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Meteorological parameters for PV installations in Indonesia

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

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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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Deep Learning Based Facial Emotion Recognition using Multiple Layers Model

Deep Learning Based Facial Emotion Recognition using Multipl...

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International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

作者： Lidia Sandra Yaya Heryadi Lukas Wayan Suparta Antoni Wibowo Psychology Department Krida Wacana Christian University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665499705

A Facial Emotion Recognition (FER) system is an important tool to be implemented in any psychology academic field and beyond. This paper aims to show a system of Facial Emotion Recognition that can be done using the multiple layers model of ResN et50 which is an ANN. The dataset is an array that consists of 7 different emotions represented by the numbers 0–6. The emotion included in the dataset is “anger”, “disgust”, “fear”, “happiness”, “sadness”, “shock”, and “neutrality”. This research found that the highest accuracy in the application of the model was recorded at 65% and the test was 60% to recognize facial emotion from a graphical input.

关键词： Deep learning Emotion recognition Mechatronics Automation Face recognition Electric shock Psychology

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Exploration of Technology Home-based Learning Guidance for Parents and Students during the Covid-19 Pandemic 9

Exploration of Technology Home-based Learning Guidance for P...

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9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020

作者： Suzanna, Suzanna Sasmoko, Sasmoko Lumban Gaol, Ford Oktavia, Tanty Matsuo, Tokuro Bina Nusantara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Information System Department Tokyo140-0011 Japan

ISBN: (纸本)9781728173979

With the sudden attack of the Corona Virus Disease 2019 (COVID-19), some 300 million children in the world have been forced to study at home because of the mass closure of schools that began on March 18, 2020. This has caused many obstacles in the teaching and learning process. Every effort is made to minimize the COVID-19 pandemic while ensuring the teaching and learning process is not interrupted. If the school closures too long and the child is trapped inside the house this will have a negative impact on the physical and mental health of the children. This situation makes parents become worried and look for alternative education in addition to formal schooling for their children. Of the various types of education offers that exist homeschooling or commonly known as home-based learning provides a way out for the current situation. Now children are quarantined in their homes and they will return to school once this epidemic fades. But with this disaster, parents' views on homeschooling or home-based learning can be different from before. They may still be marked if home-based learning can be a long-term education. With the existence of COVID-19, most parents might finally realize that education without formal schooling is not a crisis but an opportunity to take their children to a better future. This research was conducted by utilizing a descriptive qualitative method and within the descriptive qualitative method, the concept of document analysis would be utilized the most. It was expected that the results of this research would explore what type of technology parents could prepare for their children to use to initiate home-based learning. © 2020 IEEE.

关键词： Viruses

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Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Mietha Anditta Natashya Amartya Laurens Spits Warnars Harco Leslie Hendric Spits Warnars Arief Ramadhan Teddy Siswanto Teddy Mantoro Nurulhuda Noordin Computer Science Departement School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Departement School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Departement BINUS Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia PJJ Informatika Telkom University Bandung Indonesia Information Systems Department Trisakti University Jakarta Indonesia Faculty of Engineering and Technology Sampoerna University Jakarta Indonesia School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Malaysia

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset.

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Predicting User Preferences with XGBoost Learning to Rank Method 3

Predicting User Preferences with XGBoost Learning to Rank Me...

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3rd International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2020

作者： Qomariyah, Nunung Nurul Kazakov, Dimitar Fajar, Ahmad Nurul Bina Nusantara University Faculty of Computing and Media Computer Science Department Jakarta11480 Indonesia University of York Computer Science Department York United Kingdom Binus Graduate Program-Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9781728184067

Learning user preferences become very important as the personalization systems grow rapidly in this current era. Offering special and personal services can be an added value for the companies to maintain their customer loyalty. Building a personalized recommendation requires a good machine learning model to understand the individual preferences. Every user can be presented with a list of items sorted by its score learned from the individual preferences. So the first couple items shown will be the most liked items by the user. We can borrow the Learning to Rank algorithm from Information Retrieval to solve this problem. In this paper, we present the implementation of user preferences learning by using XGBoost Learning to Rank method in movie domain. We show the evaluation of three different approaches in Learning to Rank according to their Normalized Discounted Cumulative Gain (NDCG) score. We can conclude that in our case study, the pairwise approach appears to be the best solution to produce a personalized list of recommendation. © 2020 IEEE.

关键词： Recommender systems

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User Preference Modelling from Movie Database 7

User Preference Modelling from Movie Database

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

作者： Qomariyah, Nunung Nurul Kazakov, Dimitar Fajar, Ahmad Nurul Bina Nusantara University Faculty of Computing and Media Computer Science Department Jakarta11480 Indonesia University of York Computer Science Department York United Kingdom Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9781665404228

Film industry becomes one of the largest amongst the other economic sectors worldwide nowadays. This industry also has a significant impact in the global economic market. Many movies have been produced each year. However, some movies still fail to reach break-even points every year. Players in this industry need to think carefully when spending most of their money to make a great and successful movie in the market. Several attempts also need to be made to estimate the success performance before a movie can be released. On the audience side, there is an indicator that we can use to decide that a movie is good by looking to its ratings. The industry can use this rating systems as a factor to be considered when evaluating the past movie performances to make better movie for the next production. This study aims to predict the movie ratings and find the most important features which correlate to the ratings. We performed an experiment on IMDb dataset which contains 5,043 movie metadata on four models of machine learning, Linear Regression (LR), Decision Tree (DT), Random Forest (RF) and K-Nearest Neighbor (KNN). From the experiment, Random Forest achieves the best performance amongst the four models. © 2020 IEEE.

关键词： Decision trees

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Modeling the relationship between public transportation and traffic conditions in urban areas: A system dynamics approach

Modeling the relationship between public transportation and ...

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International Conference on Physics and Mathematics for Biological science 2019, ICOPAMBS 2019

作者： Sardjono, W. Selviyanti, E. Perdana, W.G. Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Health Department Politeknik Negeri Jember Jember Jawa Timur68124 Indonesia Post Graduate Program of Environmental Science School of Environmental Science University of Indonesia Jakarta11480 Indonesia

The goals of the paper were to describe were and find the relations between numbers of available public transportation and traffic congestion and other variables that can reduce traffic congestion in Jakarta. The data that used in the simulation were provided by DKI Jakarta Provincial Statistics Agency from view years ago. To analyze the problem, System Dynamics are used to simulate the condition in the future using the models created based on relations between several variables. The results of the analysis shows that numbers of available public transportation cannot reduce traffic congestion if the numbers of private transportation weren't decreased. It can be concluded that government must force their citizen to reduce the number of private transportation by increasing the inflation supported by increasing numbers of available public transportation to accommodate deficit in transportation while building new roads to accommodate transportation growth in the future. © Published under licence by IOP Publishing Ltd.

关键词： Traffic congestion

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Mobile application for the futsal sports community in Jakarta

Mobile application for the futsal sports community in Jakart...

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Artificial Intelligence and Smart Systems (ICAIS), International Conference on

作者： Farel Darari Deksano Dimas Raka Erfiandhi Anggy Cahya Prasetya Aditya Satria Nagara Patmuryanto Harco Leslie Hendric Spits Warnars School Of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program—Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728195377

ISBN: (纸本)9781728195384

The rapid development of technology makes many changes that occur in the community in carrying out daily activities, one of which is the use of online-based applications to support community activities in Jakarta. This study aims to build applications to support community activities in the field of futsal sport, namely ordering Android-based sports arenas. This ordering application consists of Home, Schedule, sparring, profile, info, and ordering. This application makes it easier for people to find information about the sports arena and make it easier to order sports fields anytime, anywhere, so they can increase profits for the sports arena business. This mobile application was applied with android studio and using MySQL for the database. Hopefully, creating this mobile application will reduce the number the crime rate committed by youth and expand their friendship not only around their house or school but for future development it is possible to run a competition that can be held at the provincial level, or at the national level and possibly even at the South East Nation country (ASEAN) level which involving several ASEAN countries.

关键词： computer science Schedules Databases Mobile applications Artificial intelligence Sports Business

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Detepet Mobile Application for Pet Tracking

Detepet Mobile Application for Pet Tracking

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Brian Wijaya Aqraldo Jessen Yuliet Sentoman Deven Markos Harco Leslie Hendric Spits Warnars School of Information System Bina Nusantara University Jakarta Indonesia BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728185194

ISBN: (纸本)9781728185200

We have often heard of cases of loss of animals in the world, the owners of these animals are very troubled in looking for lost animals, so often when the pet is lost, the owner leaves it or makes the news of the competition for who can find it. We strive to help these pet owners easily detect the presence of pets they have through a mobile application that we make, namely Detepet that can track all the pets you have, so you are not afraid of losing your pet. In this case, the user should register their pet and the tool GPS necklace will be attached to the pet and the pet will be under monitoring of the systems.

关键词： Heart rate Animals Tools Mobile applications Registers Informatics Monitoring

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