Article Per Year (5 Year)
p-Index From 2019 - 2024
0.817
P-Index
This Author published in this journals
All Journal Journal of Applied Science, Engineering, Technology, and Education JINAV: Journal of Information and Visualization Daengku: Journal of Humanities and Social Sciences Innovation ARRUS Journal of Mathematics and Applied Science
Miguel Botto-Tobar
(1) Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands; (2) Research Group in Artificial Intelligence and Information Technology, University of Guayaquil, 090510, Guayaquil, Ecuador
Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Other

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

Found 4 Documents
Search

 1 
Bibliometric Analysis of “Statistics: A Journal of Theoretical and Applied Statistics” on 1985-2021 Period Ansari Saleh Ahmar; Miguel Botto-Tobar; Abdul Rahman; Angela Diaz Cadena; R. Rusli; Rahmat Hidayat
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).
Forecasting the Value of Oil and Gas Exports in Indonesia using ARIMA Box-Jenkins Ansari Saleh Ahmar; Miguel Botto-Tobar; Abdul Rahman; Rahmat Hidayat
JINAV: Journal of Information and Visualization Vol. 3 No. 1 (2022)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav260

Abstract

The objective of the study was to forecast the value of oil and gas exports in Indonesia using the ARIMA Box-Jenkins. With this prediction, it is hoped that it can be a study for future policy making. This oil and gas export data is obtained from the Indonesian Central Bureau of Statistics (BPS) website, in raw data from January 2010 to March 2022. This data is predicted using the ARIMA method with the help of R software. The stages of data analysis with ARIMA include: data stationary test, build the model indication, parameter estimation and significance test, and residual diagnostic test of the model. The results of data analysis conducted in this study show that there are 3 indications of models that were generated, namely ARIMA(1,1,0); ARIMA(0,1,1); and ARIMA(1,1,0). From these 3 model indications, the best model was ARIMA(0,1,1) with AIC value of 2047.65.
Cluster Analysis Using Ensemble ROCK Method in District/City Grouping in South Sulawesi Province based on People's Welfare Indicators Taufiq Hidayat; Ruliana Ruliana; Zulkifli Rais; Miguel Botto-Tobar
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
The Comparison of Single and Double Exponential Smoothing Models in Predicting Passenger Car Registrations in Canada Ansari Saleh Ahmar; Sitti Masyitah Meliyana; Miguel Botto-Tobar; Rahmat Hidayat
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 4 No. 2 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku2639

Abstract

This study aims to compare the two main variants of exponential smoothing methods in the context of business forecasting: Single Exponential Smoothing (SES) and Double Exponential Smoothing (DES). In this study, we applied these three methods to the data on Monthly Passenger Car Registrations in Canada from 2019 to 2022. The performance of each method was evaluated using Root Mean Square Error (RMSE) as the primary metric. The analysis results showed that Single Exponential Smoothing (SES) produced the best performance with the lowest RMSE of 13.07859 for an alpha of 0.6, compared to DES, which yielded higher RMSE values. These findings indicate that although DES have the capability to handle trends and seasonality, in some cases, especially when the data has single fluctuations without significant seasonal patterns or trends, SES can provide more accurate forecasting results. This study provides valuable insights for practitioners in selecting the most appropriate forecasting method based on the characteristics of the data at hand.
Co-Authors Ahmar, Ansari Saleh Angela Diaz Cadena R. Rusli Rahman, Abdul Rahmat Hidayat Ruliana Sitti Masyitah Meliyana R. Taufiq Hidayat Zulkifli Rais