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Dr. Bens Pardamean
Bina Nusantara University

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Hold a dual-appointment as Associate Professor of Computer Science and Director of Bioinformatics & Data Science Research Center | AI R&D Center at Bina Nusantara (BINUS) University in Jakarta, Indonesia.

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Communication
Published: 24 July 2021 in Sustainability
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COVID-19, as a global pandemic, has spread across Indonesia. Jakarta, as the capital of Indonesia, is the province with the most positive cases. The government has issued various guidelines, both at the central and regional levels. Since it began in 2021, the planned new measures, called ‘Pemberlakuan Pembatasan Kegiatan Masyarakat Darurat’, or PPKM emergency public activity restrictions, began with the possibility that the number of active cases might decrease. Accordingly, global vaccinations were also carried out, as they were in Indonesia. However, the first phase prioritized frontline health workers and high-risk elderly people. This study conducted a causal impact analysis to determine the effectiveness of PPKM in Jakarta and its vaccination program against the increase in daily new cases. Based on this test, PPKM showed a significant effect on the addition of daily new cases and recovered cases. Conversely, the vaccination program only had a significant impact on recovered cases. A forecast of the COVID-19 cases was conducted and indicated that the daily new cases showed a negative trend, although it fluctuated for the next 7 days, while death and recovered cases continued to increase. Hence, it can be said that the vaccination program has still not shown its effectiveness in decreasing the number of daily new cases while PPKM is quite effective in suppressing new cases.

ACS Style

Toni Toharudin; Resa Pontoh; Rezzy Caraka; Solichatus Zahroh; Panji Kendogo; Novika Sijabat; Mentari Sari; Prana Gio; Mohammad Basyuni; Bens Pardamean. National Vaccination and Local Intervention Impacts on COVID-19 Cases. Sustainability 2021, 13, 8282 .

AMA Style

Toni Toharudin, Resa Pontoh, Rezzy Caraka, Solichatus Zahroh, Panji Kendogo, Novika Sijabat, Mentari Sari, Prana Gio, Mohammad Basyuni, Bens Pardamean. National Vaccination and Local Intervention Impacts on COVID-19 Cases. Sustainability. 2021; 13 (15):8282.

Chicago/Turabian Style

Toni Toharudin; Resa Pontoh; Rezzy Caraka; Solichatus Zahroh; Panji Kendogo; Novika Sijabat; Mentari Sari; Prana Gio; Mohammad Basyuni; Bens Pardamean. 2021. "National Vaccination and Local Intervention Impacts on COVID-19 Cases." Sustainability 13, no. 15: 8282.

Journal article
Published: 17 July 2021 in Atmosphere
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We reported the result of our study on the impact of Large-Scale Social Restriction (LSSR) phases due to the COVID-19 outbreak on the air quality in Jakarta. Specifically, this study covered the change of Air Quality Index (AQI) based on five pollutants, PM10, SO2, CO, O3, and NO2, contained in Jakarta’s air before and during LSSR. The AQI data were provided by the Ministry of Environment and Forestry, Indonesia, from January 2019 to December 2020 at five different locations in Jakarta, with missing data for March and September 2020 due to unknown reasons. These data were grouped into the period before the LSSR from January 2019 to February 2020 and the period during LSSR from April 2020 to December 2020. In order to measure the change in the air quality of Jakarta before and during LSSR, we ran a chi-squared test to the AQI for each location and LSSR phase as well as paired one-sided t-test for the seasonal trend. The result of this study showed that, in general, LSSR improved the air quality of Jakarta. The improvement was mainly contributed by reduced transportation activities that were induced by LSSR. Further analysis on the seasonal pollutants trend showed a variation of AQI improvement in each phase due to their unique characteristics.

ACS Style

Bens Pardamean; Reza Rahutomo; Tjeng Cenggoro; Arif Budiarto; Anzaludin Perbangsa. The Impact of Large-Scale Social Restriction Phases on the Air Quality Index in Jakarta. Atmosphere 2021, 12, 922 .

AMA Style

Bens Pardamean, Reza Rahutomo, Tjeng Cenggoro, Arif Budiarto, Anzaludin Perbangsa. The Impact of Large-Scale Social Restriction Phases on the Air Quality Index in Jakarta. Atmosphere. 2021; 12 (7):922.

Chicago/Turabian Style

Bens Pardamean; Reza Rahutomo; Tjeng Cenggoro; Arif Budiarto; Anzaludin Perbangsa. 2021. "The Impact of Large-Scale Social Restriction Phases on the Air Quality Index in Jakarta." Atmosphere 12, no. 7: 922.

Journal article
Published: 13 July 2021 in Sustainability
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The COVID-19 pandemic has caused effects in many sectors, including in businesses and enterprises. The most vulnerable businesses to COVID-19 are micro, small, and medium enterprises (MSMEs). Therefore, this paper aims to analyze the business vulnerability of MSMEs in Indonesia using the fuzzy spatial clustering approach. The fuzzy spatial clustering approach had been implemented to analyze the social vulnerability to natural hazards in Indonesia. Moreover, this study proposes the Flower Pollination Algorithm (FPA) to optimize the Fuzzy Geographically Weighted Clustering (FGWC) in order to cluster the business vulnerability in Indonesia. We performed the data analysis with the dataset from Indonesia’s national socioeconomic and labor force survey (SUSENAS and SAKERNAS). We first compared the performance of FPA with traditional FGWC, as well as several known optimization algorithms in FGWC such as Artificial Bee Colony, Intelligent Firefly Algorithm, Particle Swarm Optimization, and Gravitational Search Algorithm. Our results showed that FPAFGWC has the best performance in optimizing the FGWC clustering result in the business vulnerability context. We found that almost all of the regions in Indonesia outside Java Island have vulnerable businesses. Meanwhile, in most of Java Island, particularly the JABODETABEK area that is the national economic backbone, businesses are not vulnerable. Based on the results of the study, we provide the recommendation to handle the gap between the number of micro and small enterprises (MSMEs) in Indonesia.

ACS Style

Rezzy Caraka; Robert Kurniawan; Bahrul Nasution; Jamilatuzzahro Jamilatuzzahro; Prana Gio; Mohammad Basyuni; Bens Pardamean. Micro, Small, and Medium Enterprises’ Business Vulnerability Cluster in Indonesia: An Analysis Using Optimized Fuzzy Geodemographic Clustering. Sustainability 2021, 13, 7807 .

AMA Style

Rezzy Caraka, Robert Kurniawan, Bahrul Nasution, Jamilatuzzahro Jamilatuzzahro, Prana Gio, Mohammad Basyuni, Bens Pardamean. Micro, Small, and Medium Enterprises’ Business Vulnerability Cluster in Indonesia: An Analysis Using Optimized Fuzzy Geodemographic Clustering. Sustainability. 2021; 13 (14):7807.

Chicago/Turabian Style

Rezzy Caraka; Robert Kurniawan; Bahrul Nasution; Jamilatuzzahro Jamilatuzzahro; Prana Gio; Mohammad Basyuni; Bens Pardamean. 2021. "Micro, Small, and Medium Enterprises’ Business Vulnerability Cluster in Indonesia: An Analysis Using Optimized Fuzzy Geodemographic Clustering." Sustainability 13, no. 14: 7807.

Journal article
Published: 28 June 2021 in Symmetry
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Design: At the heart of time series forecasting, if nonlinear and nonstationary data are analyzed using traditional time series, the results will be biased. At the same time, if just using machine learning without any consideration given to input from traditional time series, not much information can be obtained from the results because the machine learning model is a black box. Purpose: In order to better study time series forecasting, we extend the combination of traditional time series and machine learning and propose a hybrid cascade neural network considering a metaheuristic optimization genetic algorithm in space–time forecasting. Finding: To further show the utility of the cascade neural network genetic algorithm, we use various scenarios for training and testing while also extending simulations by considering the activation functions SoftMax, radbas, logsig, and tribas on space–time forecasting of pollution data. During the simulation, we perform numerical metric evaluations using the root-mean-square error (RMSE), mean absolute error (MAE), and symmetric mean absolute percentage error (sMAPE) to demonstrate that our models provide high accuracy and speed up time-lapse computing.

ACS Style

Rezzy Caraka; Hasbi Yasin; Rung-Ching Chen; Noor Goldameir; Budi Supatmanto; Toni Toharudin; Mohammad Basyuni; Prana Gio; Bens Pardamean. Evolving Hybrid Cascade Neural Network Genetic Algorithm Space–Time Forecasting. Symmetry 2021, 13, 1158 .

AMA Style

Rezzy Caraka, Hasbi Yasin, Rung-Ching Chen, Noor Goldameir, Budi Supatmanto, Toni Toharudin, Mohammad Basyuni, Prana Gio, Bens Pardamean. Evolving Hybrid Cascade Neural Network Genetic Algorithm Space–Time Forecasting. Symmetry. 2021; 13 (7):1158.

Chicago/Turabian Style

Rezzy Caraka; Hasbi Yasin; Rung-Ching Chen; Noor Goldameir; Budi Supatmanto; Toni Toharudin; Mohammad Basyuni; Prana Gio; Bens Pardamean. 2021. "Evolving Hybrid Cascade Neural Network Genetic Algorithm Space–Time Forecasting." Symmetry 13, no. 7: 1158.

Journal article
Published: 11 June 2021 in IEEE Access
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Current approaches of university students’ Grade Point Average (GPA) prediction rely on the use of tabular data as input. Intuitively, adding historical GPA data can help to improve the performance of a GPA prediction model. In this study, we present a dual-input deep learning model that is able to simultaneously process time-series and tabular data for predicting student GPA. Our proposed model achieved the best performance among all tested models with 0.4142 MSE (Mean Squared Error) and 0.418 MAE (Mean Absolute Error) for GPA with a 4.0 scale. It also has the best $R^{2}$ -score of 0.4879, which means it explains the true distribution of students’ GPA better than other models.

ACS Style

Harjanto Prabowo; Alam Ahmad Hidayat; Tjeng Wawan Cenggoro; Reza Rahutomo; Kartika Purwandari; Bens Pardamean. Aggregating Time Series and Tabular Data in Deep Learning Model for University Students’ GPA Prediction. IEEE Access 2021, 9, 1 -1.

AMA Style

Harjanto Prabowo, Alam Ahmad Hidayat, Tjeng Wawan Cenggoro, Reza Rahutomo, Kartika Purwandari, Bens Pardamean. Aggregating Time Series and Tabular Data in Deep Learning Model for University Students’ GPA Prediction. IEEE Access. 2021; 9 ():1-1.

Chicago/Turabian Style

Harjanto Prabowo; Alam Ahmad Hidayat; Tjeng Wawan Cenggoro; Reza Rahutomo; Kartika Purwandari; Bens Pardamean. 2021. "Aggregating Time Series and Tabular Data in Deep Learning Model for University Students’ GPA Prediction." IEEE Access 9, no. : 1-1.

Communication
Published: 25 May 2021 in Sustainability
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Background and objectives: The impacts of COVID-19 are like two sides of one coin. During 2020, there were many research papers that proved our environmental and climate conditions were improving due to lockdown or large-scale restriction regulations. In contrast, the economic conditions deteriorated due to disruption in industry business activities and most people stayed at home and worked from home, which probably reduced the noise pollution. Methods: To assess whether there were differences in noise pollution before and during COVID-19. In this paper, we use various statistical methods following odds ratios, Wilcoxon and Fisher’s tests and Bayesian Markov chain Monte Carlo (MCMC) with various comparisons of prior selection. The outcome of interest for a parameter in Bayesian inference is complete posterior distribution. Roughly, the mean of the posterior will be clear with point approximation. That being said, the median is an available choice. Findings: To make the Bayesian MCMC work, we ran the sampling from the conditional posterior distributions. It is straightforward to draw random samples from these distributions if they have regular shapes using MCMC. The case of over-standard noise per time frame, number of noise petition cases, number of industry petition cases, number of motorcycles, number of cars and density of vehicles are significant at α = 5%. In line with this, we prove that there were differences of noise pollution before and during COVID-19 in Taiwan. Meanwhile, the decreased noise pollution in Taiwan can improve quality of life.

ACS Style

Rezzy Caraka; Yusra Yusra; Toni Toharudin; Rung-Ching Chen; Mohammad Basyuni; Vilzati Juned; Prana Gio; Bens Pardamean. Did Noise Pollution Really Improve during COVID-19? Evidence from Taiwan. Sustainability 2021, 13, 5946 .

AMA Style

Rezzy Caraka, Yusra Yusra, Toni Toharudin, Rung-Ching Chen, Mohammad Basyuni, Vilzati Juned, Prana Gio, Bens Pardamean. Did Noise Pollution Really Improve during COVID-19? Evidence from Taiwan. Sustainability. 2021; 13 (11):5946.

Chicago/Turabian Style

Rezzy Caraka; Yusra Yusra; Toni Toharudin; Rung-Ching Chen; Mohammad Basyuni; Vilzati Juned; Prana Gio; Bens Pardamean. 2021. "Did Noise Pollution Really Improve during COVID-19? Evidence from Taiwan." Sustainability 13, no. 11: 5946.

Accepted manuscript
Published: 20 May 2021 in Chinese Physics C
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In this paper, we utilize a potentially versatile Bayesian parameter approach to compute the value of the pion charge radius and quantify its uncertainty from several experimental $e^{+}e^{-}$ data sets for the pion vector form factor. We employ dispersion relations to model the pion vector form factor for the extraction of the radius. Nested model selection is used to determine the order of polynomial appearing in the form factor formulation that can be supported by the data, adapting the computation of Bayes evidence and Bayesian effective complexity following Occam's razor. Our findings show that five out of six used data sets favor the nine-parameter model for the radius extraction and we average the radii from the data sets based upon this. Despite of some inconsistencies with the most updated radius values, our approach may serve as a more intuitive way to deal with parameter estimations in dispersion theory.

ACS Style

Alam Ahmad Hidayat; Bens Pardamean. A Bayesian-based Approach for Extracting the Pion Charge Radius from Electron-electron Scattering Data. Chinese Physics C 2021, 1 .

AMA Style

Alam Ahmad Hidayat, Bens Pardamean. A Bayesian-based Approach for Extracting the Pion Charge Radius from Electron-electron Scattering Data. Chinese Physics C. 2021; ():1.

Chicago/Turabian Style

Alam Ahmad Hidayat; Bens Pardamean. 2021. "A Bayesian-based Approach for Extracting the Pion Charge Radius from Electron-electron Scattering Data." Chinese Physics C , no. : 1.

Journal article
Published: 11 May 2021 in Scientific Reports
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Colorectal cancer is a common cancer in Indonesia, yet it has been understudied in this resource-constrained setting. We conducted a genome-wide association study focused on evaluation and preliminary discovery of colorectal cancer risk factors in Indonesians. We administered detailed questionnaires and collecting blood samples from 162 colorectal cancer cases throughout Makassar, Indonesia. We also established a control set of 193 healthy individuals frequency matched by age, sex, and ethnicity. A genome-wide association analysis was performed on 84 cases and 89 controls passing quality control. We evaluated known colorectal cancer genetic variants using logistic regression and established a genome-wide polygenic risk model using a Bayesian variable selection technique. We replicate associations for rs9497673, rs6936461 and rs7758229 on chromosome 6; rs11255841 on chromosome 10; and rs4779584, rs11632715, and rs73376930 on chromosome 15. Polygenic modeling identified 10 SNP associated with colorectal cancer risk. This work helps characterize the relationship between variants in the SCL22A3, SCG5, GREM1, and STXBP5-AS1 genes and colorectal cancer in a diverse Indonesian population. With further biobanking and international research collaborations, variants specific to colorectal cancer risk in Indonesians will be identified.

ACS Style

Irawan Yusuf; Bens Pardamean; James W. Baurley; Arif Budiarto; Upik A. Miskad; Ronald E. Lusikooy; Arham Arsyad; Akram Irwan; George Mathew; Ivet Suriapranata; Rinaldy Kusuma; Muhamad F. Kacamarga; Tjeng W. Cenggoro; Christopher McMahan; Chase Joyner; Carissa I. Pardamean. Genetic risk factors for colorectal cancer in multiethnic Indonesians. Scientific Reports 2021, 11, 1 -9.

AMA Style

Irawan Yusuf, Bens Pardamean, James W. Baurley, Arif Budiarto, Upik A. Miskad, Ronald E. Lusikooy, Arham Arsyad, Akram Irwan, George Mathew, Ivet Suriapranata, Rinaldy Kusuma, Muhamad F. Kacamarga, Tjeng W. Cenggoro, Christopher McMahan, Chase Joyner, Carissa I. Pardamean. Genetic risk factors for colorectal cancer in multiethnic Indonesians. Scientific Reports. 2021; 11 (1):1-9.

Chicago/Turabian Style

Irawan Yusuf; Bens Pardamean; James W. Baurley; Arif Budiarto; Upik A. Miskad; Ronald E. Lusikooy; Arham Arsyad; Akram Irwan; George Mathew; Ivet Suriapranata; Rinaldy Kusuma; Muhamad F. Kacamarga; Tjeng W. Cenggoro; Christopher McMahan; Chase Joyner; Carissa I. Pardamean. 2021. "Genetic risk factors for colorectal cancer in multiethnic Indonesians." Scientific Reports 11, no. 1: 1-9.

Journal article
Published: 30 April 2021 in International Journal of Criminology and Sociology
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Nterdisciplinary and cross-cultural studies of the impacts of environment and social vulnerability must be undertaken to address the problem of social vulnerability in the foreseeable future. Scientist or social scientists should first continuously strive towards approaches can integrate municipal technological expertise, experiences, knowledge, perceptions, and expectations into emergency circumstances, so that people can be sharper on issues and offer responses with their matters. In this paper. We performing the Bibliometric Analysis to review published papers on the keyword 'Social Vulnerability'. There are 29,468 papers published in the last 52 years from 1969 to November 2020. Disaster research by implementing the Internet of Things (IoT), data mining, machine learning is still needed.

ACS Style

Toni Toharudin; Jadi Suprijadi; Rezzy Eko Caraka; Resa Septiani Pontoh; Rung Ching Chen; Youngjo Lee; Bens Pardamean. Social Vulnerability and How It Matters: A Bibliometric Analysis. International Journal of Criminology and Sociology 2021, 10, 610 -619.

AMA Style

Toni Toharudin, Jadi Suprijadi, Rezzy Eko Caraka, Resa Septiani Pontoh, Rung Ching Chen, Youngjo Lee, Bens Pardamean. Social Vulnerability and How It Matters: A Bibliometric Analysis. International Journal of Criminology and Sociology. 2021; 10 ():610-619.

Chicago/Turabian Style

Toni Toharudin; Jadi Suprijadi; Rezzy Eko Caraka; Resa Septiani Pontoh; Rung Ching Chen; Youngjo Lee; Bens Pardamean. 2021. "Social Vulnerability and How It Matters: A Bibliometric Analysis." International Journal of Criminology and Sociology 10, no. : 610-619.

Journal article
Published: 12 April 2021 in Symmetry
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Design: Health issues throughout the sustainable development goals have also been integrated into one ultimate goal, which helps to ensure a healthy lifestyle as well as enhances well-being for any and all human beings of all social level. Meanwhile, regarding the clime change, we may take urgent action to its impacts. Purpose: Nowadays, climate change makes it much more difficult to control the pattern of diseases transmitted and sometimes hard to prevent. In line with this, Centres for Disease Control (CDC) Taiwan grouped the spread of disease through its source in the first six main groups. Those are food or waterborne, airborne or droplet, vector-borne, sexually transmitted or blood-borne, contact transmission, and miscellaneous. According to this, academics, government, and the private sector should work together and collaborate to maintain the health issue. This article examines and connects the climate and communicable aspects towards Penta-Helix in Taiwan. Finding: In summary, we have been addressing the knowledge center on the number of private companies throughout the health care sector, the number of healthcare facilities, and the education institutions widely recognized as Penta Helix. In addition, we used hierarchical likelihood structural equation modeling (HSEMs). All the relationship variables among climate, communicable disease, and Penta Helix can be interpreted through the latent variables with GoF 79.24%.

ACS Style

Rezzy Caraka; Maengseok Noh; Rung-Ching Chen; Youngjo Lee; Prana Gio; Bens Pardamean. Connecting Climate and Communicable Disease to Penta Helix Using Hierarchical Likelihood Structural Equation Modelling. Symmetry 2021, 13, 657 .

AMA Style

Rezzy Caraka, Maengseok Noh, Rung-Ching Chen, Youngjo Lee, Prana Gio, Bens Pardamean. Connecting Climate and Communicable Disease to Penta Helix Using Hierarchical Likelihood Structural Equation Modelling. Symmetry. 2021; 13 (4):657.

Chicago/Turabian Style

Rezzy Caraka; Maengseok Noh; Rung-Ching Chen; Youngjo Lee; Prana Gio; Bens Pardamean. 2021. "Connecting Climate and Communicable Disease to Penta Helix Using Hierarchical Likelihood Structural Equation Modelling." Symmetry 13, no. 4: 657.

Research article
Published: 07 January 2021 in Nutrition and Cancer
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Reports from various population-based studies indicate that the incidence of colorectal cancer may be strongly affected by dietary patterns of the respective populations. The nature of dietary patterns of specific Indonesia population on the risk of colorectal cancer might differ from previously published data with the global population. Therefore, we conducted a study where the dietary pattern in colorectal cancer patient cohorts was compared to age- and population-matched control. We documented 89 colorectal cancer cases and among 173 individuals from the South Sulawesi population. A series of logistic regression and Fisher’s exact tests were utilized to test associations of dietary intakes and colorectal cancer risk as well as colorectal cancer staging. Our data demonstrate that vegetable (p-value = 8.70 × 10−26, OR = 0.49) and fruit (p-value = 7.59x10−5, OR = 0.70) intakes are associated with the reduced risk of colorectal cancer incidence. Conversely, acidic food, reheated food, meat, spicy food, and alcohol are associated with the increment case of cancer. Moreover, meat intake (p-value < 0.01) shows a significant association with cancer staging progression. Common dietary pattern is a determinant aspect to the colorectal cancer incidence as well as its staging progression.

ACS Style

Ika Nurlaila; Alam A. Hidayat; Arif Budiarto; Bharuno Mahesworo; Kartika Purwandari; Bens Pardamean. Dietary Intake as Determinant Nongenetic Factors to Colorectal Cancer Incidence and Staging Progression: A Study in South Sulawesi Population, Indonesia. Nutrition and Cancer 2021, 1 -9.

AMA Style

Ika Nurlaila, Alam A. Hidayat, Arif Budiarto, Bharuno Mahesworo, Kartika Purwandari, Bens Pardamean. Dietary Intake as Determinant Nongenetic Factors to Colorectal Cancer Incidence and Staging Progression: A Study in South Sulawesi Population, Indonesia. Nutrition and Cancer. 2021; ():1-9.

Chicago/Turabian Style

Ika Nurlaila; Alam A. Hidayat; Arif Budiarto; Bharuno Mahesworo; Kartika Purwandari; Bens Pardamean. 2021. "Dietary Intake as Determinant Nongenetic Factors to Colorectal Cancer Incidence and Staging Progression: A Study in South Sulawesi Population, Indonesia." Nutrition and Cancer , no. : 1-9.

Journal article
Published: 01 January 2021 in Communications in Mathematical Biology and Neuroscience
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From a psychiatric perspective, the detection of Autism Spectrum Disorders (ASD) can be seen from the differences in some parts of the brain. The availability of the four-dimensional resting-state Functional Magnetic Resonance Imaging (rs-fMRI) from Autism Brain Imaging Data Exchange I (ABIDE I) led us to reorganize it into two-dimensional data and extracted it further to create a pool of neuroimage dataset. This dataset was then augmented by shear transformation, brightness, and zoom adjustments. Resampling and normalization were also performed. Reflecting on prior studies, this classification accuracy of ASD using only 2D neuroimages should be improved. Hence, we proposed the use of transfer learning with the InceptionResNetV2 model on the augmented dataset. After freezing layer by layer, the best training, validation, and testing results were 70.22%, 57.75%, and 57.6%, respectively. We proved that the transfer learning approach was successfully outperformed the convolutional neural network (CNN) model from the previous study by up to 2.6%.

ACS Style

Nicholas Dominic; Daniel -; Tjeng Wawan Cenggoro; Arif Budiarto; Bens Pardamean. Transfer learning using inception-ResNet-v2 model to the augmented neuroimages data for autism spectrum disorder classification. Communications in Mathematical Biology and Neuroscience 2021, 2021, 1 .

AMA Style

Nicholas Dominic, Daniel -, Tjeng Wawan Cenggoro, Arif Budiarto, Bens Pardamean. Transfer learning using inception-ResNet-v2 model to the augmented neuroimages data for autism spectrum disorder classification. Communications in Mathematical Biology and Neuroscience. 2021; 2021 ():1.

Chicago/Turabian Style

Nicholas Dominic; Daniel -; Tjeng Wawan Cenggoro; Arif Budiarto; Bens Pardamean. 2021. "Transfer learning using inception-ResNet-v2 model to the augmented neuroimages data for autism spectrum disorder classification." Communications in Mathematical Biology and Neuroscience 2021, no. : 1.

Journal article
Published: 01 January 2021 in Communications in Mathematical Biology and Neuroscience
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Indonesia is the fourth highest consumer of cigarettes in the world with an estimated high cost in healthcare expenditure on tobacco-related diseases. Nonetheless, regulations on tobacco products are lax and healthcare provider involvement in aiding smoking cessation is minimal. Generally, a variety of smoking cessation aids exists and medical genetics have come into play to enhance their efficacy. A questionnaire survey was piloted to query participants on their smoking habits, past cessation attempts, opinions on factors related to smoking cessation, and reactions to information that medical genetics could provide within the context of smoking cessation. The findings showed that most participants have attempted cessation without aid. Pharmacotherapy was not used by any respondents while behavioral interventions were scarcely used. Nevertheless, 83% of participants indicated that medical genetics information would be useful in future cessation attempts and that they would consult physicians for advice.

ACS Style

Carissa I. Pardamean; James W. Baurley; Bens Pardamean. Pharmacotherapy based on medical genetics for smoking cessation. Communications in Mathematical Biology and Neuroscience 2021, 2021, 1 .

AMA Style

Carissa I. Pardamean, James W. Baurley, Bens Pardamean. Pharmacotherapy based on medical genetics for smoking cessation. Communications in Mathematical Biology and Neuroscience. 2021; 2021 ():1.

Chicago/Turabian Style

Carissa I. Pardamean; James W. Baurley; Bens Pardamean. 2021. "Pharmacotherapy based on medical genetics for smoking cessation." Communications in Mathematical Biology and Neuroscience 2021, no. : 1.

Journal article
Published: 18 November 2020 in IEEE Access
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The diagnosis of a hazard can be classified into three key domains, particularly regarding the natural hazards, non-natural hazards and social hazards. The disasters which have actually happened in West Papua require considerable attention and consideration of the Indonesian Government, despite since they have handled as much as they can to provide solutions and make people feel secure and pleasant. In this paper, using location-based social vulnerability calculation in West Papua involves the components of Information, Technology, and Communication, Food Access, Natural Disaster, Social Protection Statement, Access to Financial Services, Description of the source of household income, Number of event floods, number of earthquake disasters, COVID-19 death cases, and Number of incidents of protest which are obtained from the National Socio-Economic Survey (SUSENAS) 2017 official statistics. After employ clustering of variables around latent variables with connectivity value of 3.9400794, Dunn 0.9373, and Silhouette 0.6333. Each factor provide a sign indicating a positive or negative effect on social vulnerability and finally a location cluster will be formed based on the index obtained.

ACS Style

Rezzy Eko Caraka; Youngjo Lee; Rung Ching Chen; Toni Toharudin; Prana Ugiana Gio; Robert Kurniawan; Bens Pardamean. Cluster Around Latent Variable for Vulnerability Towards Natural Hazards, Non-Natural Hazards, Social Hazards in West Papua. IEEE Access 2020, 9, 1972 -1986.

AMA Style

Rezzy Eko Caraka, Youngjo Lee, Rung Ching Chen, Toni Toharudin, Prana Ugiana Gio, Robert Kurniawan, Bens Pardamean. Cluster Around Latent Variable for Vulnerability Towards Natural Hazards, Non-Natural Hazards, Social Hazards in West Papua. IEEE Access. 2020; 9 (99):1972-1986.

Chicago/Turabian Style

Rezzy Eko Caraka; Youngjo Lee; Rung Ching Chen; Toni Toharudin; Prana Ugiana Gio; Robert Kurniawan; Bens Pardamean. 2020. "Cluster Around Latent Variable for Vulnerability Towards Natural Hazards, Non-Natural Hazards, Social Hazards in West Papua." IEEE Access 9, no. 99: 1972-1986.

Journal article
Published: 13 August 2020 in International Journal of Online and Biomedical Engineering (iJOE)
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One of the main objectives of Electronic Health Record (EHR) is the transferability of patient data from one location to another. Many locations with scarce resources, particularly unreliable internet connectivity, face difficulties in accessing and sharing EHR data. This article presents our proposed design that utilizes Amazon Web Services (AWS) for a sharing mechanism platform among distributed healthcare organizations found in an environment with scarce resources. We proposed the use of database replication mechanism and REST (Representational State Transfer) web service to perform information exchange among health organizations and public health information systems.

ACS Style

Muhamad Fitra Kacamarga; Arif Budiarto; Bens Pardamean. A Platform for Electronic Health Record Sharing in Environments with Scarce Resource Using Cloud Computing. International Journal of Online and Biomedical Engineering (iJOE) 2020, 16, 63 -76.

AMA Style

Muhamad Fitra Kacamarga, Arif Budiarto, Bens Pardamean. A Platform for Electronic Health Record Sharing in Environments with Scarce Resource Using Cloud Computing. International Journal of Online and Biomedical Engineering (iJOE). 2020; 16 (9):63-76.

Chicago/Turabian Style

Muhamad Fitra Kacamarga; Arif Budiarto; Bens Pardamean. 2020. "A Platform for Electronic Health Record Sharing in Environments with Scarce Resource Using Cloud Computing." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 9: 63-76.

Review
Published: 30 April 2020 in Healthcare Informatics Research
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Recently, wearable device technology has gained more popularity in supporting a healthy lifestyle. Hence, researchers have begun to put significant efforts into studying the direct and indirect benefits of wearable devices for health and wellbeing. This paper summarizes recent studies on the use of consumer wearable devices to improve physical activity, mental health, and health consciousness. A thorough literature search was performed from several reputable databases, such as PubMed, Scopus, ScienceDirect, arXiv, and bioRxiv mainly using "wearable device research" as a keyword, no earlier than 2018. As a result, 25 of the most recent and relevant papers included in this review cover several topics, such as previous literature reviews (9 papers), wearable device accuracy (3 papers), self-reported data collection tools (3 papers), and wearable device intervention (10 papers). All the chosen studies are discussed based on the wearable device used, complementary data, study design, and data processing method. All these previous studies indicate that wearable devices are used either to validate their benefits for general wellbeing or for more serious medical contexts, such as cardiovascular disorders and post-stroke treatment. Despite their huge potential for adoption in clinical settings, wearable device accuracy and validity remain the key challenge to be met. Some lessons learned and future projections, such as combining traditional study design with statistical and machine learning methods, are highlighted in this paper to provide a useful overview for other researchers carrying out similar research.

ACS Style

Bens Pardamean; Haryono Soeparno; Arif Budiarto; Bharuno Mahesworo; James Baurley. Quantified Self-Using Consumer Wearable Device: Predicting Physical and Mental Health. Healthcare Informatics Research 2020, 26, 83 -92.

AMA Style

Bens Pardamean, Haryono Soeparno, Arif Budiarto, Bharuno Mahesworo, James Baurley. Quantified Self-Using Consumer Wearable Device: Predicting Physical and Mental Health. Healthcare Informatics Research. 2020; 26 (2):83-92.

Chicago/Turabian Style

Bens Pardamean; Haryono Soeparno; Arif Budiarto; Bharuno Mahesworo; James Baurley. 2020. "Quantified Self-Using Consumer Wearable Device: Predicting Physical and Mental Health." Healthcare Informatics Research 26, no. 2: 83-92.

Journal article
Published: 12 February 2020 in International Journal of Online and Biomedical Engineering (iJOE)
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Technology Acceptance Model (TAM) framework was utilized in this study. Its purpose was to determine the correlation between independent variables consisting of Perceived Ease of Use (PEU), Perceived Usefulness (PU), Attitude toward Using (AU) with dependent variable Behavioral Intention to Use (BIU). Data collection techniques were carried out by distributing questionnaires through group discussion forums. Respondents consisted of medical workers and health cadres both in Jakarta and Yogyakarta. Data were analyzed using correlation test and t-test. The results of the correlation test state that the correlation between PEU and AU is 0.30, which shows a weak correlation. Meanwhile, the correlation of PU and AU is 0.56, PEU and BIU is 0.41, and PU and BIU is 0.47, which are considered as moderate correlations. Finally, a strong correlation exists between AU and BIU. T-test results show that the effect of PU on AU is statistically significant with CI = 95%. Likewise, the effects of PEU on AU, AU towards BIU, PU towards BIU, and PEU towards BIU are significant (p < 0.05).

ACS Style

Hery Harjono Muljo; Bens Pardamean; Anzaludin Samsinga Perbangsa; Yulius Lie; Kartika Purwandari; Bharuno Mahesworo; Alam Ahmad Hidayat; Tjeng Wawan Cenggoro. TAM as a Model to Understand the Intention of Using a Mobile-based Cancer Early Detection Learning Application. International Journal of Online and Biomedical Engineering (iJOE) 2020, 16, 80 -93.

AMA Style

Hery Harjono Muljo, Bens Pardamean, Anzaludin Samsinga Perbangsa, Yulius Lie, Kartika Purwandari, Bharuno Mahesworo, Alam Ahmad Hidayat, Tjeng Wawan Cenggoro. TAM as a Model to Understand the Intention of Using a Mobile-based Cancer Early Detection Learning Application. International Journal of Online and Biomedical Engineering (iJOE). 2020; 16 (2):80-93.

Chicago/Turabian Style

Hery Harjono Muljo; Bens Pardamean; Anzaludin Samsinga Perbangsa; Yulius Lie; Kartika Purwandari; Bharuno Mahesworo; Alam Ahmad Hidayat; Tjeng Wawan Cenggoro. 2020. "TAM as a Model to Understand the Intention of Using a Mobile-based Cancer Early Detection Learning Application." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 2: 80-93.

Journal article
Published: 01 January 2020 in Communications in Mathematical Biology and Neuroscience
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As one of the most important Post-Translational Modification (PTM), phosphorylation is responsible for cellular signaling pathways and activation of enzymes. With current computational power and algorithm, it is possible to process big data, especially biomedical data, to find a complicated pattern with reasonable computation time. Computational approach for phosphorylation site prediction is more time-efficient and need fewer resources com-pared to traditional. However, the accuracy of current computational methods for phosphorylation site prediction still needs to be improved. This paper aims to create a computational method for phosphorylation site prediction with better classification performance compared to previous studies. The data used in this research to train the XGBoost models are extracted features from 2 different databases from the previous studies. The test result show that our model gave the highest accuracy on 4 out of 6 datasets. To extend our research, the XGBoost model was retrained which focused on 100 most important features from previous experiment. However, the result does not imply that it has a better result compared to our first models. As the result showing that our models gave better ac-curacy compared to the previous studies in most of the datasets, we can conclude that XGBoost model is better in predicting phosphorylation sites compared to other methods.

ACS Style

Bharuno Mahesworo; Tjeng Wawan Cenggoro; Arif Budiarto; Favorisen Rosyking Lumbanraja; Bens Pardamean. Phosphorylation site prediction using gradient tree boosting. Communications in Mathematical Biology and Neuroscience 2020, 2020, 1 .

AMA Style

Bharuno Mahesworo, Tjeng Wawan Cenggoro, Arif Budiarto, Favorisen Rosyking Lumbanraja, Bens Pardamean. Phosphorylation site prediction using gradient tree boosting. Communications in Mathematical Biology and Neuroscience. 2020; 2020 ():1.

Chicago/Turabian Style

Bharuno Mahesworo; Tjeng Wawan Cenggoro; Arif Budiarto; Favorisen Rosyking Lumbanraja; Bens Pardamean. 2020. "Phosphorylation site prediction using gradient tree boosting." Communications in Mathematical Biology and Neuroscience 2020, no. : 1.

Journal article
Published: 01 January 2020 in Communications in Mathematical Biology and Neuroscience
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A retrospective study of the abdominal aortic aneurysm (AAA) with EVAR treated patients. The third-party collected the data from twelve vascular centres in Indonesia during 2012-2017. Patient demographics and computed tomography data were evaluated with Osirix MD Software. During five years, we had 148 EVAR cases done using Endurant stent graft (Medtronic). In this paper, we perform Bayesian modelling and selection of feature selection by Boruta. Before performing the models, we will determine the selection of dependent variables start with the Age, Class, and Sex. It will get what is important to be dependent and independent. The difference between Bayesian and the classical method is the introduction of prior information in the form of probability distributions. In addition, to determine the parameters using the Bayesian method obtained from the probability statement. Parameter estimation in Bayesian is no longer a point estimate but, on the contrary, is a statistical distribution. In other words, Bayesian states that a parameter is a variable that has a distribution. Bayesian has become a popular method in modern statistical analysis. Bayesian is applied to a broad spectrum in the scientific and research fields. Bayesian data analysis involves learning from data that uses probability models for many observations and some information to be studied. In other words, analysing statistical models are by combining prior knowledge about the model or parameters of the model. In a nutshell, the simulation results obtained modelling with Bayesian-ZIP-MCMC R2 87.52 and Bayesian-Boruta R2 88.28%.

ACS Style

Rezzy Eko Caraka; Nyityasmono Tri Nugroho; Shao-Kuo Tai; Rung-Ching Chen; Toni Toharudin; Bens Pardamean. Feature importance of the aortic anatomy on endovascular aneurysm repair (EVAR) using Boruta and Bayesian MCMC. Communications in Mathematical Biology and Neuroscience 2020, 2020, 1 .

AMA Style

Rezzy Eko Caraka, Nyityasmono Tri Nugroho, Shao-Kuo Tai, Rung-Ching Chen, Toni Toharudin, Bens Pardamean. Feature importance of the aortic anatomy on endovascular aneurysm repair (EVAR) using Boruta and Bayesian MCMC. Communications in Mathematical Biology and Neuroscience. 2020; 2020 ():1.

Chicago/Turabian Style

Rezzy Eko Caraka; Nyityasmono Tri Nugroho; Shao-Kuo Tai; Rung-Ching Chen; Toni Toharudin; Bens Pardamean. 2020. "Feature importance of the aortic anatomy on endovascular aneurysm repair (EVAR) using Boruta and Bayesian MCMC." Communications in Mathematical Biology and Neuroscience 2020, no. : 1.

Journal article
Published: 07 December 2019 in Journal of Big Data
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In building management, energy optimization is one of the main concern that needs to be automated. For automation, an intelligent system needs to be developed. However, an intelligent system needs to be trained in a large dataset before it can be used reliably. In this paper, we present a transfer learning scheme to develop an intelligent system for smart building management system. Specifically, the intelligent system is able to count human inside a room, which can be utilized to adaptively adjust energy usage in a room. The transfer learning scheme employs a deep learning model that is pretrained on ImageNet dataset. To enable the human counting capability, the model is trained on a dataset specifically collected for human counting case.

ACS Style

Bens Pardamean; Hery Harjono Muljo; Tjeng Wawan Cenggoro; Bloomest Jansen Chandra; Reza Rahutomo. Using transfer learning for smart building management system. Journal of Big Data 2019, 6, 1 -12.

AMA Style

Bens Pardamean, Hery Harjono Muljo, Tjeng Wawan Cenggoro, Bloomest Jansen Chandra, Reza Rahutomo. Using transfer learning for smart building management system. Journal of Big Data. 2019; 6 (1):1-12.

Chicago/Turabian Style

Bens Pardamean; Hery Harjono Muljo; Tjeng Wawan Cenggoro; Bloomest Jansen Chandra; Reza Rahutomo. 2019. "Using transfer learning for smart building management system." Journal of Big Data 6, no. 1: 1-12.