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INDONESIA
Emerging Science Journal
Published by Ital Publication
ISSN : 26109182     EISSN : -     DOI : -
Core Subject : Social,
Environmental Science
Emerging Science Journal is not limited to a specific aspect of science and engineering but is instead devoted to a wide range of subfields in the engineering and sciences. While it encourages a broad spectrum of contribution in the engineering and sciences. Articles of interdisciplinary nature are particularly welcome.
Arjuna Subject : -
Articles 1,058 Documents
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Secondary Socialization of Homeschoolers during the Covid-19 Pandemic Š imek, Václav; Oláh, Albert; Bočková, KateŠ™ina
Emerging Science Journal Vol. 5 (2021): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SPER-12

Abstract

The presented article deals with the description of the socialization of basic school pupils, i.e. pupils in younger and middle school age, who fulfill the compulsory school attendance in the form of individual education (homeschooling) in the context of the legislation of the Czech Republic. In the context of fulfilling the article aim, we formulated three research questions, which were evaluated using quantitative research in the form of a questionnaire survey. The research confirmed that parents of homeschoolers significantly support their children in participating in organized leisure activities and are actively involved in mediating their child's contact with other children. In the comparison of the examined groups there were no significant differences in how the children perceive their friends, what their favorite activities are or how much time they spend with them. The difference was more noticeable in the parental approach in education, when setting some rules. This article can outline areas that can be further explored in more detail and compared in context. Doi: 10.28991/esj-2021-SPER-12 Full Text: PDF
Assessing the Impact of COVID-19 on Corporate Investment Behavior Farooq, Umar; Tabash, Mosab I.; Anagreh, Suhaib; Alnahhal, Mohammed
Emerging Science Journal Vol. 5 (2021): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SPER-11

Abstract

The current wave of COVID-19 outbreak has created new strategical challenges for policy officials of the industrial sector across the world. The effect of COVID-19 is more in developing economies where industrial sector is already struggling for its stability. This study introduces the impact of COVID-19 on the corporate investment behavior of non-financial publicly listed firms of Pakistan. To achieve the objective, we employ the panel data ranging from 2010 to 2020 and apply the difference-in-differences (DID) model to quantifies the empirical relationship. The outcomes of DID model suggest that the pandemic period and treatment have a significant and negative impact on corporate capital investment behavior. During pandemic spread period, the enterprises have limited their investment into fixed assets due to less productive use of such assets. Similarly, industries that exist in high-impact areas face a negative investment growth rate due to quarantine policy, fewer social movements, and high installing cost of new machinery. However, this negative effect diminishes across those firms that have a quick cash inflow rate and more availability of bank loans. These two factors serve as a financial setback against the adversities of pandemic. By drawing upon the empirical reasoning on the effect of COVID-19, this study also presents possible solutions to alienate unfavorable impacts of this pandemic. Current analysis can be considered as an early attempt towards investigating the consequences of COVID-19 on investment decisions of industrial sector.JEL Classification: G32: G31: G40: C33 Doi: 10.28991/esj-2021-SPER-11 Full Text: PDF
Real-Time Monitoring of COVID-19 SOP in Public Gathering Using Deep Learning Technique Khel, Muhammad Haris Kaka; Kadir, Kushsairy; Albattah, Waleed; Khan, Sheroz; Noor, MNMM; Nasir, Haidawati; Habib, Shabana; Islam, Muhammad; Khan, Akbar
Emerging Science Journal Vol. 5 (2021): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SPER-14

Abstract

Crowd management has attracted serious attention under the prevailing pandemic conditions of COVID-19, emphasizing that sick persons do not become a source of virus transmission. World Health Organization (WHO) guidelines include maintaining a safe distance and wearing a mask in gatherings as part of standard operating procedures (SOP), considered thus far the most effective preventive measures to protect against COVID-19. Several methods and strategies have been used to construct various face detection and social distance detection models. In this paper, a deep learning model is presented to detect people without masks and those not keeping a safe distance to contain the virus. It also counts individuals who violate the SOP. The proposed model employs the Single Shot Multi-box Detector as a feature extractor, followed by Spatial Pyramid Pooling (SPP) to integrate the extracted features to improve the model's detecting capabilities. The MobilenetV2 architecture as a framework for the classifier makes the model highly light, fast, and computationally efficient, allowing it to be employed in embedded devices to do real-time mask and social distance detection, which is the sole objective of this research. This paper's technique yields an accuracy score of 99% and reduces the loss to 0.04%. Doi: 10.28991/esj-2021-SPER-14 Full Text: PDF
IoT-based Lava Flood Early Warning System with Rainfall Intensity Monitoring and Disaster Communication Technology Suwarno, Iswanto; Ma'arif, Alfian; Maharani Raharja, Nia; Nurjanah, Adhianty; Ikhsan, Jazaul; Mutiarin, Dyah
Emerging Science Journal Vol. 4 (2020): Special Issue "IoT, IoV, and Blockchain" (2020-2021)
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SP1-011

Abstract

A lava flood disaster is a volcanic hazard that often occurs when heavy rains are happening at the top of a volcano. This flood carries volcanic material from upstream to downstream of the river, affecting populous areas located quite far from the volcano peak. Therefore, an advanced early warning system of cold lava floods is inarguably vital. This paper aims to present a reliable, remote, Early Warning System (EWS) specifically designed for lava flood detection, along with its disaster communication system. The proposed system consists of two main subsystems: lava flood detection and disaster communication systems. It utilizes a modified automatic rain gauge; a novel configured vibration sensor; Fuzzy Tree Decision algorithm; ESP microcontrollers that support IoT, and disaster communication tools (WhatsApp, SMS, radio communication). According to the experiment results, the prototype of rainfall detection using the tipping bucket rain gauge sensor can measure heavy and moderate rainfall intensities with 81.5% accuracy. Meanwhile, the prototype of earthquake vibration detection using a geophone sensor can remove noise from car vibrations with a Kalman filter and measure vibrations in high and medium intensity with an accuracy of 89.5%. Measurements from sensors are sent to the webserver. The disaster mitigation team uses data from the webserver to evacuate residents using the disaster communication method. The proposed system was successfully implemented in Mount Merapi, Indonesia, coordinated with the local Disaster Deduction Risk (DDR) forum. Doi: 10.28991/esj-2021-SP1-011 Full Text: PDF
RETRACTED: Conceptualizing Post-COVID-19 Malaysia's Tourism Recovery: An Auto-Regressive Neural Network Analysis Arokiasamy, Anantha Raj A.; Smith, Philip Michael Ross; Kijbumrung, Thanapat
Emerging Science Journal Vol. 5 (2021): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SPER-10

Abstract

This article has been retracted: please see Emerging Science Journal policies:(https://ijournalse.org/index.php/ESJ/about/editorialPolicies).Reason: The present article has been retracted at the request of the Research Ethics, Integrity, and Governance team at RMIT University, Australia. Following a research integrity investigation into multiple allegations against former staff member Dr. Alex Arokiasamy, it was found, on the balance of probabilities, that Dr. Arokiasamy breached the Australian Code and/or RMIT Policy by: 1) assigning authorship to individuals who did not make a significant intellectual or scholarly contribution, and 2) publishing a paper with a 40% similarity to other publications.
Preservation of the Muyu Indigenous Language with an Android-based Dictionary Tambaip, Beatus; Wayangkau, Izak Habel; Suwarjono, Suwarjono; Loupatty, Martha; Adam, Aenal Fuad; Hariyanto, Hariyanto
Emerging Science Journal Vol. 4 (2020): Special Issue "IoT, IoV, and Blockchain" (2020-2021)
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SP1-06

Abstract

Indonesia is a country rich in cultural diversity, with each culture having its own regional language characterizing the area. The Muyu language is one of the regional languages, used by the Muyu tribal community in Boven Digoel Regency, Papua Province. The language is now under the threat of abandonment by the Muyu community, especially the younger generation. One of the causes is the lack of written learning media for the language to be inherited by older speakers in the form of books and electronic dictionaries. This study will try to develop an Android-based Muyu-Indonesian-English dictionary application using the waterfall method (classic life cycle). The aim is to test students' preferences and attitudes towards the development of Muyu language knowledge. The research sample consisted of 40 respondents consisting of Muyu students at Musamus University. A questionnaire was used to measure the extent of student responses to the use of the Muyu-Indonesian-English dictionary application. The test results show that the system has no errors in carrying out the functions that have been created previously at the manufacturing stage. The three-language Muyu-Indonesian-English dictionary application is able to search for vocabulary properly and correctly in Muyu, Indonesian, and English. The attitude of students towards the usefulness of this dictionary application is measured at the medium category, meaning that the application is useful as a tool to facilitate students of the Muyu language, especially Android users, in finding vocabulary in three languages, and can be a tool for learning the Muyu language and preserving local wisdom so that it does not become extinct. Doi: 10.28991/esj-2021-SP1-06 Full Text: PDF
Utilization of IoT for Soil Moisture and Temperature Monitoring System for Onion Growth Wayangkau, Izak Habel; Mekiuw, Yosehi; Rachmat, Rachmat; Suwarjono, Suwarjono; Hariyanto, Hariyanto
Emerging Science Journal Vol. 4 (2020): Special Issue "IoT, IoV, and Blockchain" (2020-2021)
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SP1-07

Abstract

The use of IoT in precision agriculture is very important in the process of increasing crop production. The local supply of onions in Merauke Regency have not fulfilled the demand, thus the high price in the market. Most of the demand for onion are still fulfilled from outside the region, as the production of local farmers has not been optimal. The weather has been identified as one of the factors that affect the quality of onion production. This study aims to create an automatic monitoring system based on an Arduino microcontroller to measure soil moisture and temperature in onion patches. The method used is to design an automatic monitoring device to determine soil moisture and temperature so that it can provide information about the growth and maintenance of onion patches. The Arduino microcontroller is connected to a reading sensor that is integrated with component devices to maintain a stable temperature and soil moisture. All devices and components are designed to operate in a custom-made environment in the form of a greenhouse prototype. The results of this study indicate that the tool and system are capable of capturing the soil moisture and temperature, as well as maintaining the soil moisture and temperature within certain parameters, in cloudy, wet and hot weather conditions. Doi: 10.28991/esj-2021-SP1-07 Full Text: PDF
Multi-Perspective Decision-making Cloud Computing Adoption Model for Small and Medium Enterprises (SMEs) Sayginer, Can; Ercan, Tuncay
Emerging Science Journal Vol. 4 (2020): Special Issue "IoT, IoV, and Blockchain" (2020-2021)
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SP1-010

Abstract

The research aims to test the model of integrated DOI theory and TOE framework to predict Cloud Computing (CC) decision-making intentions of SMEs, Izmir, Turkey. The survey data was collected from 140 Information Technology (IT) decision-makers via Google forms survey tool. Confirmatory factor analyses were made to examine the decision-making approach of SMEs. The study revealed that the variance of top management support and complexity explained 29.8% of the decision-making approach to CC adoption. The originality of the study is that the research on cloud computing in Turkey is scarce and not comprehensive either. In addition, they are not for Turkish SMEs. This research will bring together an introductory plan for cloud providers to understand the intentions of SMEs for adopting cloud computing. This research will also provide scholars with an in-depth analysis of the status contributing to the academic research in the field of ICT development in developing countries. This study will contribute to SMEs' ICT infrastructure policies, and support governments in creating a legal framework to make laws for a secure environment for SMEs to reduce costs, and gain a competitive advantage over Large Enterprises (LEs). Doi: 10.28991/esj-2021-SP1-010 Full Text: PDF
Environmental Energy Harvesting Techniques to Power Standalone IoT-Equipped Sensor and Its Application in 5G Communication Singh, Satyanand
Emerging Science Journal Vol. 4 (2020): Special Issue "IoT, IoV, and Blockchain" (2020-2021)
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SP1-08

Abstract

In the recent few years, due to its significant deployment to meet global demand for smart cities, the Internet of Things (IoT) has gained a lot of attention. Environment energy harvesting devices, which use ambient energy to generate electricity, could be a viable option in near future for charging or powering stand-alone IoT sensors and electronic devices. The key advantages of such energy harvesting gadgets are that they are environmentally friendly, portable, wireless, cost-effective, and compact. It is significant to propos and fabricate an improved, high-quality, economical, and efficient energy harvesting systems to overcome power supply to tiny IoT devices at the remote locations. In this article, various types of mechanisms for harvesting renewable energies that can power sensor enabled IoT locally, as well as its associated wireless sensor networks (WSNs), are reviewed. These methods are discussed in terms of their advantages and applications, as well as their drawbacks and limitations. Furthermore, methodological performance analysis for the decade 2005 to 2020 is surveyed in order to identify the methods that delivered high output power for each device. Furthermore, the outstanding breakthrough performances of each of the aforementioned micro-power generators during this time period are emphasized. According to the research, thermoelectric modules can convert up to 2500í—10^(-3) W/cm^2, thermo-photovoltaic 10.9%, piezoelectric 10,000 mW/cm^3 and microbial fuel cell 6.86 W/m^2 of energy. Doi: 10.28991/esj-2021-SP1-08 Full Text: PDF
Fingerprint Database Enhancement by Applying Interpolation and Regression Techniques for IoT-based Indoor Localization Suroso, Dwi Joko; Adiyatma, Farid Yuli Martin; Cherntanomwong, Panarat; Sooraksa, Pitikhate
Emerging Science Journal Vol. 4 (2020): Special Issue "IoT, IoV, and Blockchain" (2020-2021)
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2021-SP1-012

Abstract

Most applied indoor localization is based on distance and fingerprint techniques. The distance-based technique converts specific parameters to a distance, while the fingerprint technique stores parameters as the fingerprint database. The widely used Internet of Things (IoT) technologies, e.g., Wi-Fi and ZigBee, provide the localization parameters, i.e., received signal strength indicator (RSSI). The fingerprint technique advantages over the distance-based method as it straightforwardly uses the parameter and has better accuracy. However, the burden in database reconstruction in terms of complexity and cost is the disadvantage of this technique. Some solutions, i.e., interpolation, image-based method, machine learning (ML)-based, have been proposed to enhance the fingerprint methods. The limitations are complex and evaluated only in a single environment or simulation. This paper proposes applying classical interpolation and regression to create the synthetic fingerprint database using only a relatively sparse RSSI dataset. We use bilinear and polynomial interpolation and polynomial regression techniques to create the synthetic database and apply our methods to the 2D and 3D environments. We obtain an accuracy improvement of 0.2m for 2D and 0.13m for 3D by applying the synthetic database. Adding the synthetic database can tackle the sparsity issues, and the offline fingerprint database construction will be less burden. Doi: 10.28991/esj-2021-SP1-012 Full Text: PDF

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