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All Journal Journal of Applied Science, Engineering, Technology, and Education ARRUS Journal of Mathematics and Applied Science International Journal of Advanced Science Computing and Engineering
Botto-Tobar, Miguel
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Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics Physics Other

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Implementation of Traffic Monitoring Technology Using Smart Surveillance in Intelligent Transportation System Rimra, Ihsan Lumasa; Lifwarda; Komanjali, Yuliano; Botto-Tobar, Miguel
International Journal of Advanced Science Computing and Engineering Vol. 5 No. 3 (2023)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.5.3.166

Abstract

Currently transportation is very attached to human life, almost every family and even every adult human being has a vehicle as a means of transportation. Based on this, a conclusion can be drawn that population growth will trigger an increase in the number of vehicles in Indonesia. The implementation of Traffic Monitoring Using Smart Surveillance in the Intelligent Transportation System is research on information and communication technology in the transportation system in order to increase mobility, reduce congestion resulting from the buildup of vehicles in one lane, and be taken into consideration by road users before crossing a road section. This system uses the Background Subtraction method, and object detection. This system was created by utilizing OpenCV and Python programming language. This research obtained an accuracy of 93.1% on camera A and 93.5% on camera B in calculating passing vehicles in the test using simulations monitored via cameras in real time.
Cluster Analysis Using Ensemble ROCK Method in District/City Grouping in South Sulawesi Province based on People's Welfare Indicators Hidayat, Taufiq; Ruliana, Ruliana; Rais, Zulkifli; Botto-Tobar, Miguel
ARRUS Journal of Mathematics and Applied Science Vol. 3 No. 1 (2023)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience1761

Abstract

Cluster analysis is a data mining technique used to group data based on the similarity of attributes of object data. One of the problems that are often encountered in cluster analysis is data with a mixed categorical and numerical scale. The clustering stage for mixed data using the ensemble ROCK (Robust Clustering using links) method is carried out by combining clustering outputs from categorical and numeric scale data. The method used for categorical data is the ROCK method and the method used for numerical data is the Hierarchical Agglomerative method. The best clustering method is determined based on the criteria for the ratio between the standard deviations within the group (SW) and the smallest standard deviation between groups (SB). Based on 24 observation objects in the regencies and cities of the Province of South Sulawesi, the ROCK ensemble method with a value of 0.1 produces three clusters with a ratio value of 2,27 x10-16 based on the combination of the output results of the ROCK method and the Hierarchical Agglomerative method
Bibliometric Analysis of “Statistics: A Journal of Theoretical and Applied Statistics” on 1985-2021 Period Ahmar, Ansari Saleh; Botto-Tobar, Miguel; Rahman, Abdul; Cadena, Angela Diaz; Rusli, R.; Hidayat, Rahmat
Journal of Applied Science, Engineering, Technology, and Education Vol. 4 No. 1 (2022)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (552.088 KB) | DOI: 10.35877/454RI.asci1135

Abstract

This study is a quantitative research using bibliometric analysis. This study aimed to find out more detail about the “Statistics: A Journal of Theoretical and Applied Statistics” or SJTAS which was published during 1985-2021. This was seen from the topic of study, country productivity, author contributions, and analysis of their citation. The data in this study were taken from the Scopus database using keywords: (ISSN(0233-1888) OR ISSN(1029-4910)). The results obtained from the Scopus database are 1.798 documents. The average article citation fluctuates annually and the highest article citation is in 2018. Keywords from articles published in the SJTAS are dominated by topics: order statistics (55 articles), asymptotic normality (43 articles), bootstrap (33 articles), exponential distribution (32 articles), and consistency (31 articles).
Co-Authors Abdul Rahman Ahmar, Ansari Saleh Cadena, Angela Diaz Ihsan Lumasa Rimra Komanjali, Yuliano Lifwarda Lifwarda R. Rusli Rahmat Hidayat Rais, Zulkifli Ruliana Ruliana, Ruliana Taufiq Hidayat