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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Ansyori, Rizal Qodarsih, Nanik Soewito, Benfano Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Badan Litbang Diklat Kumdil MA RI Jalan Cikopo Selatan Mega Mendung Bogor Indonesia

Enterprise Architecture (EA) has been receiving growing attention from organizations. Most organizations still face problems in EA implementation, EA Development is not an easy task. Since risk of failed EA implementation might occur, organization needs to know the Critical Success Factors (CSF) to implementation EA in organization especially in public sectors agency. This study provided a review of the extent literature (2007-2017) on framework that used to EA implementation and identify the CSF that affect to implement EA in public sectors agency. This Systematic Literature Review (SLR) establish a synthesis analysis based on the research model using PRISMA checklist. The final list of selected primary studies for the first stage had 16 primary studies. Then, the full texts of 16 primary studies were analyzed. Then from that, performed the synthesis to produce Enterprise Architecture framework and factors that affect enterprise architecture implementation. Base on summarize, can be conclude that the most commonly used framework in this literature study is TOGAF and The US Federal Enterprise Architecture Framework (FEAF), about 32% the public sectors using TOGAF framework to implementation EA, and about 25% public sectors using FEAF framework to implementation EA. According to the results of this study as many as 68% of papers say that the technical development is a CSF in the implementation of EA in public sector and about 50% of papers say that the framework and methodology is a CSF of implementation of EA in public sector. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Information management

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Biclustering Method to Capture the Spatial Pattern and to Identify the Causes of Social Vulnerability in Indonesia: A New Recommendation for Disaster Mitigation Policy

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Procedia computer science 2019年 157卷 31-37页

作者： Puspita Anggraini Kaban Robert Kurniawan Rezzy Eko Caraka Bens Pardamean Budi Yuniarto Sukim Computational Statistics Department Polytechnic of Statistics - STIS Jakarta 13330 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia College of Informatics Chaoyang University of Technology Taichung City 41349 Taiwan (R.O.C.) Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Geographically, Indonesia is a meeting point of three continental plates. Scilicet, the Eurasian Plate, the Indo-Australian Plate, and the Pacific Plate. Therefore, Indonesia is part of the infamous volcanic zone called the ”Ring of Fire” and one of the areas prone to natural disasters such as volcanic eruptions, earthquakes, tsunamis, floods, and landslides. This study aims to capture the spatial pattern and identify the causes of social vulnerability in the districts/cities in Indonesia using the biclustering method. The data is extracted from the Indonesian National Socio-Economic Survey (SUSENAS) by BPS-Statistics in 2014. The biclustering result indicates that each district/city has its own social vulnerability characteristics and shows that the vulnerable aspects of each district/city are different. The adjacent observations tend to have social vulenrability characteristics. The results of this study can be used as a reference for national disaster mitigation policy in Indonesia.

关键词： biclustering disaster mitigation social vulnerability SoVI spatial pattern

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Identification of types of tree damage based on forest health monitoring (FHM) in the management of TAHURA WAR utilization blocks

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AIP Conference Proceedings 2024年第1期2970卷

作者： Rahmat Safe’i Rico Andrian Tri Maryono Sepia Tapasya Tri Rizky Putra Master of Forestry Study Program Forestry Department Faculty of Agriculture University of Lampung Jl. Prof. Dr. Ir. Soemantri Brodjonegoro No. 1 Bandar Lampung Lampung 35145 Indonesia Dept. Computer Science Faculty of Mathematics and Natural Science University of Lampung Jl. Prof. Dr. Ir. Soemantri Brodjonegoro No. 1 Bandar Lampung Lampung 35145 Indonesia Plant Protection Study Program Faculty of Agriculture University of Lampung Jl. Prof. Dr. Ir. Soemantri Brodjonegoro No. 1 Bandar Lampung Lampung 35145 Indonesia Departement of Forestry Faculty of Agriculture University of Lampung Jl. Prof. Dr. Ir. Soemantri Brodjonegoro No. 1 Bandar Lampung Lampung 35145 Indonesia

Regarding management, TAHURA WAR is divided into blocks, one of which is the utilization block. In this block, the community can carry out utilization and use of forest areas. One of the causes of forest use by the community in this block is damage to trees due to high human activities or other concomitant causes. This study aimed to identify the damage to trees based on FHM in the TAHURA WAR utilization block. This research was conducted on five FHM cluster plots of utilization blocks that have been built. Identification is made by measuring and analyzing trees’ location, type, and severity based on the FHM method. The results showed 14 varieties of tree damage from 345 trees. The most common types of damage found were open wounds (code 03) with 162 trees and cancer (code 01) with 78 trees with an average severity of 20-29%. The two types of tree damage were often found at the location of the lower bole (code 3) and lower and upper bole (code 4), with the status of the level of tree damage in the moderate category (6.7 – 9.9). Thus, in the TAHURA WAR utilization block, two dominant types of tree damage were identified. This condition resulted in a considerable decrease in the quantity and quality of wood in the TAHURA WAR utilization block.

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Specify of Estimation Using C4.5 Algorithm of Software Project Estimation at the Point of Sales Application with Cocomo II 4

Specify of Estimation Using C4.5 Algorithm of Software Proje...

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4th International Conference on science and Technology, ICST 2018

作者： Novel, Kadinar Sfenrianto, Sfenrianto Gata, Windu Nainggolan, Kaman Wahyudi, Mochamad Jakarta Indonesia Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Master of Computer Science Postgraduate Programs STMIK Nusa Mandiri Jakarta Indonesia

ISBN: (纸本)9781538658130

In software development, it is required an appropriate estimate. One of the most commonly used software project estimation models is Constructive Cost Model(COCOMO II). The model is often used to obtain accurate results in estimating important factors such as cost and human resources. However, to obtain the more accurate estimation results, this study proposes a C4.5 algorithm based on COCOMO II estimation results. In this study, software project estimates are used in the Point of Sales (POS) applications. Based on these data with COCOMO II method, it is estimated that the schedule, staff, and cost are also specifying estimation from the result of COCOMO II using a C4.5 algorithm. The accuracy of the estimation results is around 90% with Algorithm C4.5. The value can be used as a reference for the development of the next POS software project. © 2018 IEEE.

关键词： Decision trees

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Industrial revolution 4.0 on big data adoption factors on social media users and popularity brands

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Journal of Physics: Conference Series 2021年第1期1839卷

作者： W Sardjono G Rama Putra E Selviyanti A Cholidin G Salim Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Computer Science Study Program Faculty of Mathematics & Natural Sciences Pakuan University Bogor Indonesia Health Department Politeknik Negeri Jember Jember Jawa Timur Indonesia 68124 Law Studi program Faculty of Law University of Muhammadiyah Jakarta Indonesia Post Graduate Program Faculty of Economic Science University of Trisakti Jakarta Indonesia

The purpose of writing this paper is to look at how factors of big data adoption affect the users of social media and brand popularity. The method used in the writing of this paper is by using path analysis and also by doing literature study to find reference material. The results of the analysis indicate that there is influence of big data adoption factors that affect the popularity of the brand. With this research, we get big data model that influence the brand popularity.

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Data annotation system for intelligent energy conservator in smart building

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IOP Conference Series: Earth and Environmental science 2020年第1期426卷

作者： Bens Pardamean Tjeng Wawan Cenggoro Bloomest Jansen Chandra Reza Rahutomo Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department College of Letters and Science University of Wisconsin 53706 Madison WI USA

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.

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Mitigating errors in mobile-based dietary assessments: Effects of a data modification process on the validity of an image-assisted food and nutrition app

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Nutrition 2023年 116卷 112212-112212页

作者： Ho, Dang Khanh Ngan Chiu, Wan-Chun Kao, Jing-Wen Tseng, Hsiang-Tung Yao, Chih-Yuan Su, Hsiu-Yueh Wei, Pin-Hui Le, Nguyen Quoc Khanh Nguyen, Hung Trong Chang, Jung-Su School of Nutrition and Health Sciences College of Nutrition Taipei Medical University Taipei Taiwan Department of Nutrition Wan Fang Hospital Taipei Medical University Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Dietetics Taipei Medical University Hospital Taipei Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Research Center for Artificial Intelligence in Medicine Taipei Medical University Taipei Taiwan Translational Imaging Research Center Taipei Medical University Hospital Taipei Taiwan Department of Adult Nutrition Counselling National Institute of Nutrition Hanoi Viet Nam Department of Clinical Nutrition and Dietetics National Hospital of Endocrinology Hanoi Viet Nam Graduate Institute of Metabolism and Obesity Sciences College of Nutrition Taipei Medical University Taipei Taiwan Nutrition Research Center Taipei Medical University Hospital Taipei Taiwan Chinese Taipei Society for the Study of Obesity (CTSSO) Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

Objective: Mobile nutrition applications (apps) provide a simple way for individuals to record their diet, but the validity and inherent errors need to be carefully evaluated. The aim of this study was to assess the validity and clarify the sources of measurement errors of image-assisted mobile nutrition apps. Methods: This was a cross-sectional study with 98 students recruited from School of Nutrition and Health sciences, Taipei Medical University. A 3-d nutrient intake record by Formosa Food and Nutrient Recording App (FoodApp) was compared with a 24-h dietary recall (24-HDR). A two-stage data modification process, manual data cleaning, and reanalyzing of prepackaged foods were employed to address inherent errors. Nutrient intake levels obtained by the two methods were compared with the recommended daily intake (DRI), Taiwan. Paired t test, Spearman's correlation coefficients, and Bland–Altman plots were used to assess agreement between the FoodApp and 24-HDR. Results: Manual data cleaning identified 166 food coding errors (12%;stage 1), and 426 food codes with missing micronutrients (32%) were reanalyzed (stage 2). Positive linear trends were observed for total energy and micronutrient intake (all P_trend < 0.05) after the two stages of data modification, but not for dietary fat, carbohydrates, or vitamin D. There were no statistical differences in mean energy and macronutrient intake between the FoodApp and 24-HDR, and this agreement was confirmed by Bland–Altman plots. Spearman's correlation analyses showed strong to moderate correlations (r = 0.834 ∼ 0.386) between the two methods. Participants’ nutrient intake tended to be lower than the DRI, but no differences in proportions of adequacy/inadequacy for DRI values were observed between the two methods. Conclusions: Mitigating errors significantly improved the accuracy of the Formosa FoodApp, indicating its validity and reliability as a self-reporting mobile-based dietary assessment tool. Dietitians a

关键词： Food records Mobile application Mobile health Smartphone application

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Unbalanced Data Clustering with K-Means and Euclidean Distance Algorithm Approach Case Study Population and Refugee Data

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Journal of Physics: Conference Series 2020年第2期1477卷

作者： NM Faizah Surohman L Fabrianto Hendra R Prasetyo Information Systems Department Tama Jagakarsa University Jakarta Indonesia Master of Computer Science-Postgraduate Program STMIK Nusa Mandiri Jakarta Indonesia

There is a lot of data that does not have a pattern and unbalanced that is difficult to classify, such as the total population of each country in the world is very varied especially when compared with the number of refugees from each of these countries, China and India numbered more than 2 billion people but the number of refugees is only 0, 01%, while Syria around 70% of the 18 million more residents are refugees. By using the K-Means algorithm, we can group countries that have similar characteristics of population and number of refugees, the average percentage of refugees to the population in each cluster is the character of the cluster. The methodology used in this study are: measures the distance of the data using the Euclidean distance formula, runs the K-Means algorithm, calculate the percentage value of each cluster and find conclusions from the characteristics of the clusters formed. We found how machine learning made a pattern of data without political and social issues, the result is K-Means describing machine learning can grouped every country in cluster that make sense.

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An Android-based Hoax Detection for Social Media

An Android-based Hoax Detection for Social Media

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International Conference on Electrical Engineering, computer science and Informatics (EECSI)

作者： Harrizki Arie Pradana Arif Bramantoro Ari Amir Alkodri Okkita Rizan Tri Sugihartono Supardi Technical Information STMIK Atma Luhur Pangkalpinang Bangka Belitung Faculty of Information Technology Universitas Budi Luhur Jakarta Indonesia Master Program in Computer Science Universitas Budi Luhur Jakarta Indonesia

Hoax is defined as a try to convince any readers to believe particular deception. A news frequently spreads on social media. Hoaxes news is engineered to meet a personal purpose and caused by predefined factors. In Indonesia, one of the top discussions is about hoax news related to natural disasters spread through social media. Some people have been sentenced to jail because of making and spreading hoax news. To date, the internet community is unable to distinguish hoax news from the actual news. This is because there is no available tool to detect hoaxes. Therefore, this paper propose an initiative to have a hoax detection application in Android-based devices by using the web scraping technique to extract data downloaded from the inputted URL with a simplified interface. The retrieved data are optimized by utilizing Nazief-Adriani stemming algorithm and analyzed by using Rabin-Karp algorithm.

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PROMOTING TIMOR LESTE’S TAIS CLOTH USING MOBILE AUGMENTED REALITY APPLICATION

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Procedia computer science 2018年 135卷 700-706页

作者： Marianus Magno Seran Bria Gede Putra Kusuma Louis Khrisna Putera Suryapranata Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The results of observations showed that the book about Tais produced by Secretariat de Estado da Arte e Cultura (SEAC) has not been able to meet the needs of users because the information is less interesting and interactive. This paper’s aim is to introduce the more interesting and interactive way to introduce Tais. Utilization of Augmented Reality (AR) technology in an application built with the Unity3D program is done to provide different way in presenting interesting and interactive information to its users. Based on the results in this paper, the developed application can handle the presentation in more interesting and interactive way. The ideal distance in the tracking process for target objects with size 7 x 6 cm is ranged from 6 cm to 30 cm, with the image ratio that can be detected at the farthest distance is 4% of the camera image. For the detection angle, the target object can be detected properly from approximately ±64 0 . From the data acquired, it can be said that AR can be used to introduce Tais in more interesting and interactive way.

关键词： augmented reality mobile application tais timor leste cultural heritage

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