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Journal : JINAV: Journal of Information and Visualization

Correlation between Covid-19 and weather/climate indicators: A Response Ahmar, Ansari Saleh
JINAV: Journal of Information and Visualization Vol. 1 No. 1 (2020)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav158

Abstract

This is a response to article by Dr. Ramadhan Tosepu and his colleagues entitled: “Correlation between the weather and the Covid-19 pandemic in Jakarta, Indonesia” in Science of The Total Environment, Vol. 725; and Dr. Muhammad Farhan Bashir and his colleagues entitled: “Correlation between the climate indicators and the Covid-19 pandemics in New York, USA.” in Science of The Total Environment, Vol. 728. We agree with the results of their research, but there are things that need to be clarified in relation to the selection of the Spearman-rank correlation as an analytical tool, because the selection of this analysis is without the normality test of the data. Spearman-rank correlation is useful for non-normally distributed continuous data; can be used for ordinal data; and is relatively robust for outliers.
Forecast Error Calculation with Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) Ahmar, Ansari Saleh
JINAV: Journal of Information and Visualization Vol. 1 No. 2 (2020)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav303

Abstract

Calculation errors in forecasting a data are very important from a forecasting process. The high level of forecasting accuracy will affect the level of confidence in forecasting decision making.
Correlation between Covid-19 and weather/climate indicators: A Response Ansari Saleh Ahmar
JINAV: Journal of Information and Visualization Vol. 1 No. 1 (2020)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav158

Abstract

This is a response to article by Dr. Ramadhan Tosepu and his colleagues entitled: “Correlation between the weather and the Covid-19 pandemic in Jakarta, Indonesia” in Science of The Total Environment, Vol. 725; and Dr. Muhammad Farhan Bashir and his colleagues entitled: “Correlation between the climate indicators and the Covid-19 pandemics in New York, USA.” in Science of The Total Environment, Vol. 728. We agree with the results of their research, but there are things that need to be clarified in relation to the selection of the Spearman-rank correlation as an analytical tool, because the selection of this analysis is without the normality test of the data. Spearman-rank correlation is useful for non-normally distributed continuous data; can be used for ordinal data; and is relatively robust for outliers.
Forecast Error Calculation with Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) Ansari Saleh Ahmar
JINAV: Journal of Information and Visualization Vol. 1 No. 2 (2020)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav303

Abstract

Calculation errors in forecasting a data are very important from a forecasting process. The high level of forecasting accuracy will affect the level of confidence in forecasting decision making.
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.
Cross-Validation and Validation Set Methods for Choosing K in KNN Algorithm for Healthcare Case Study Robbi Rahim; Ansari Saleh Ahmar; 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.jinav1557

Abstract

KNN categorization is simple and successful in healthcare. In this research's example case study, the KNN algorithm classified the new record as "Abnormal." The classification method began with choosing K, then calculating the Euclidean distance between the new record and the training set, finding the K nearest neighbors, then classifying the new record based on those K neighbors. The findings show that the KNN algorithm is effective in healthcare and highlight several shortcomings that should be addressed in future study. Weighting variables, choosing the best K value, and handling non-uniform data are these restrictions. The findings show the KNN algorithm's medical potential.
The Effect of Review Video Making on Problem Based Learning to Spatial Ability Dewi Satria Ahmar; Muhammad Fath Azzajjad; Ansari Saleh Ahmar
JINAV: Journal of Information and Visualization Vol. 3 No. 2 (2022)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav1441

Abstract

The aims of thi study is to know the effect of review video making on problem based learning to spatial ability. This research is a quasy experimental research using posttest only control design. The experimental class applied video review on problem-based learning model and the control class did not do video review but only applied problem-based learning model. The population in this study amounted to 49 people and the research sample was 40 people. The sampling technique used in determining the research sample was purposive sampling technique. The research instrument used an essay test which was prepared based on indicators of spatial ability consisting of spatial perception, mental rotation, and spatial visualization. Data analysis techniques include descriptive analysis and inferential analysis. Descriptive data analysis describes the comparison of spatial ability scores of experimental and control classes while inferential analysis is used to test the hypothesis. Descriptive analysis of spatial abilities obtained the average value of the experimental class and control class is 90.50 and 59.50, The results of the spatial ability analysis test using the Mann-Whitney test showed a significance value <0.05, indicating that there is an effect of reviewing student-made videos in the Problem Based Learning Integrated Project assignment learning model on spatial abilities.
Evaluating ARIMA Models for Short-Term Rainfall Forecasting in Polewali Mandar Regency Ahmar, Ansari Saleh; Mokhtar, Ali
JINAV: Journal of Information and Visualization Vol. 5 No. 2 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav3266

Abstract

This study aims to forecast rainfall in Polewali Mandar Regency using the ARIMA model. This is a quantitative study that uses secondary data, specifically monthly rainfall data (in mm) from January 2008 to December 2020, obtained from the NERC EDS Centre for Environmental Data Analysis. Two ARIMA models were tested: ARIMA(0,1,1)(0,1,1)[12] and ARIMA(1,1,1)(0,1,1)[12], with model selection based on the Akaike Information Criterion (AIC), which balances model fit and complexity. The AIC calculation revealed that the ARIMA(1,1,1)(0,1,1)[12] model had a lower AIC value (1677.33) compared to the ARIMA(0,1,1)(0,1,1)[12] model (1678.16), making ARIMA(1,1,1)(0,1,1)[12] the preferred model. Using this model, the forecasted rainfall for the next five months is as follows: January 2021: 279.8745 mm, February 2021: 238.2206 mm, March 2021: 237.1745 mm, April 2021: 349.3206 mm, and May 2021: 336.0976 mm. These forecasts provide valuable information for water resource management, agricultural irrigation planning, and disaster mitigation related to rainfall. The study emphasizes the importance of selecting the appropriate model to improve forecasting accuracy.
Co-Authors Abdul Rahman Abdul Rahman Abdussakir Abdussakir Absussakir Abdussakir Achmad Sani Supriyanto Agus Nasir Ahmad Rifad Riadhi Ahmad Talib Akbar Iskandar Akbar Iskandar Alfairus, Muh. Qodri Ali Mokhtar Alief Imron Juliodinata Alok Kumar Panday Alsa, Yudhistira Ananda Andika Isma ANDIKA SAPUTRA Angela Diaz Cadena Asfar Asfar Asmar Asmar, Asmar Astuti, Niken Probondani Aswi, Aswi Ayu Rahayu Azzajjad, Muhammad Fath Boj del Val, Eva Boj, Eva Bustan, M Nadjib Dary Mochamad Rifqie Della Fadhilatunisa Dewi Fatmarani Surianto Dewi Satria Ahmar Djawad, Yasser Abd. Ersa Karwingsi Eva Boj Faizal Arya Samman Fathahillah Fathahillah Hamzah Upu Hardianti Hafid Hastuty Hastuty Hastuty Hastuty Hastuty Musa Herman Herman Hidayat M., Wahyu Ifriana Ifriana Ilimu, Edi Irwan Irwan Irwan Irwan Isma Muthahharah Jamaluddin Jamaluddin Kamaluddin Kamaluddin Kasmudin Mustapa Khadijah Khaeruddin Khaeruddin Lince, Ranak M. Miftach Fakhri Maemunah Magfirah Manalu, Yessi Febianti Mansyur Mansyur Marni Marni, Marni Meliyana R, Sitti Masyitah Miguel Botto-Tobar Misriani Suardin Mohd. Rizal Mohd. Isa Muhammad Abdy Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Farhan Muhammad Kasim Aidid Muhammad Kasim Aidid Muhammad Nadjib Bustan Muhammad Nadjib Bustan Muhammad Nusrang Muliadi Muliadi N. Nurahdawati Nachnoer Arss Nasrul Ihsan Niken Probondani Astuti Niken Probondani Astuti Novi Afryanthi S. Nur Anisa Nurdin Arsyad, Nurdin Nurhikmawati, Nurhikmawati Nurul Khofifah Salsabila Parkhimenko Vladimir Anatolievich Patmasari, Andi Poerwanto, Bobby R. Ruliana R. Rusli R. Rusli R. Rusli Rahman, Abdul Rahman, Muhammad Fatur Rahmat Hidayat Rahmat Hidayat Rais, Zulkifli Rajesh Kumar Ramli Umar Riny Jefri Rizal Bakri Robbi Rahim Rosidah Rosidah Rosidah Rosidah Ruliana Ruliana Ruliana, Ruliana Rusli Rusli Rusli Rusli Rusli Rusli Rusli Rusli Rustam, Sitti Nailah Sahid Sahid Salim Al Idrus Salim Al Idrus Sapto Haryoko Sarinah Emilia Tonio Shofiyah Al Idrus Singh, Pawan Kumar Siti Nurazizah Auliah Sitti Masyitah Meliyana R. Sitti Rahmawati Sobirov, Bobur Sri Hastuti Virgianti Pulukadang Sri Muliani Sriwahyuni, Andi Ayu Suci Lestari Sutamrin, Sutamrin Suwardi Annas Suwardi Annas Suwardi Annas Syafruddin Side Tabash, Mosab Tri Santoso Triutomo, Agung wahyuni wahyuni Yunus, Asmar Zakiyah Mar'ah Zakiyah Mar'ah Zamil Wahab Zulkifli Rais