cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Rahmat Hidayat
Contact Email
mr.rahmat@gmail.com
Phone
-
Journal Mail Official
rahmat@pnp.ac.id
Editorial Address
-
Location
Kota padang,
Sumatera barat
INDONESIA
JOIV : International Journal on Informatics Visualization
Published by Politeknik Negeri Padang
ISSN : 25499610     EISSN : 25499904     DOI : -
Core Subject : Science,
Computer Science & IT
JOIV : International Journal on Informatics Visualization is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of Computer Science, Computer Engineering, Information Technology and Visualization. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the JOIV follows the open access policy that allows the published articles freely available online without any subscription.
Arjuna Subject : -
Articles 16 Documents
 1   2 
Search results for , issue "Vol 5, No 1 (2021)" : 16 Documents clear
A Framework of Mutual Information Kullback-Leibler Divergence based for Clustering Categorical Data Yanto, Iwan Tri Riyadi; Setiyowati, Ririn; Azizah, Nur; Rasyidah, -
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.462

Abstract

Clustering is a process of grouping a set of objects into multiple clusters, so that the collection of similar objects will be grouped into the same cluster and dissimilar objects will be grouped into other clusters. Fuzzy k-means Algorithm is one of clustering algorithm by partitioning data into k clusters employing Euclidean distance as a distance function. This research discusses clustering categorical data using Fuzzy k-Means Kullback-Leibler Divergence. In the determination of the distance between data and center of cluster uses mutual information known as Kullback-Leibler Divergence distance between the joint distribution and the product distribution from two marginal distributions. Extensive theoretical analysis was performed to show the effectiveness of the proposed method. Moreover, the proposed method's comparison results with Fuzzy Centroid and Fuzzy k-Partition approaches in terms of response time and clustering accuracy were also performed employing several datasets from UCI Machine Learning. The experiment results show that the proposed Algorithm provides good results both from clustering quality and accuracy for clustering categorical data as compared to Fuzzy Centroid and Fuzzy k-Partition.
The Development of Cellular Automata-based Entrepreneurial Growth Simulator Cecilia E. Nugraheni; Vania Natali
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.430

Abstract

Entrepreneurship plays an essential role in the economic growth of a country. These roles include creating jobs, reducing unemployment, increasing people's income, combining production factors (nature, labor, capital, and expertise), and increasing national productivity. For the economy to thrive and healthy, it requires at least 4% of the population who work as entrepreneurs. Due to this vital role, entrepreneurial growth must be maintained. One of the efforts to do this is by monitoring growth directly and continuously. Besides that, another way is to do a simulation. By knowing the condition of entrepreneurship at one time and all the factors that affect entrepreneurial growth, simulations can be carried out to determine or predict future conditions. Based on this simulation, essential steps can be taken, or policies can be made to maintain profitable entrepreneurial growth. This paper presents a mathematical model that can simulate and visualize entrepreneurship's growth in six provinces of Sumatra Island, Indonesia. This mathematical model uses cellular automata as its basis and is called Entrepreneurial Cellular Automata (ECA). One of the advantages of Cellular Automata is that it is easy to visualize. The entrepreneurial model used as a reference is a model from the Global Entrepreneurship Monitoring (GEM). This mathematical model has been implemented in a simulator program. This paper describes the simulator development and the use of simulator to simulate and visualize the entrepreneurial growth of the six provinces.
Combining Hybrid Approach Redefinition-Multiclass Imbalance (HAR-MI) and Hybrid Sampling in Handling Multi-Class Imbalance and Overlapping Hartono Hartono; Erianto Ongko
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.420

Abstract

The class imbalance problem in the multi-class dataset is more challenging to manage than the problem in the two classes and this problem is more complicated if accompanied by overlapping. One method that has proven reliable in dealing with this problem is the Hybrid Approach Redefinition-Multiclass Imbalance (HAR-MI) method which is classified as a hybrid approach that combines sampling and classifier ensembles. However, in terms of diversity among classifiers, a hybrid approach that combines sampling and classifier ensembles will give better results. HAR-MI provides excellent results in handling multi-class imbalances. The HAR-MI method uses SMOTE to increase the number of samples in the minority class. However, this SMOTE also has a weakness where an extremely imbalanced dataset and a large number of attributes will be over-fitting. To overcome the problem of over-fitting, the Hybrid Sampling method was proposed. HAR-MI combination with Hybrid Sampling is done to increase the number of samples in the minority class and at the same time reduce the number of noise samples in the majority class. The preprocessing stages at HAR-MI will use the Minimizing Overlapping Selection under Hybrid Sampling (MOSHS) method, and the processing stages will use Different Contribution Sampling. The results obtained will be compared with the results using Neighbourhood-based under-sampling. Overlapping and Classifier Performance will be measured using Augmented R-Value, the Matthews Correlation Coefficient (MCC), Precision, Recall, and F-Value. The results showed that HAR-MI with Hybrid Sampling gave better results in terms of Augmented R-Value, Precision, Recall, and F-Value
A Survey on Smart Campus Implementation in Malaysia Musa, Masitah; Ismail, Mohd Norasri; Md Fudzee, Mohd Farhan
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.434

Abstract

Universities around the world are actively implementing smart campuses. A smart campus is a campus environment capable of providing efficient technology and infrastructure in providing services to support and improve the teaching process, research, and student experience. It comprises initiatives to better support and enhances the better experience in the teaching and learning process and other services in the campus environment. To successfully implement the initiatives, a framework is required to define the scope of the implementation. Several universities in Malaysia are currently developing initiatives to implement their smart campus. This paper surveyed the literature and resources from universities in Malaysia to identify smart campus initiatives implemented following the smart campus domain. Due to the lack of resources available in the prominent database of indexed journal articles, the main source of review is based on official university sources such as official websites and so on. The result shows that all universities implemented all smart campus domains. Smart Management domain has the highest number of 58% of the overall initiatives. The second highest domain is Smart Learning at 13%, followed by Green Campus at 10%. We also identify that there is new domain of smart campus that was introduced. The new domain is Smart Research. Based on the survey, most universities in Malaysia are actively improving their work processes and the environment by implementing smart campus.
Drivers of Cloud Computing Adoption in Small Medium Enterprises of Indonesia Creative Industry Gui, Anderes; Fernando, Yudi; Shaharudin, Muhammad Shabir; Mokhtar, Mazita; Karmawan, I Gusti Made; Suryanto, -
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.461

Abstract

Cloud computing is one of the enablers of Industrial Revolution 4.0 (IR.40). IR 4.0 is advantageous as it allows companies to increase performance and productivity. However, there are many enablers of IR 4.0, such as big data analytics, cloud computing, machine learning, and blockchain. However, the readiest to be used technology is cloud computing. While the advantages of cloud computing are well understood from the perspective of the literature and companies' point of view, the empirical evidence is still scarce. The research explores the drivers of cloud adoption between small and medium-sized enterprises (SMEs) in Indonesia. The study method is a quantitative method through e-survey data collection analyzed using IBM SPSS and Smart PLS software. The recognition of drivers will allow IT decision-makers to design the right platform for SMEs, increasing their company competitiveness. The findings revealed that cloud flexibility, perceived concern, privacy, relative advantage, perceived cost-benefit, quality of service, and top management support are among the top cloud adoption priorities that need to be improved in the creative industry to ensure the adoption of cloud computing more apparent. The study's contribution revealed that cloud computing is no longer at the infant stage in terms of adoption. Thus, the findings paved the way for scholars to undertake future research focusing on cloud computing implementation. Companies, on the other hand, can learn from this research by improving the adoption aspects.
Subjective Norms and Academic Dishonesty: A Decision Tree Algorithm Analysis Dewanti, Patriani Wahyu; Purnama, Ida Ayu; Sukirno, -; Parthasarathy, Karthikeyan
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.423

Abstract

Academic dishonesty becomes an exciting phenomenon to be examined. This research aimed to examine the effect of subjective norms on academic dishonesty. Data were collected from 426 accounting students from public and private universities in Yogyakarta, Indonesia. The data were analyzed with the J48 algorithm decision tree. The interest that happened in the low subjective norms node was divided into public universities and private universities. Based on the decision of tree visualization, male students with the more extended length of study in public universities tended to have lower subjective norms but higher academic dishonesty than their counterparts. The results were discussed, and recommendations were also provided to several relevant parties.

Page 2 of 2 | Total Record : 16

 1   2 

Filter by Year

2021 2021


Reset
Filter By Issues
All Issue Vol 9, No 6 (2025) Vol 9, No 5 (2025) Vol 9, No 4 (2025) Vol 9, No 3 (2025) Vol 9, No 2 (2025) Vol 9, No 1 (2025) Vol 8, No 3-2 (2024): IT for Global Goals: Building a Sustainable Tomorrow Vol 8, No 4 (2024) Vol 8, No 3 (2024) Vol 8, No 2 (2024) Vol 8, No 1 (2024) Vol 7, No 3-2 (2023): Empowering the Future: The Role of Information Technology in Building Resilien Vol 7, No 4 (2023) Vol 7, No 3 (2023) Vol 7, No 2 (2023) Vol 7, No 1 (2023) Vol 6, No 2-2 (2022): A New Frontier in Informatics Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation Vol 6, No 4 (2022) Vol 6, No 3 (2022) Vol 6, No 2 (2022) Vol 6, No 1 (2022) Vol 5, No 4 (2021) Vol 5, No 3 (2021) Vol 5, No 2 (2021) Vol 5, No 1 (2021) Vol 4, No 4 (2020) Vol 4, No 3 (2020) Vol 4, No 2 (2020) Vol 4, No 1 (2020) Vol 3, No 2-2 (2019): Internet of Things and Smart Environments Vol 3, No 4 (2019) Vol 3, No 3 (2019) Vol 3, No 2 (2019) Vol 3, No 1 (2019) Vol 2, No 4-2 (2018): Cyber Security and Information Assurance Vol 2, No 3-2 (2018): The Diversity in Information Systems Vol 2, No 4 (2018) Vol 2, No 3 (2018) Vol 2, No 2 (2018) Vol 2, No 1 (2018) Vol 1, No 4-2 (2017): The Advancement of System and Applications Vol 1, No 4 (2017) Vol 1, No 3 (2017) Vol 1, No 2 (2017) Vol 1, No 1 (2017) More Issue