equation modeling. The results of the analysis showed that there was a direct effect of the communication approach and the use of information technology on students learning motivation. There was a significant direct effect of students learning motivation on students achievement in the Indonesian language class. The communicative approach had an indirect effect on students achievement and showed a stronger coefficient of the effect on learning motivation compared to the use of information technology. These findings were discussed in depth based on the theory and results of previous studies.

Google Classroom as an Online Learning Media for Indonesian Language Learning During COVID-19 Pandemic

—The COVID-19 pandemic forced schools to change their offline learning model to online. Teachers can use many platforms for online learning, such as Google Classroom. This study aims to reveal the use of google classroom in online learning of Indonesian subjects at schools during the pandemic. A literature study is used in this research. Data is collected from various sources, such as journal articles, proceedings, books, and online news. The results of the analysis show that in learning Indonesian during a pandemic, Google Classroom is used by teachers as an online learning medium because it is easy for students to access. Using Google Classroom effectively increases student understanding and can increase student activity in learning. © 2023 ACADEMY PUBLICATION.

NLP Analysis of COVID-19 Radiology Reports in Indonesian using IndoBERT

The presence of COVID-19, a respiratory disease, can be detected through medical imaging, such as Chest X-Ray (CXR) and Computed Tomography (CT) scans. These radiology images can also show how the patient's condition progresses. Radiologists need to provide a written report for each image, so that other clinicians can use it in their decision making. In this study, we applied one of the Natural Language Processing (NLP) models called IndoBERT to analyze radiology reports of COVID-19 patients written in Indonesian. We performed two tasks, clustering to group reports by meaning and understand their content, and text classification to predict one of the five possible outcomes for each patient. We show the most frequent topics in radiology reports, and word scores in each topic. The IndoBERT model was fine tuned on a medical text, 'Kamus Kedokteran Dorland' in an attempt to further improve it. This proved unnecessary: on one hand, there were no additional benefits, on the other, the standard model alone achieved a very satisfactory classification accuracy of over 90 %. © 2022 IEEE.

Extraction of Event Sentence Information in the Covid-19 Distribution Location Detection System based on the Indonesian Language Corpus

The procedure for obtaining data on people affected by the COVID-19 disease is carried out through a manual data collection mechanism through health centers, government and private hospitals, health clinics spread throughout Indonesia, and rapid tests carried out at certain times and locations. Such a surveillance system requires time, a lot of health personnel, and is expensive. In addition, the geographical condition of the Indonesian state, which consists of many large and small islands and the vast territory of Indonesia requires another strategy to find out and make it easier to complete data on people affected by COVID-19, such as the use of information technology. The use of the Twitter dataset to detect the spread of disease in a region or country has been widely carried out by researchers. Sentence extraction is a process that must be done to facilitate the analysis of a short or very long news sentence to get the meaning and essence of the news contained in the sentence. The primary information can be identified based on keywords generated using extraction and ion techniques. The initial stage of the research focused on building a corpus of twitter data and a corpus of vocabulary. The first process that will be carried out is to collect natural language datasets from Indonesian-language Tweets on Twitter. Next, carry out the process of extracting incident sentence information with steps, namely making standard sentence formats, simplifying sentences, identifying essensial words, and determining input and target words in sentences. © 2022 Institute of Advanced Engineering and Science (IAES).

Trends of Influenza’s Symptoms Drug Search Terms in Indonesian-Language using Google Trends in the Covid-19 Pandemic

Covid-19 has spread globally and causes severe acute respiratory syndrome. The symptoms of covid-19 have similarities with influenza, such as cough, fever, runny nose, and sore throat. Therefore, the internet sources tend to have an increasing search related to influenza symptoms drugs. This study aims to assess the search trend of influenza symptoms drugs using google trend analysis in Indonesia. We explore Google trend analysis using search terms in the Indonesian language related to influenza symptoms drugs from December 6th, 2020 to November 30th, 2021. The positive confirmed cases were obtained from the Indonesian government website https://covid19.go.id/. Our results demonstrated the increasing search terms related to influenza drug symptoms during July and August. The highest term search was “obat batuk”. The positive covid-19 confirmed cases in Indonesia increased during July and August. During the peak of the covid-19 outbreak in Indonesia in July-August 2021, there was an increase in Google Trends searching related to influenza’s drug symptoms.

Implementing the OH guide in Indonesia for Creating and Safe and Healthy Workplace

Introduction: The Covid-19 pandemic highlighted the ever increasing importance of Occupational Health and Safety issues at work. Lack of resources in the local language is a barrier to effect awareness and communication. Materials and Methods: The relevant permissions were sought and colleagues came together at Binawan University were able top come together in the translation of the Occupational Health and Safety Guide (Creating a Safe and Healthy Workplace. A Guide to Occupational Health and safety for Entrepreneurs, Owners, and Managers). guidance book into Bahasa Indonesia. Results: Representative of Ministry of Health of Indonesia, Ministry of Labor of Indonesia, National Social Security Agency, and Indonesian Union workers conveyed positive feedbacks on the book and the launching. Conclusion: This process has facilitated a unified learning tool for Indonesian managers, owners, and entrepreneurs to be exposed to OSH. It is hoped that this process can encourage this OH guide to be translated into other locally accessible languages.