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Clara Hetty Primasari
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INDONESIA
Indonesian Journal of Information System
Published by Universitas Atma Jaya Yogyakarta
ISSN : 26230119     EISSN : 26232308     DOI : -
Core Subject : Science,
Computer Science & IT
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Articles 192 Documents
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Online Review Analysis TriggeringHype in the Motion Picture Industry Laheba, Timothy Rey; Anggoro, Paulus Wisnu
Indonesian Journal of Information Systems Vol 4, No 1 (2021): August 2021
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i1.4528

Abstract

Competition in the motion picture industry continues to intensify at a very rapid pace. This phenomenon makes the production house continue to try to look for new ways to maximize revenue from the short life cycle of a film. One of the variables currently playing a larger role in decision-making to watch a film is a review. Two types of reviews are often used in the motion picture industry, namely the reviews from critics and fellow consumers. This study tries to see whose review will trigger a hype or buzz that much needed in the motion picture industry. Data from 219 respondents were collected to see their response regarding a review and whose review will encourage them to talk about a film to their peers and ultimately create the hype needed by a film. There are different perceptions for reviews given by critics, and fellow consumers with reviews from fellow consumers have greater potential to create and ignite hype in the motion picture industry.
Student Perceptions Analysis of Online Learning: A Machine Learning Approach Suparwito, Hari; Polina, Agnes Maria; Budiraharjo, Markus
Indonesian Journal of Information Systems Vol 4, No 1 (2021): August 2021
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i1.4594

Abstract

The covid-19 pandemic is currently occurring affects almost all aspects of life, including education. School From Home (SFH) is one of the ways to prevent the spread of Covid-19. The face-to-face learning method in class turns into online learning using information technology facilities. Even though there are many barriers to implementing classes online, online learning provides a new perspective for students' learning process. One of the factors for the online learning process's success is the interaction between the two main actors in the learning process, i.e., lecturers and students. The study's purpose was to analyze students' perceptions of the online learning process. The research data were obtained from a student questionnaire, which included five main criteria in the learning process: 1) self-management aspects, 2) personal efforts, 3) technology utilization, 4) perceptions of self-roles, and 5) perceptions of the role of the lecturer. Students provide an assessment through a questionnaire about the online learning methods they experience during the Covid-19 pandemic. The random forest algorithm was applied to examine data. The study results were focused on three main criteria (variable importance) that affect students' perceptions of the online learning process. The results described that the students' satisfaction in online learning is influenced by 1) The relationship between students and lecturers. 2) The learning materials need to be changed and adapted to the online learning method; 3) The use of technology to access online learning. The study contributes to improving the online learning method for the student.
Social Media and the COVID-19: South African and Zimbabwean Netizens’ Response to a Pandemic Mutanga, Murimo Bethel; Ureke, Oswelled; Chani, Tarirai
Indonesian Journal of Information Systems Vol 4, No 1 (2021): August 2021
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i1.4338

Abstract

Since the end of 2019, the world faced a major health crisis in the form of the Coronavirus (COVID-19) pandemic. To mitigate the impact of the pandemic, governments across the globe instituted measures such as restricting local and international travel and in many cases, ordering citizens to stay indoors. Considering the social and economic impact of these restrictions it becomes crucial to investigate internet citizens’ (netizens) perception about the precautionary measures adopted. The study is anchored in the digital public sphere theory, which treats social media applications as virtual platforms where netizens commune to share ideas and debate about issues that affect them. Social media platforms already have critical public views on the current pandemic. However, the majority of this data is unstructured and difficult to interpret. Natural language processing (NLP), on the other hand, makes the task of gathering and analysing vast amounts of textual data feasible. Extracting structured knowledge from natural language, however, comes with unique challenges due to diverse linguistic properties including abbreviation, spelling mistakes, punctuations, stop words and non-standard text. In this work, The Latent Dirichlet Allocation (LDA) algorithm was applied to tweeter data to extract topics discussed by netzens from Zimbabwe and South Africa.  The primary focus of this paper, is to comparatively explore the variety of topics that occupied twitter communities from the two countries. We examine whether or not the national identities that define and differentiate citizens of these countries also exist on Twitter as evident in the emerging topics. Furthermore, this work investigated public opinion by analysing how citizens discuss the issues around the COVID-19 pandemic on social media
Entrepreneurial Modes towards Information Technology Applications in Business during Pandemic Covid-19 Based on Indonesia SMEs’ Stories Robertus In Nugroho Budisantoso; Antonius Sumarwan
Indonesian Journal of Information Systems Vol. 4 No. 2 (2022): February 2022
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i2.4840

Abstract

This paper aims to identify entrepreneurial modes towards information technology applications in business during pandemic Covid-19 based on Indonesia SMEs’ stories. This study uses phenomenological approach in discerning 33 Economics students’ reports on SMEs’ ways in relating to social media platforms in the midst of the pandemic as relatively different business instruments driven by information technology along with their encounters to new opportunities within novel landscape of business. The reports indicate a general pattern of three critical stages linked to entrepreneurial challenges namely in the first stage business distortion, in the middle efficiency calculation, and finally available resources allocation. Using two factors i.e. learning capability of the business actors and the sophistication degree of information technology applications, the ways through which entrepreneurs relate to information technology within pandemic context can be identified into four types of mode namely adoption, adaptation, aversion, and abandon. Most of them are in adoption mode, few are in adaptation and abandon modes, and none in aversion mode.
Evaluation of UAJY Learning Management System’s Usability using USE Questionnaire and Eye-tracking Aloysius Gonzaga Pradnya Sidhawara
Indonesian Journal of Information Systems Vol. 4 No. 2 (2022): February 2022
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i2.5273

Abstract

One of the influential learning resources utilized today is a web-based learning management system. The web-based e-learning’s usability is also influenced by the user interface. In measuring usability, eye-tracking technology can be employed to examine eye gaze of an individual when looks at a specific point at a certain time. The use of eye-tracking is beneficial in obtaining objective data. This study aims to evaluate the usability of UAJY Learning Management System website interface and examine the user's interaction with the website interface. Thirty-five participants were recruited in a usability testing experiment. Participants were asked to do three tasks related to the use of e-learning features while their eye movements were recorded. The USE Questionnaire and task-related question data were processed using statistical descriptive methods and eye movement data generated into heatmaps. The Usefulness, Ease of Use, Ease of Learn, and Satisfaction aspects of the UAJY LMS gains more than 80% feasibility percentage. Overall results of feasibility categorized the UAJY LMS as Very Feasible. There was no difference found in usability aspects between gender, faculty background, and eye condition groups. Heatmaps results show that navigational elements in the LMS are utilized properly and successfully help participants in performing tasks.
A Survey of Face Recognition based on Convolutional Neural Network Raymond Erz Saragih; Quynh Huong To
Indonesian Journal of Information Systems Vol. 4 No. 2 (2022): February 2022
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i2.5439

Abstract

Face recognition is one of the interesting research topics in the field of computer vision. In recent years, deep learning methods, especially the Convolutional Neural Network, have progressed. One of the successes of CNN is in face recognition. Face recognition by computer is a technique done so that the computer can automatically recognize faces in an image. Various researchers have conducted related research on facial recognition. This survey presents researches related to face recognition based on Convolutional Neural Network that has been conducted. The studies used are studies that have been published in the last five years. It was performed to determine the renewal that emerged in face recognition based on Convolutional Neural Network. The basic theory of the Convolutional Neural Network, face recognition, and description of the database used in various researches are also discussed. Hopefully, this survey can provide additional knowledge regarding face recognition based on the Convolutional Neural Network.
Game Design Factor Questionerin User Experience Analysis on Selera Nusantara Game Kathryn Widhiyanti; Kusuma Dewangga; Firas Almukhtar
Indonesian Journal of Information Systems Vol. 4 No. 2 (2022): February 2022
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i2.5449

Abstract

Game products are one of the media to provide pleasure, satisfaction and knowledge for users. Game Selera Nusantara is a game product created by a game studio in Yogyakarta, namely Gambir Studio, created with the aim of providing pleasure, satisfaction and knowledge to its users. In order for the goal of the Selera Nusantara Game to be achieved, a game design by a user-centered game designer is needed. Game Selera Nusantara is a game with the Casual genre that has a target audience of children and teenagers with the main goal of introducing Nusantara cuisine. The good aim of the Selera Nusantara Game which introduces the culture of the archipelago is the basis of this research by assessing the quality of the game so that it can be accepted by the target audience optimally. The User Experience method with Game Design Factor Questionaire and compared with the results of interviews with game designers from Game Selera Nusantara used in this study provides an analysis of the quality of the game quantitatively. The results of the analysis show that Game Selera Nusantara has a high score on the criteria of Game Goals, Game Mechanism, Interaction, Fantasy Game, Narrative, Sensation, Game Value, Mystery, Flow, which is more than 90%. This means that the Selera Nusantara game has been able to fulfill the goal of providing pleasure, satisfaction and knowledge to its users in accordance with the design of the game designer.
Exploring of Potential of Cloud Computing for Small and Medium Enterprises Shafinah Kamarudin; Ahmad Hidayat Ahmad Khalili; Zakry Fitri Abd. Aziz; Khairul Anuar Kamarudin; Amelia Natasya Abdul Wahab
Indonesian Journal of Information Systems Vol. 4 No. 2 (2022): February 2022
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i2.5487

Abstract

Business activities such as human resources management, payroll, finance, and accounting are crucial for Small and Medium Enterprises (SMEs). Therefore, adopting technologies such as cloud computing is expected to improve SMEs’ efficiency. The migration from current business practices to cloud computing amongst SME entrepreneurs remains a challenge. Therefore, this study presents a short review of cloud computing concepts, the characteristics, types of cloud computing service models, and also cloud computing deployment models. This study highlights the benefits and challenges faced by SMEs entrepreneurs in adopting cloud computing. Also, this study explores the existing cloud computing services provided for SMEs. The present study aims to provide a better understanding of cloud computing’s potential to be applied in helping SMEs manage their business activities.
NoonGil Lens+: Second Level Face Recognition from Detected Objects to Decrease Computation and Performance Trade-off Jo Vianto; Djoko Budiyanto Setyohadi; Anton Satria Prabuwono; Mohd Sanusi Azmi; Eddy Julianto
Indonesian Journal of Information Systems Vol. 4 No. 2 (2022): February 2022
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i2.5488

Abstract

Artificial intelligence has developed in various fields. The development became more significant after Neural Networks(NN) began to gain popularity. Convolutional Neural Networks(CNNs) are good at solving problems such as classification and object detection. However, the CNNs model tends to function to solve a specific problem. In the case of both object detection and face recognition it is difficult to make a single model that works well. NoonGil Lens+ is expected to be an approach that can solve both problems at once. As well as being a solution, it is also hoped that this approach can reduce the trade-off of accuracy and execution speed. The approach we propose can be called as Noongil Lens+, a system that connects YOLOv3 and FaceNet. It is inspired from a korean series called ‘STARTUP’. The author only develops the FaceNet model and the proposed system in this paper (NoonGil Lens+). Region Selection, a machine learning-based greedy approach was proposed to determine snapshots to fed into FaceNet for facial identity classification. FaceNet is trained on the CelebA dataset which has gone through the preprocessing process and is validated using the LFW dataset. NoonGil Lens+ was validated using 70 images of 7 celebrities, characters, and athletes. In general, the research was carried out successfully. NoonGil Lens+ using Region Selection has an accuracy of up to 75.2%. The Region Selection execution speed is also faster compared to Cascade Faces.
Performance Comparison of Deep Learning Models to Detect Covid-19 Based on X-Ray Images Slamet Riyadi; Yunita Lestari; Cahya Damarjati; Kamarul Hawari Ghazali
Indonesian Journal of Information Systems Vol. 4 No. 2 (2022): February 2022
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i2.5491

Abstract

The SARS-Cov-2 outbreak caused by a coronavirus infection shocked dozens of countries. This disease has spread rapidly and become a new pandemic, a serious threat and even destroys various sectors of life. Along with technological developments, various deep learning models have been developed to classify between Covid-19 and Normal X-ray images of lungs, such as Inception V3, Inception V4 and MobileNet. These models have been separately reported to perform good classification on Covid-19. However, there is no comparison of their performance in classifying Covid-19 on the same data. This research aims to compare the performance of the three mentioned deep learning models in classifying Covid-19 based on X-ray images. The methods involve data collection, pre-processing, training, and testing using the three models. According to 2,169 dataset, the InceptionV3 model obtained an average accuracy value of 99.62%, precision value 99.65%, recall value 99.5%, specificity value 99.5%, and f-score value 99.52%; while the InceptionV4 model obtained an average accuracy value of 97.79%, precision value 98.11%, recall value 90.18%, specificity value 90.18%, and f-score value 97.25%; and the MobileNet model obtained an average accuracy value of 99.67%, precision value 99.77%, recall value 99.38%, specificity value 99.38%, and f-score value of 99.67%. The three models can classify the Covid-19 and Normal X-ray images based on research results, while the MobileNet model achieved the best performance. The model has stable performance in achieving graphic results and has extensive layers; the more layers there are to achieve better accuracy results.

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