Article Per Year (5 Year)
p-Index From 2019 - 2024
0.888
P-Index
This Author published in this journals
All Journal Aptisi Transactions on Technopreneurship (ATT)
Hiroshi Kenta
University Of Miyazaki
Humanities Computer Science & IT Economics, Econometrics & Finance Education Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Application of iLearning Education in Learning Methods for Entrepreneurship and Elementary School Student Innovation Kim Beom Rii; Lee Kyung Choi; Yamato Shino; Hiroshi Kenta; Irsa Rizkita Adianita
Aptisi Transactions On Technopreneurship (ATT) Vol 2 No 2 (2020): September
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v2i2.90

Abstract

Primary school is an early age in the introduction of information and communication technology, therefore it is necessary to be prepared abilities and skills in the use of technology. Learning about entrepreneurship at the elementary school level is generally still traditional, where valuable renewal results are created. However, in this 4.0 era, many elementary students still traditionally run entrepreneurship, this has not been a challenge in line with the Ministry of Education and Culture on an independent campus. In order to create the involvement of young people in the field of entrepreneurship, the right solution is how entrepreneurship learning in Learning can be applied from an early age, namely to elementary school students. SEP (School Enrichment Program) is an entrepreneurial learning application based on iLearning aimed at elementary school students to have a high quality of creativity and a willingness to innovate at an early age. Based on the observational test results the Ubiquitous Learning Method is significantly able to influence the motivation of elementary school students to be enthusiastic in terms of entrepreneurial learning from an early age, and to show the results that Cronbach's Alpha 0.9> 0.6 ie the SEP is very accurate in its application especially can improve the results significant in influencing the formation of intentions in entrepreneurship even more starting to spread the trend of entrepreneurship which has now touched various circles, one of them among students.
Gamification Based Blockchain Tournaments Between Miners Hiroshi Kenta; Yamato Shino; Dewi Immaniar; Eka Purnama Harahap; Alfian Dimas Ahsanul Rizki Ahmad
Aptisi Transactions On Technopreneurship (ATT) Vol 3 No 1 (2021): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v3i1.144

Abstract

We have modelled mining resource and cryptocurrency-related relationships into a non-cooperative game. Then we took advantage of the traffic congestion results, set a native convention for the Nash equilibria, and created a short algorithm to find the equilibria. Next, we will make calculations for several system models whose variations follow the existing mining resources and have appropriately allocated according to the details of the mining complexity level that has defeated. In the included resources, the game's result is the allocation of resources as a feature of a normalized Nash equilibrium. In the model that has proposed, we provide a property structure of the type of equilibrium that exists, such as a condition where there are two or more mining infrastructures that will be active and another state that explains that no Miners get results in wanting a specific cryptocurrency, like bitcoin.
Media Promotional for Art in Tangerang City with Audio Visual Adobe Creative Yamato Shino; Hiroshi Kenta; I Komang Mertayasa
Aptisi Transactions On Technopreneurship (ATT) Vol 4 No 2 (2022): July
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v4i2.115

Abstract

Historical buildings contain elements of art in the city of Tangerang, which have good potential to become a tourist destination, but they must be appropriately managed to generate a source of income for the region. The diversity of ethnicities, races, and religions is an important supporting factor in influencing the diversity of artistic values. One of them is the Lenggang Cisadane Dance which is typical art of Tangerang City. And many historical buildings such as the Thousand Doors Mosque, Fortress Museum, Kalipasir Mosque, Al-Adzhom Mosque, etc. Every historical asset needs to be introduced to the public, and this is the authority of the Communication and Information Technology Office (DisKomInfo). However, the information media used is still very minimal. Therefore, a study was conducted using the KPM method, which outputs video using the Adobe Creative Suite. The media needed to maximize promotion and information is the Video Art, Tourism, and Historic Buildings, with an informative and practical display. The beauty of Tangerang City holds history and high artistic value, so it is hoped that this research can increase public interest in studying history and doing tourism.
Image-based Air Quality Prediction using Convolutional Neural Networks and Machine Learning Marviola Hardini; Mochamad Heru Riza Chakim; Lena Magdalena; Hiroshi Kenta; Ageng Setiani Rafika; Dwi Julianingsih
Aptisi Transactions On Technopreneurship (ATT) Vol 5 No 1Sp (2023): Special Issue: Technopreneurship Driving Change in the Nation's Future Leadersh
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v5i1Sp.337

Abstract

Air quality has become a major public concern due to the significant threat posed by air pollution to human health, and rapid and efficient monitoring of air quality is crucial for pollution control and human health. In this paper, deep learning and image-based models are proposed to estimate air quality. To evaluate the level of air quality, the model collects feature information from landscape photos taken by mobile cameras. To analyze public perception of air quality, researchers collected questionnaire data from 257 people. The Smartpls method allows for structural analysis to determine the influence of each variable on other variables and the extent of their contribution to the final variable of overall perception of air quality. This study aims to develop a novel approach for air quality prediction using image-based data and machine learning techniques. The research used convolutional neural networks to extract features from images and predict the air quality index. The study was conducted using a dataset obtained from a network of air quality sensors across the city. The results of the study showed that the proposed approach can provide accurate air quality predictions compared to the traditional methods. The developed model was able to capture the complex relationships between air quality and environmental factors, such as temperature and humidity. The implications of the study suggest that image-based air quality prediction can be a powerful tool for improving public health and reducing the impact of air pollution. The study's findings hold promise for a healthier future by facilitating more effective pollution management and improved air quality regulation. The study's primary novelty lies in its approach to air quality prediction by deploying convolutional neural networks to extract image features for predicting air quality indices. This application of advanced machine learning techniques to image-based data for air quality estimation marks a significant advancement.
Co-Authors Alfian Dimas Ahsanul Rizki Ahmad Dewi Immaniar Dwi Julianingsih Harahap, Eka Purnama I Komang Mertayasa Irsa Rizkita Adianita Kim Beom Rii Lee Kyung Choi Lena Magdalena Marviola Hardini Mochamad Heru Riza Chakim Rafika, Ageng Setiani Yamato Shino