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7th International Conference on Cyber and IT Service Management, CITSM 2019

作者： Harvy, Ikrar Matitaputty, Gilbert Alessandro Girsang, Abba Suganda Michael, Steve Isa, Sani Muhamad BINUS Graduate Program-Master of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9781728129099

Data is the part that represents the evidence in presenting the state of the surrounding environment, obtained through research in the form of numbers, sources or scales. with data, conditions can be measured to produce the best solution. GIS Bookstore is one company that needs data every month to be analyzed. However, GIS Bookstore has constraints in processing large data with increasing time. for example GIS bookstore has problems in analyzing bestsellers because of the increasing number of authors and book publishers who work together. In this study, GIS Bookstore found a solution by implementing business intelligence that plays a role in the processing of raw data in large amounts of data into well-structured data information, the results are collected and processed in a data warehouse scheme. Targets stored in the data warehouse are data that will be processed based on the model design method (ERD) and star schema. This paper discusses the GIS Bookstore data warehouse with the aim of analyzing the sales of most books based on a certain time period. The method used in retrieving data uses Pentaho data integration tools, MySQL workbench, report designer, bi server and workbench schema. © 2019 IEEE.

关键词： Data warehouses

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Data annotation system for intelligent energy conservator in smart building 3

Data annotation system for intelligent energy conservator in...

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3rd International Conference on Eco Engineering Development, ICEED 2019

作者： Pardamean, Bens Cenggoro, Tjeng Wawan Chandra, Bloomest Jansen Rahutomo, Reza Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department College of Letters and Science University of Wisconsin MadisonWI53706 United States Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

The concept of smart building includes the optimization of energy usage in a building. One of the possible solutions for this is to adaptively adjust appliances utilization according to activity level in the building. Thus, an intelligent activity estimation system needs to be developed. However, massive annotated dataset is necessary to train the system. Therefore, we propose a system that enables rapid data annotation to collect the massive dataset. With the proposed system, an image can be annotated within 4.8 seconds in average. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Historic preservation

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Parameter Optimization of Support Vector Regression Using Harris Hawks Optimization

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Procedia computer science 2021年 179卷 17-24页

作者： I Nyoman Setiawan Robert Kurniawan Budi Yuniarto Rezzy Eko Caraka Bens Pardamean Computational Statistics Department Polytechnic of Statistics - STIS Jakarta 13330 Indonesia Department of Information Management College of Informatics Chaoyang University of Technology Taiwan (ROC) Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia 11530 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia. 11530.

Support Vector Regression (SVR) is often used in forecasting. Adjustment of parameters in the SVR affects the results of forecasting. This study aims to analyze the SVR method that is optimized using Harris Hawks Optimization (HHO), hereinafter referred to as HHO-SVR. The HHO-SVR was evaluated using five benchmark datasets to determine the performance of this method. The HHO process is also compared based on the type of kernel and other metaheuristic algorithms. The results showed that the HHO-SVR has almost the same performance as other methods but is less efficient in terms of time. In addition, the type of kernel also affects the process and results.

关键词： SVR harris hawks optimization parameter optimization kernel forecasting

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Clustering Steam User Behavior Data using K-Prototypes Algorithm

Clustering Steam User Behavior Data using K-Prototypes Algor...

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International Conference on Engineering, Technology and Innovative Researches 2019, ICETIR 2019

作者： Ranti, Kiefer Stefano Salim, Kelvin Girsang, Abba Suganda Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

The use of user telemetry to gather player behavioral data on video games can be very beneficial to game developers with a certain business model. With the help of user telemetry in game development, it can provide access to data on user behavior from installed game clients platform such as Steam. These behavioral data can be used to find out the Steam user behavioral patterns on playtime distributions that can be studied by developers in order to have a deeper understanding of the behaviors of their players. In this study, the data are clustered using the k-prototypes algorithm, a combination of k-means and k-modes algorithm that can be used to cluster mixed attributes. The result shows that the clusters represent the types and preferences of the players. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Software design

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Song Recommendation System Using Collaborative Filtering Methods 19

Song Recommendation System Using Collaborative Filtering Met...

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Proceedings of the 3rd International Conference on Digital Technology in Education

作者： Abba Suganda Girsang Antoni Wibowo Edwin Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450372206

Currently, digital online music increase significantly, both in terms of content and users. Increasing the number of digital music content every month conduce a lot of song catalog data and becoming unstructured and making it difficult for users to choose the songs they want to listen to. To make it easier for users to optimize a large number of subscribed music catalogs, a user-centric music recommendation system is needed that allows users to be able to manage catalogs of digital music content according to their needs. This study examines how to implement song recommendation system using collaborative filtering method in digital online music. This study uses 20,000 users, 6,000 songs and 470,000 transactions rating. Through those research, it is discovered that user-based collaborative technique that could make one system for clients will gather those playlist they really want to hear.

关键词： digital music recommendation playlist generation Collaborative filtering

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Slice-Fusion: Reducing False Positives in Liver Tumor Detection for Mask R-CNN

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IEEE/ACM Transactions on Computational Biology and Bioinformatics 2023年第5期20卷 3267-3277页

作者： Tu, Deng-Yao Lin, Peng-Chan Chou, Hsin-Hung Shen, Meng-Ru Hsieh, Sun-Yuan National Cheng Kung University Master Degree Program on Artificial Intelligence Tainan City70101 Taiwan National Cheng Kung University Institute of Medical Informatics Department of Oncology Department of Genomic Medicine National Cheng Kung University Hospital College of Medicine Department of Computer Science and Information Engineering Tainan City70101 Taiwan National Chi Nan University Department of Computer Science and Information Engineering Nantou County54561 Taiwan National Cheng Kung University Graduate Institute of Clinical Medicine Department of Obstetrics and Gynecology Department of Pharmacology National Cheng Kung University Hospital College of Medicine Tainan City70101 Taiwan National Cheng Kung University Institute of Medical Information Institute of Manufacturing Information and Systems Center for Innovative FinTech Business Models International Center for the Scientific Development of Shrimp Aquaculture Department of Computer Science and Information Engineering Tainan City70101 Taiwan

Automatic liver tumor detection from computed tomography (CT) makes clinical examinations more accurate. However, deep learning-based detection algorithms are characterized by high sensitivity and low precision, which hinders diagnosis given that false-positive tumors must first be identified and excluded. These false positives arise because detection models incorrectly identify partial volume artifacts as lesions, which in turn stems from the inability to learn the perihepatic structure from a global perspective. To overcome this limitation, we propose a novel slice-fusion method in which mining the global structural relationship between the tissues in the target CT slices and fusing the features of adjacent slices according to the importance of the tissues. Furthermore, we design a new network based on our slice-fusion method and Mask R-CNN detection model, called Pinpoint-Net. We evaluated proposed model on the Liver Tumor Segmentation Challenge (LiTS) dataset and our liver metastases dataset. Experiments demonstrated that our slice-fusion method not only enhance tumor detection ability via reducing the number of false-positive tumors smaller than 10mm, but also improve segmentation performance. Without bells and whistles, a single Pinpoint-Net showed outstanding performance in liver tumor detection and segmentation on LiTS test dataset compared with other state-of-the-art models. © 2004-2012 IEEE.

关键词： Tumors

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Aggregating Structural Features for Computational Analysis of Mutations in BRCT Domains of BRCA1 Protein

Aggregating Structural Features for Computational Analysis o...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Alam Ahmad Hidayat Rudi Nirwantono Mahmud Isnan Joko Pebrianto Trinugroho Bens Pardamean Mathematics Department School of Computer Science Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department Bioinformatics and Data Science Research Center BINUS Graduate Program Jakarta Indonesia

Understanding the mechanistic interpretability of mutation effects in a protein can help predict the clinical implications of the genetic variants. Hence, computational variant effect predictions that involve protein structural features of the protein mutations might be suitable in this case. In this work, we focus on BRCT domains of BRCA1 gene that is widely studied in breast cancer studies. We retrieved 88 selected missense variants found in BRCT domains annotated in both ClinVar and gnomAD databases. To computationally characterize the pathogenic property of the mutations we used two types of features extracted from protein structures: a change in free Gibbs energy and a set of features derived from molecular dynamics simulations of each mutant. Using a dimensional reduction and Gaussian mixture model (GMM)-based clustering we demonstrate that the variants are segregated into two regions that may correspond to their pathogenic status. This method can be a potential computational pipeline for providing the preliminary mechanistic interpretation of mutation effects in terms of their thermodynamic and structural features.

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Virtual Plant of Basil (Ocimum Basillicum) by Using Functional-Structural Plant Model

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IOP Conference Series: Earth and Environmental science 2022年第1期998卷

作者： Ditdit Nugeraha Utama Heraldo Y Purwantono Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Indonesia is one of the most populated and large country in south-east Asia. Its abundance of natural resources was well known. Supported by its tropical climate, made Indonesia is also among the largest tropical country in the world. However, according to the data, arable land in Indonesia has drastically decreased over the years in line with the rising demand for residency areas. This statistic shows a rather concerning fact that it is possible that even though Indonesia with this richness of natural resources one day would not fulfil its own domestic food needs. Moreover, competitions and hindrances that experienced by the Indonesian farmers might also worsen this limited food supply. In this research, the computational plant model (called virtual model) of the above-land Basil plant (Ocimum Basillicum P.) was proposed. The Basil plant that is taken as a research object is specific. It is a plant growing in a hydroponic environment. By using structural and functional plant model (FSPM) and simple mathematical and statistical methods, the constructed model was able to portray the growth pattern of each plant organ morphologically and biologically. The development and growth patterns of each plant organ (i.e., stem, petiole, leaves, etc.) are also depicted in detail and precisely. The model was quite novel. It practically can be exploited by agronomists and researchers to see the potential effort in optimizing the plant's yield.

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The Implementation of Isolated Geothermal Grid on the Community Cuisine Learning in Rural Area in North Sumatera 7

The Implementation of Isolated Geothermal Grid on the Commun...

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

作者： Gaol, Ford Lumban Meyliana Winanti Prabowo, Harjanto Hutagalung, Fonny Bina Nusantara University BINUS Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Jalan Universiti Kuala Lumpur Wilayah Persekutuan50603 Malaysia

ISBN: (纸本)9781665404228

Hutajulu is a village of 450 households with a minigrid supplied solely by a 45kW geothermal system. The problems that happened is the very low performance of the grid interactions between energy use and grid operating practices when the areas are in the dry season. We also found that the weak. We use the approached with the Design Research that will adopt for modelling approached of the experiment on the Grid performance. The experiment results are shown that to reduce the consumption of the firewood for eight households, we adopt four types of electric cookstove that use the geothermal. We also investigate the interaction between the electric cookstove and the power system. We also found that The effects of the power system and the electric stoves on the cooking preferences is also revealed. © 2020 IEEE.

关键词： Electric stoves

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Virtual Plant Computational Model of Green-Leaf Vegetable Plant Bok Choy (Brassica chinensis L.) for Investment Decision

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IOP Conference Series: Earth and Environmental science 2022年第1期998卷

作者： D. N. Utama A. Wibowo Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Plant computational modelling is a part of ecological informatics. It is a research domain that model the plant/s and is correlated to an environmental issue. A vegetable is one imperative plant. It has an important role in aspects of health, the environment, and also the economy. The study was performed to make a plant computational model of the green-leaf vegetable plant Bok Choy that can suggest the environment-oriented decision in agriculture investment. Two methods functional structural plant modelling (FSPM) and simple mathematics are operated respectively to model the Bok Choy plant morphologically and the decision recommendation. The study produced the morphological 3-dimension (3D) model of the forty-fve-day-age plant Bok Choy and investment decision to plant Bok Choy in a hydroponic system.

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