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Genome data mining approach to identify potential protein in crop plants

AIP Conference Proceedings 2024年第1期3026卷

作者： Joko Pebrianto Trinugroho Faisal Asadi Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

There is a need to produce more crop plants to meet the future global demand. However, the climate change has affected the global crop yield. Consequently, finding an alternative approach to improve crop yield becomes essential. The development of sequencing techniques, as well as information technologies, have enabled us to perform genome data mining. Using genome data mining approach, it is possible to identify or discover a protein which has a particular characteristic. This study aims to identify a protein, which could potentially improve crop yield, using genome data mining approach. D1 protein was used as the target, as this protein is highly involved in photosynthesis. Then, protein sequences of various crop plants were collected from biological database. After conducting data trimming and filtering, sequence analysis was performed. The analysis was used to construct phylogenetic tree and create a 3D protein model. Sequence analysis displayed variation in amino acid sequence in D1 protein. Protein modelling located the variations, which scattered within D1 protein. Furthermore, we highlighted the amino acid residues that are the targets for genetic engineering. The research findings may provide a reference to improve crop production through genome mining approach.

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Distraction Detection in Driving Using Pose Extraction and Machine Learning Techniques

Distraction Detection in Driving Using Pose Extraction and M...

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International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Fitra Abdurrachman Bachtiar Issa Arwani Ridwan Aji Budi Prasetyo Gusti Pangestu Riza Setiawan Soetedjo Al Ravíe Muthiar Mahesa Informatics Engineering Department Brawijaya University Malang Indonesia Information System Department Brawijaya University Malang Indonesia Psychology Department Brawijaya University Malang Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia

There are a lot of technologies have been implemented in the modern cars these days, ranging from preventive braking system to driving assistance. It is believe that equipping car with modern technology would enhance safety. However, there are other aspects need to be considered in safety driving, that is human factor. Human factors are believed have high contribution in road accidents. Human factors such as emotional control and distraction may leads to dangerous driving behaviours. This study investigates the driver pose distraction. The distracted driver pose detected through pose detection using landmark feature extraction. The dataset used in this study is State Farm Distracted Driving Detection which is a secondary dataset. The extracted driver pose are in numeric form and used as the input for the classification model to detect ten kinds of driving distraction ranging from safety driving to talking to passenger. Four classifiers used to detect distracted driver are CatBoost, Decision Tress, Random Forest and SVM. The model performance evaluated using Precision, Recall, Accuracy, and F1-score. Furthermore, prediction time recorded to determine the best model to detect driver distraction. The results shows that CatBoost model outperformed all other model with F1-score and prediction time of 0.899 and 0.014 second. Random Forest model performance is the second highest compared to four other with F1-score and prediction time of 0.881 and 0.028 seconds. CatBoost model is the best model even though Cat Boost model execution time is not the highest and the model performance is not significantly different compared to Random Forest.

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NLP Text Classification for COVID-19 Automatic Detection from Radiology Report in Indonesian Language

NLP Text Classification for COVID-19 Automatic Detection fro...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Nunung Nurul Qomariyah Ardelia Shaula Araminta Raphael Reynaldi Monique Senjaya Sri Dhuny Atas Asri Dimitar Kazakov Computer Science Department School of Computing and Creative Arts Bina Nusantara University Jakarta Indonesia Pulmonology Department Head of Functional Medical Staff Pasar Minggu Regional Hospital Jakarta Indonesia Computer Science Department University of York United Kingdom

Radiology is used as an important assessment for patients with pulmonary disease. The radiology images are usually accompanied by a written report from a radiologist to be passed to the other referring physicians. These radiology reports are written in a natural language where they can have different systematic structures based on the language used. In our study, the radiology reports were collected from an Indonesian hospital and written in Bahasa Indonesia. We performed an automatic text classification to differentiate the information written in the radiology reports into two classes, COVID-19 and non COVID-19. To find the best model, we evaluated several embedding techniques available for Bahasa and five Machine Learning (ML) models, namely (1) XGBoost, (2) fastText, (3) LSTM, (4) Bi-LSTM and (5) IndoBERT. The result shows that IndoBERT outperformed the others with an accuracy of 98%. In terms of training speed, the shallow neural network architecture implemented with the fastText library can train the model in under one second and still result in a reasonably good accuracy of 86%.

关键词： COVID-19 Training Seminars Systematics Pulmonary diseases Text categorization Neural networks

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Rectangular heatsink temperature simulation based on two-dimensional diffusion equation

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AIP Conference Proceedings 2023年第1期2975卷

作者： Wilsen Vesakha Lymantama Viska Noviantri Azani Cempaka Sari Mathematics Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

A heatsink is a cooling device on an electrical component that protects it from overheating, which can cause damage. As a cooling device, heatsink performance will be interesting to discuss by analyzing its temperature distribution. A two-dimensional unsteady state diffusion equation is applied here to model this distribution since the physical situation on the heatsink satisfied heat conduction. The model is solved numerically by a forward time central space scheme. Some simulations completed this scheme for heatsink with a rectangular fin to see the temperature variation over time. The chopper, aluminum, and iron materials are used here to see the thermal diffusivity effect on the temperature distribution. The results show that a copper heatsink performs better than the others. Furthermore, the temperature simulation results use to calculate thermal resistance to measure the quality of the heatsink. It shows that the combination of fins number, dimensions of the heatsink, and heat source affected their thermal resistance. The thermal resistance is reciprocal to the fins number and height but proportional to the heat source surface temperature, which has been validated with the theoretical concept and previous research. In the end, this study has a conclusion about the suitable material that can optimize heat dissipation based on its thermal resistance.

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Analysis Implementation of Chatbots to Increase Knowledge of Stunting Prevention in Indonesian Society with Bibliometric

Analysis Implementation of Chatbots to Increase Knowledge of...

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International Conference on Information Management and Technology (ICIMTech)

作者： Indrajani Sutedja Lutfi Handayani Maryuni Hendry Mohammad Reza Faisal Information Systems Department School of Information Sytems Bina Nusantara University Jakarta Indonesia Faculty of Nursing and Midwifery Midwifery Study Program Binawan University Jakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Salatiga Indonesia Department of Computer Science FMIPA Lambung Mangkurat University Banjarmasin Indonesia

ISBN: (数字)9798350390025

ISBN: (纸本)9798350390032

The healthcare industry uses AI, because it is more efficient. In Indonesia, the accuracy of measurements and transmission of children's growth and development is often wrong. Many small hospitals usually don't have length measuring equipment, so the results are inaccurate. This research aims to determine the effectiveness of the stunting prevention program in Indonesia using an information system. The methodology used is a qualitative method, to conduct subjective research and analysis. The results of the research are to improve the website/mobile application information system which can display a child's growth and development history and simple educational information related to nutrition. Digital recording methods can speed up the process of updating data with a central database in real time. The value of this research is to reach the public to utilize technology and obtain personalized and interactive information directly to individuals. The theoretical implications of this research focus on information dissemination and understanding how chatbots influence knowledge acquisition and behavior change in the context of stunting prevention can contribute to advancing these theories in the field of public health. Managerial implications can provide cost effectiveness as Chatbots offer potentially cost-effective solutions and data-driven insights where managers can leverage chatbot analytics.

关键词： Prevention and mitigation Scalability Bibliometrics Refining Chatbots Real-time systems Stakeholders Artificial intelligence Sustainable development Research and development

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Autonomous car using CNN deep learning algorithm 2

Autonomous car using CNN deep learning algorithm

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2nd Annual Conference of science and Technology, ANCOSET 2020

作者： Sonata, I. Heryadi, Y. Lukas, L. Wibowo, A. Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Jl. Kyai H. Syahdan No.9 Jakarta11480 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jl Jend. Sudirman No.51 Jakarta12930 Indonesia

Autonomous cars have become an interesting discussion in recent years. Several major automotive industries such as Tesla, GM and Nissan are trying to become pioneers in autonomous car technology. Giant technology companies such as Google Waymo, Baidu and Aptiv also developing autonomous car technology. Several technological approaches are carried out in implementing autonomous cars for recognizing surrounding situations, such as radar, lidar, sonar, GPS, and odometry. An automatic control system is used to control navigation based on the data obtained from these sensors. This paper will discuss the use of CNN deep learning algorithm for recognizing the surrounding environment in creating the automatic navigation required by autonomous cars. The system designed will create and learn the data set that will be taken in advance and the learning outcomes will be implemented in an open simulation system. This simulation shows high accuracy in learning to navigate the autonomous car by observing the surrounding environment. © Published under licence by IOP Publishing Ltd.

关键词： Autonomous vehicles

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The Role of Big Data in Enhancing Student's Sustainable Development Awareness: A Case Study in Higher Education 2020

The Role of Big Data in Enhancing Student's Sustainable Deve...

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2nd International Conference on Big Data Engineering and Technology, BDET 2020

作者： Pane, Murty Magda Siregar, Christian Lake, Silverius C.J.M. Character Building Development Center Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia Character Building Development Center Mass Communication Program Communication Dept. Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450376839

This study objective is to find the general picture of the knowledge, attitude and behavior of students for sustainable development. It used the quantitative method with 160 students as the research subjects with the data collection technique of questionnaire distribution. The questionnaires are valid (the corrected item total correlations for knowledge, attitudes and behavior are: 0.745, 0.878 and 0.726) and reliable (α for knowledge, attitudes and behavior are: 0.985, 0.978 and 0.959). The positive nuances questionnaire's results are analyzed through a correlative analysis. The results showed scale 4 were chosen most for knowledge and attitude (41.40% and 42.93%), only in behavior the scale 3 was the most chosen (34.63%). The results concluded that the students tend to have positive knowledge, attitude and behavior towards the sustainable development, and the results will give strong support the sustainable future for human security. The results were connected with the big data, especially in social media and instant messaging where they can learn and get educated about sustainable development. © 2020 ACM.

关键词： Sustainable development

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The Contribution of Assessment Platform Technology to Promote Teacher's Work in schools 6

The Contribution of Assessment Platform Technology to Promot...

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6th International Conference on Interactive Digital Media, ICIDM 2020

作者： Zamahsari, Gamal Kusuma Putikadyanto, Agus Purnomo Ahmad Maulana, Fairuz Iqbal Bina Nusantara University Faculty of Economics and Communication Communication Science Department Jakarta11480 Indonesia Institute of Islamic Religion Madura Indonesian Language Education Study Program Pamekasan69371 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728149288

This study examines the efficiency of summative assessment in schools utilizing the *** assessment platform. The objectives of this study were (1) to describe staff efficiency on summative assessment using *** in schools, and (2) to describe the time efficiency on summative assessment using *** in schools. This study uses a qualitative design. The location of this research is Junior High school 3 Malang. Data were collected through observation, document study, and interviews. Interviews were conducted with the vice-principal of the curriculum field. Investigation of validity data used triangulation, with additional interviews to the curriculum team and teachers at the school. Summative assessments using the *** platform show the more efficient in terms of staff's work as much as 17% compared to conventional summative assessment and a time efficiency of 44% compared to conventional assessments. The use of technology saves time from the planning, processing, and reporting stages of the assessment. The greatest efficiency is in the summative assessment processing stage because the costs of correcting or scanning student work, changing grades, and analyzing question items are not done manually. The use of technology with the *** platform for summative assessment in schools can be an alternative solution to promote teacher work. © 2020 IEEE.

关键词： Curricula

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Environmental friendly "jambur" building relevance in Karo Batak communities and gotong-royong/sisampat-sampati communities in Covid-19 pandemics 5

Environmental friendly "jambur" building relevance in Karo B...

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5th International Conference on Climate Change 2020, ICCC 2020

作者： Tarigan, N.P. Character Building Development Center Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Universitas Pelita Harapan Doctor of Research in Management in Education Leadership Program Student Jl. Garnisun Dalam No. 8 Karet Semanggi Jakarta12930 Indonesia Gerakan Peduli Disabilitas Dan Lepra Indonesia [GPDLI Indonesia

It can be an exciting and positive thing to realize an Indonesian-style building in a location from certain ethnic groups like the Karo Batak. Notably, suppose they collaborated with social empowerment where they live so that the diversity of Indonesia's ethnic groups will be more colorful in cooperating or working together or in the "Sisampat-sampati"in Karo Language. In that case, this can be built by creating approaches for developing the character of ethnic groups and in person. Developing the character of a person or ethnic group in Indonesia will make the Indonesian people better in the future, because in principle, these characters are formed from many national cultures, such as respect for nature and others. Indonesia is very friendly or likes to communicate and interact, so that the use of social media in Indonesia can be said to be very broad and the third largest for several types of social media. However, whether this has excellent implications for increasing the quality of life or significant quality of life is still a big question especially Sustainable Development Goals (SDG) number 13, climate change. However, with a hypothesis that mutual character building is the right answer, the researcher is pleased to provide input from a broader view of character development itself and architecture. This will undoubtedly bring significant changes to the nation in the future. This paper is a conceptual article or literature study and input from several journals. © Published under licence by IOP Publishing Ltd.

关键词： Climate change

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Systematic literature review: Accelerate the rice production for global food security

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AIP Conference Proceedings 2023年第1期2594卷

作者： N. Dominic T. W. Cenggoro B. Pardamean Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

By 2050, about 70% of extra food production is needed to feed the world's population. As a majority staple food, the expansion of rice production should be accelerated. This systematic literature review aims to discover the factors that influence rice yields through a methodology that is partitioned into four main stages, i.e., query entry into multiple database sources, article title filtering, abstract filtering, and final article selection. The results show that genetics, irrigation system management, and farmers’ long-evolved local knowledge or experiences are the three big factors that elevate the rice production rates. Nevertheless, global warming is a serious challenge that should be deeply considered due to its great impact on reducing rice yields by up to 14.5%. Thus, the development of genetically modified rice varieties needs to be escalated while still maintaining other exogenous factors. This study contributes to providing a broader perspective for decision-makers and other relevant experts to accelerate rice production to achieve global food security.

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