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All Journal JOIV : International Journal on Informatics Visualization
Rasyid, Alfandino
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Computer Science & IT

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Implementation of Big Data Information System Using Open-Source Metabase for Civil Registration and Vital Statistics Data Visualization in Surabaya Budiarti, Rizqi Putri Nourma; Sukaridhoto, Sritrusta; Zuhdi, Ubaidillah; Rasyid, Alfandino; Sonhaji, Agus Imam
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1722

Abstract

Civil registration involves the mandatory and continuous documentation of important life events of a country's population under local legal requirements. In many countries, these documents are required to access government services such as education, healthcare, social services, formal employment, insurance benefits, and inheritance rights. Indonesia should prioritize building a comprehensive Civil Registration and Vital Statistics (CRVS) using a big data information system to ensure every individual has a legal identity, can access government services, and collect accurate and reliable statistics on vital events through geospatial maps. Surabaya, a city in Indonesia, still needs a comprehensive Civil Registration and Vital Statistics (CRVS) system. We produce many informative visualizations from the query and modeling processes in Metabase. Based on the PIECES framework, this application's importance level is 4.56 or 91.25%, meaning the application is important, and the satisfaction level is 4.29 or 85.76%, meaning the application is satisfied for the respondents. This research provides a brief overview of how Metabase works and how it can be used to generate visualizations of job-type data. It demonstrates the ease with which visualizations can be changed and customized. It had a good affordability point, making its implementation easier and more beneficial. It also emphasizes the importance of having a powerful tool like Metabase for data analysis and decision-making, especially for the dispendukcapil as a civil registration agency.
High-Performance Computing on Agriculture: Analysis of Corn Leaf Disease Fajrianti, Evianita Dewi; Pratama, Afis Asryullah; Nasyir, Jamal Abdul; Rasyid, Alfandino; Winarno, Idris; Sukaridhoto, Sritrusta
JOIV : International Journal on Informatics Visualization Vol 6, No 2 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2.793

Abstract

In some cases, image processing relies on a lot of training data to produce good and accurate models. It can be done to get an accurate model by augmenting the data, adjusting the darkness level of the image, and providing interference to the image. However, the more data that is trained, of course, requires high computational costs. One way that can be done is to add acceleration and parallel communication. This study discusses several scenarios of applying CUDA and MPI to train the 14.04 GB corn leaf disease dataset. The use of CUDA and MPI in the image pre-processing process. The results of the pre-processing image accuracy are 83.37%, while the precision value is 86.18%. In pre-processing using MPI, the load distribution process occurs on each slave, from loading the image to cutting the image to get the features carried out in parallel. The resulting features are combined with the master for linear regression. In the use of CPU and Hybrid without the addition of MPI there is a difference of 2 minutes. Meanwhile, in the usage between CPU MPI and GPU MPI there is a difference of 1 minute. This demonstrates that implementing accelerated and parallel communications can streamline the processing of data sets and save computational costs. In this case, the use of MPI and GPU positively influences the proposed system.
Co-Authors Agus Imam Sonhaji, Agus Imam Budiarti, Rizqi Putri Nourma Fajrianti, Evianita Dewi Idris Winarno Nasyir, Jamal Abdul Pratama, Afis Asryullah Ubaidillah Zuhdi