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Statistical analysis and data visualization of Indonesia and Malaysia SARS Cov-2 metadata

AIP Conference Proceedings 2023年第1期2594卷

作者： D. Sudigyo A. Budiarto B. Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

SARS CoV-2 is a fascinating topic to investigate, especially in Indonesia and Malaysia, which share similar racial demographics. However, statistical analysis of information on the SARS CoV-2 from a database, especially GISAID, does not contain specific customizations related to virus comparisons between selected countries. Therefore, the researchers conducted statistical analysis and data visualization using the Python programming language to describe and investigate SARS CoV-2 Indonesia and Malaysia from the GISAID database. SARS CoV-2 metadata from Indonesia (N=117) and Malaysia (N=250), which were gathered during 2020, were compared. This comparison was aimed to investigate the discrepancies of COVID-19 cases in closely related populations. Firstly, data visualization was conducted using the Python Matplotlib library to create bar charts for clades and mutation comparison. Additionally, a series of boxplots were generated to show age discrepancies stratified by gender. Furthermore, the statistical tests showed that only the dominant Malaysian (G and O) clades were found to be significantly different compared to Indonesian cases (p-value=0.016). The proportion of two major mutations (G614D and NSP12 P323L) were also significantly different in the two countries caused by the dominant clade differences (p-value=0.007). Lastly, the differences in the age distribution of COVID-19 cases between the two countries were significant only in the male group (p-value=0.017).

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Jakarta website information about self isolation using QGIS

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AIP Conference Proceedings 2023年第1期2734卷

作者： Anisa Rahmawati Muhammad Rayhan Brata Muhammad Rosyad Syamil Samsul Arifin Computer Science. School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Statistics Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

The increase in Covid-19 is increasingly significant, especially in Jakarta. The increase in Covid-19 cases in Jakarta today touched 849,843 new cases as of August 30, 2021. The high increase in Covid-19 cases is due to the presence of this new variant of the Covid-19 virus, namely the lambda variant which is more deadly than the previous Covid-19 virus. Based on the data on the increase in the Covid-19 virus, a website was created regarding hotels that have self-isolation facilities. The purpose of this website is to help people who need a place to self-isolate. Researchers took 30 samples of hotels spread across Jakarta, and Tangerang and have self-isolation facilities, making this website using QGIS technology which has Geographic Information System technology.

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The evaluation of android-based application on tuition fee for elementary school using user experience questionnaire

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AIP Conference Proceedings 2024年第1期2927卷

作者： Marcel Weisang R. M. Rendra Adikara Richard Tandy Japutra Mirza Ramadhani Department of Computer Science Bina Nusantara University Malang Indonesia

This research is aimed to evaluate the interface and user experience of wadahnya and then give suggestions for the system interface. Wadahnya is a Tuition Payment Application that aims to support payment transaction activities in the school Administration section. Many schools still make tuition payments using manual processes, resulting in data inconsistency. Because tuition Payment transactions are stored in the manual form written in big books, many schools have difficulty finding information on student data who have or have not made payments, and schools have a problem making precise and accurate reports. The user Experience Questionnaire (UEQ) method is our primary way to carry out the evaluation. The advantages of the UEQ are attractiveness, pragmatic quality, and hedonic quality. In addition, An Excel-formatted data analysis tool was provided to facilitate the measurement of the UEQ. The evaluation was conducted on 49 respondents. UEQ ratings are very satisfying. The Attractiveness value is 1.36, Perspicuity value is 1.43, efficiency value is 1.49, Dependability value is 1.31, stimulation value is 1.29, and novelty value is 0.46. The analysis results of pragmatic quality and hedonic quality are also well evaluated, with mean values of 1.41 and 0.87, respectively. Analysis using UEQ shows that the user experience can be said to be good, with an average value above one except for novelty. This research can be used as a recommendation for designing a new program by improving other aspects.

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Implementation of Neuroresearch Method in Self Assessment Services Development: BeeBest E-Application

Implementation of Neuroresearch Method in Self Assessment Se...

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International Conference on ICT For Smart Society (ICISS)

作者： Sasmoko Yasinta Indrianti Sonya Rapinta Manalu Lukas Tanto Kurniawan Abu Yazid Abu Bakar Primary Teacher Education Department Faculty of Humanities Research Interest Group of Educational Technology Bina Nusantara University Jakarta Indonesia Entrepreneurship Department Universitas Agung Podomoro Jakarta Entrepreneurship Department Universitas Agung Podomoro Research Interest Group of Educational Technology Jakarta Indonesia Mobile application & Technology School of Computer Science Research Interest Group of Educational Technology Bina Nusantara University Jakarta Indonesia Mobile Application and Technology School of Computer Science Research Interest Group of Educational Technology Bina Nusantara University Jakarta Indonesia Faculty of Education Universiti Kebangsaan Malaysia Malaysia

The neuroresearch method is a combination of qualitative and quantitative research. Neuroresearch in this study is applied to develop the BeeBest application which is based on a fundamental concept where the progress and development of a nation is based on the importance of human capital. Therefore, various efforts have been made to improve the quality of human capital itself, especially quality work life (QWL). The BeeBest application is a self-assessment-based application that is useful for increasing the QWL of its users. The research method used is the Neuroresearch Method which consists of 3 (three) stages, namely Exploratory, Explanatory, and Confirmatory Research. The results of the research show the stages of Neuroresearch which are the basis for the development of BeeBest Apps. BeeBest Apps are expected to be able to contribute to increasing the capacity and competency of human capital through self-assessment and self-intervention in a sustainable manner. QWL can be built when a person is able to see and photograph his own capacity so that he can use and utilize it productively and optimally as an effort to make a valuable contribution to his life.

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A comparison of noisy photoplethysmography (PPG) signals using heartpy with MAX30102 and pulse sensor

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AIP Conference Proceedings 2023年第1期2594卷

作者： H. Robertus C. L. Hendiarta A. A. S. Gunawan Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The heart rate is one of the important pieces of information for healthcare equipment. The patient’s heart rate can be monitored using wearable devices to provide a system for detecting heart attacks early. The research represents the implementation of the Internet of Things (IoT) and cloud computing on the heart rate estimation system. The Internet of Things (IoT) used is ESP32 PICO D4 as a microchip of LilyGo T-Wristband with the MAX30102 heart rate module. The research aims to develop a heart rate sensor for accurate health diagnostic applications and evaluate the accuracy of a health diagnostic application using a heart rate sensor by focusing on creating a heart rate estimation system. This evaluation is done by comparing with another heart rate sensor which is Pulse Sensor. The percentage of RMSE of the two sensors is calculated from two subjects. The values are 16.9% and 4.2%, respectively. The results show that the performance of the two heart rate sensors is not much different.

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Oil Palm Fruits Dataset in Plantations for Harvest Estimation Using Digital Census and Smartphone

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Scientific data 2025年第1期12卷 972页

作者： Martinus Grady Naftali Gregory Hugo Muhammad Reza Azhar Priyadi Muhammad Asrol Ditdit Nugeraha Utama Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta 10480 Indonesia. Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta 10480 Indonesia. Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia.

This article presents a dataset of oil palm Fresh Fruit Bunches (FFBs) images from commercial plantations in Central Kalimantan, Indonesia, focusing on five maturity stages: Unripe, Underripe, Ripe, Flower, and Abnormal. The data collection involved smartphone video recordings of unharvested trees from multiple angles under varying conditions. Video frames were extracted and expertly annotated using computer Vision Annotation Tool (CVAT), with annotations exported in Common Objects in Context (COCO) format suitable for object detection tasks. It has 10,207 images in its training set, 2,896 in the validation set, and 1,400 in the test set, which are supplemented using data augmentation to handle class imbalance and increase variation. These images have real-world complications arising from partial visibility, low contrast, occlusion, and blurriness. It forms the basis that will support the development of deep learning models for detection and classification of FFB, particularly for monitoring of harvest times, yield prediction, and optimization of resources in plantation operations.

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A prototype of Baby Monitoring Use Raspberry Pi 7

A prototype of Baby Monitoring Use Raspberry Pi

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Rudyansyah, Aldy Hendric Spits Warnars, Harco Leslie Lumban Gaol, Ford Matsuo, Tokuro Bina Nusantara University BINUS Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Graduate School of Industrial Technology Tokyo Japan

ISBN: (纸本)9781665404228

The security system in monitoring the room or something suspicious activity that can cause crimes in the field of information and technology as in private homes is indispensable. Aims to keep valuables from theft and loved ones like babies from kidnapping or reducing the risk of an accident in an unguarded infant activity. The use of CCTV still has constraints because some functions are still done manually such as should always move the record of the CCTV data every day to different memory so that there is waste in using memory. Moreover, the position of the camera can not be adjusted freely in the placement so that it can easily be destroyed by irresponsible people, and also ordinary CCTV needs electricity that is considerable in its use. This research is done to improve and facilitate the process of monitoring of baby activity and the room where the baby is called sleep or rest, all monitoring activities can be done using only a Web browser that can be accessed by a smartphone or desktop. The monitoring system is created using a program called RPi Cam that is installed on the Raspberry Pi with a Raspberry Camera module as a monitoring camera and a DHT22 sensor module as a room temperature monitor. © 2020 IEEE.

关键词： Security systems

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K-Means Clustering Model to Discriminate Copper-Resistant Bacteria as Bioremediation Agents

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Procedia computer science 2021年 179卷 804-812页

作者： Ika Nurlaila Wahyu Irawati Kartika Purwandari Bens Pardamean Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Department of Biology Education Faculty of Education Pelita Harapan University Tangerang Indonesia 15811 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Copper (Cu) has been excessively used for some valuable commodities and this creates environmental problems. The inorganic element becomes toxic when presents beyond the recommended tolerated concentration. Bacterial-based remediation is seen to be an excellent tool to overcome it as it reduces the copper contamination without yielding any other forms of contamination. There are some pivotal properties in the bacteria render them being considered as bioremediation agents against coppers contamination, namely bioaccumulation and biosorption. In the present study, we question if these bacteria could be clustered into a strong and representative proximity according to their functional properties. Mostly, bacteria are grouped based on their genetic profiles derived from the 16S rRNA sequencing. We propose that our K-Means clustering model can be employed to identify genetically-unlabelled bacteria. But first, a prominent reference should be developed and we are in this phase. We figured out the K-Means clustering model do not pull the same-genus bacteria into the same cluster. Instead, the model gathers into a proximity those isolates with similarity on a functional characteristic termed minimum inhibitory concentration (MIC), regardless their origins and their hierarchy in taxonomy.

关键词： Copper-Resistant Bacteria K-Means Minimum Inhibitory Concentration

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Meteorological parameters for PV installations in Indonesia

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AIP Conference Proceedings 2024年第1期3026卷

作者： Joko Pebrianto Trinugroho Alam Ahmad Hidayat Reza Rahutomo Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Many countries are still dependent on fossil fuels as their primary energy supply. However, there is a growing concern about the sustainability and the environmental issue of fossil fuels. Therefore, it is important to utilize renewable resources as the energy supply, such as solar energy. As a country with a tropical climate, Indonesia has a great potential to use solar energy, due to the abundance of sunlight exposure. The present study aims to analyze several meteorological parameters for the installation of photovoltaic (PV) technology in Jakarta, Indonesia. The meteorological data provided by the Ministry of Environment and Forestry, Indonesia from 2008-2021 were used at three different locations in Jakarta. Data visualizations were used to show the difference between each variable in different locations. In addition, the statistical difference between the variables in the three locations was also examined using the Mann-Whitney U test. The test shows that all parameters are evenly distributed in the three locations except for a moderate difference in air temperature in the two locations. Furthermore, the monthly analysis of the parameters also indicates that the dry season, especially from August to September, would be the optimal time to utilize PV technology. Hence, this study would be useful to give preliminary insight regarding a site-specified assessment of PV plants in Jakarta based on local meteorological data.

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The development of a matchmaking system through the use of reinforcement learning for pet match (PATCH)

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AIP Conference Proceedings 2025年第1期3250卷

作者： Radisa Hussein Rachmadi Maria Seraphina Astriani Computer Science Department School of Computing and Creative Arts Bina Nusantara University Jakarta Indonesia

Pets are sometimes considered as an extended family; they deserve all the love and attention just as they show to their owners. During the Covid-19 pandemic, there was a surge in pet adoptions as research shows that pets can help with depression and loneliness. Now that the pandemic has slowly faded, and people are coming out of their homes more often, pets are often left neglected which is why it is needed to create a solution to cater to connecting pets for either breeding purposes or playdate purposes. The authors decided to develop a mobile application that will serve as a platform to connect pet owners through a matchmaking style application integrated with reinforcement machine learning and the scope of this paper focused on the pet matchmaking. The solution is developed by using Neural Networks and Proximal Policy Optimization (PPO) to predict user’s best possible matches based on the user’s swipes. The results show an improvement in better objective matches when compared to a random matching algorithm.

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