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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Hartono, Sugiarto Kosala, Raymondus Raymond Supangkat, Suhono Harso Ranti, Benny Information Systems Department Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9781538658215

Document management system makes user to access information anytime and anywhere. The purpose of this research is to analyze what variables have impact on the intention to use of document management system. To achieve the objectives conducted by identification problem on the research model developed from the model of Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology to the use of document management system. Furthermore, the data obtained from the respondents tested outer model, inner model test, hypothesis test and to produce a comprehensive analysis will be conducted Importance Performance Analysis. This research will result in a comprehensive analysis and able to provide recommendations and solutions for improvement from the implementation DMS has been done earlier. © 2018 IEEE.

关键词： Information services

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Fuzzy Decision Support Model for Human Resources Performance Appraisal 3

Fuzzy Decision Support Model for Human Resources Performance...

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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Utama, Ditdit Nugeraha Rustamaji, Eri Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia Information System Department Syarif Hidayatullah State Islamic University Jakart Indonesia

ISBN: (纸本)9781538658215

Human resources (HRs) performance appraisal is one of several parts of HRs planning. It plays the imperative role to encourage HRs to have a good spirit and become correctly loyal to institution. The major objective of research is to propose a constructed decision support model (DSM) for appraising the HRs performance. The methods object oriented, fuzzy logic, hill climbing, and survey are benefitted to be main methods of this study which respectively are used to analyze and design the constructed model, justify and analyze data values, optimize the suggested decision, and collect data. By scientifically taking into account four selected fundamental performance parameters (i.e. education, teaching capability, research, and community service), the study was conducted;where, the measurement of performance bonus for university lecturer is chosen as a research object. Specifically for collecting data, 35 university lecturers were occupied to estimate the significance level of parameters. The lecturers are coming from two faculties of UIN Syarif Hidayatullah (Jakarta, Indonesia);i.e. faculties of science and technology and communication. At last, the model is practically going to assist the decision makers to fairly assess HRs performance;and the study showed a simulation result of assessment based on forty empirical data of university lecturer. © 2018 IEEE.

关键词： Fuzzy logic

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A Geoelectric Approach for Karst Groundwater Analysis

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

作者： Amallia Ferhat Taufik Seizarsyah Mohammad Prasanto Bimantio Nanda Satya Nugraha Dian Pratama Putra Teddy Suparyanto Alam Ahmad Hidayat Bens Pardamean Agribusiness Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Geophysical Engineering Department Universitas Pembangunan Nasional 'Veteran' Yogyakarta Indonesia Agricultural Crop Technology Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Forestry Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Agricultural Engineering Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia 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

Artesian well is one of the major efforts to obtain water source for fulfilling water demands in Eroniti Conservation park, Ponjong, Yogyakarta by drilling deep into several soil layers. Vertical Electrical Sounding (VES) method is the most common approach to determine the existence of groundwater. The method probes layers of rock below the ground surface based on their electrical properties, since the electrical resistivity of each layer is theoretically different. This study aims to utilize the VES approach for investigating the properties of the rock layers in the area to explore groundwater sources. We install six different VES points in the observation area using Schlumberger electrode configuration. The methodology of the work consists of three steps: the planning of the placement of the sounding points, the measurement step performed by a unit of IRIS SYSCAL Resistivity meter, and the data analysis and interpretation. Employing the resistivity analysis, we conclude that the observed region consists of Mediterranean soil as a result of weathering of limestone as well as lithology of the limestone. Furthermore, there are two types of aquifer found in the area: a perched aquifer found 27 meters below the ground surface of VES point 1 and a confined aquifer 166 meters below the ground surface of VES point 2 and 6.

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A Model of Visual Intelligent System for Genus Identification of Fish in the Siluriformes Order

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IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Taufik Budhi Pramono R Ardharyan Islamy Saprudin Joni Johanda Putra Teddy Suparyanto Kartika Purwandari Tjeng Wawan Cenggoro Bens Pardamean Aquaculture Study Program Faculty of Fisheries and Marine Science Jenderal Soedirman University Purwokerto Central Java Indonesia 53123 Aquatic Resources Management Brawijaya University Malang East Java Indonesia Graduate Program Aquatic Resources Faculty of Fisheries and Marine Science Jenderal Soedirman University Purwokerto Central Java Indonesia 53123 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 BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Ambiguity in the fish naming is present in several fish species database, especially for fish in Siluformes order. To fix the ambiguity, a visual intelligent system is needed to automate the fish naming correction in the database. In this study, we developed a deep-learning-based model as the core of the intelligent system. The proposed model achieved 89% accuracy for the classification of three genera in Siluformes order: Mystus, Hemibagrus, and Glyptothorax.

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Mining Association rule with Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) data mining technique 2

Mining Association rule with Attribute Oriented Induction Hi...

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2nd International Conference on Inventive Communication and Computational Technologies, ICICCT 2018

作者： Warnars, Harco Leslie Hendric Spits Gaol, Ford Lumban Heryadi, Yaya Trisetyarso, Agung Sanchez, Horacio Emilio Perez Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta11480 Indonesia Guadalupe30107 Spain

ISBN: (纸本)9781538619742

Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) as proposed new data mining technique has been success to mine frequent and similar patterns. Moreover, the AOI-HEP data mining technique has been improved with confidence mining pattern into two terms, where firstly give confidence mining pattern for each AOI-HEP pattern either frequent or similar pattern. Secondly, give confidence for each dataset as confidence AOI-HEP pattern between frequent and similar patterns. Confidence for each AOI-HEP pattern will show how interested each of AOI-HEP pattern between frequent and similar pattern, whilst confidence per dataset will show how interested each dataset between frequent and similar pattern. In this paper the mining of AOI-HEP has been extended to mine AOI-HEP association rules using the current AOI-HEP frequent pattern, since association rule deal with frequent pattern. Based from previous experiments upon 4 UCI machine learning datasets such as adult, breast cancer, census and IPUMS, there are 9 finding AOI-HEP frequent patterns where 8 from adult and breast cancer datasets respectively. Finally, there are 2 and 1 AOI-HEP association rules from adult and breast cancer datasets respectively. © 2018 IEEE.

关键词： Association rules

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Anomaly Detection in Climate Data Using Stacked and Densely Connected Long Short-Term Memory Model

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Journal of computers (Taiwan) 2020年第4期31卷 42-53页

作者： Saleh Abbas, Bahtiar Wahyono, Teguh Heryadi, Yaya Soeparno, Haryono Doctor of Computer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Salatiga Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Industrial Engineering Bina Nusantara University Jakarta Indonesia

Climate anomalies are considered as an important factor closely related to many disasters causing many human losses, such as airline crash, wildfires, drought and flooding in many areas. Many researchers have projected that the rising global temperature will increase the draught, especially in the mid-latitude areas. Taking those problems into account, studies on anomaly detection in climate are crucial. While climate prediction aims to analyze and model regular pattern of climate, climate anomaly studies aim to model climate deviation from its previous general patterns. Long Short Term Memory (LSTM) is a method employed in this research because it has been proven to work effectively in several anomaly detection studies, especially for data with similar characteristics. This paper presents empirical results of using Basic LSTM, Densely Connected (DC) LSTM, and Stacked-DC LSTM models to detect temperature anomaly as a manifestation of climate change in Semarang City. The results show that Stacked DC LSTM produced higher accuracy in detecting anomaly than the other two methods. © 2020 computer Society of the Republic of China. All rights reserved.

关键词： Long short-term memory

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Review Study of Business Intelligence to Support Strategic Decision Making

Review Study of Business Intelligence to Support Strategic D...

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International Conference on Electrical Engineering and Informatics, ICEEI

作者： Astari Retnowardhani Wahyu Sardjono Yaya Sudarya Triana BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Universitas Mercu Buana Jakarta Indonesia

In this era the business competition between regions and countries will be more stringent. One way to survive and improve its performance is through the management of information, it is necessary to be able to see and assess the company from a variety of perspectives. One of the keys to surviving and playing a role is to manage complete, fast and precise information. Data analysis will be easy if the required data is available. Business intelligence techniques (BI) can be used to assist in the decision-making process. Many organization and educational institution have implemented BI as the support system. Therefore, we make a comparison study about BI research finding from several articles. From the comparison study it can be seen the research in the BI field is continues to grow and also following the technology trend. This can be seen from the topics discussed in the journal articles in the period 2010-2017. This study is conducted to see the spread and trend of business intelligence research in various forms of organization. Also can be seen the advantages of BI in the decision-making process.

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Transfer Learning from Chest X-Ray Pre-trained Convolutional Neural Network for Learning Mammogram Data 3

Transfer Learning from Chest X-Ray Pre-trained Convolutional...

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

作者： Pardamean, Bens Cenggoro, Tjeng Wawan Rahutomo, Reza Budiarto, Arif Karuppiah, Ettikan Kandasamy 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 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia NVIDIA Corporation United States

Breast cancer is one of the deadliest cancer for female nowadays. Despite of the rapid advancement in medical image analysis with the rise of deep learning, development of breast cancer detection system is limited due to relatively small size of the publicly available mammogram dataset. In this paper, we discover an effective configuration for transfer learning from Chest X-Ray pre-trained Convolutional Neural Network to overcome the small-size mammogram dataset problem. We found that the best configuration achieve 90.38% validation accuracy for modified. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Deep learning

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Crowdsourcing annotation system of object counting dataset for deep learning algorithm 2

Crowdsourcing annotation system of object counting dataset f...

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2nd International Conference on Eco Engineering Development 2018, ICEED 2018

作者： Cenggoro, Tjeng Wawan Tanzil, Fidelson Aslamiah, Ayu Hidayah Karuppiah, Ettikan Kandasamy Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia NVIDIA Corporation Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

Deep Learning is currently the state-of-the-art technique for various computer Vision tasks, including object counting. Despite of its high performance, Deep Learning requires a gigantic amount of training data to show its best result. Getting this massive data in reasonable time requires a proper strategy such as crowdsourcing. However, in case of object counting, we found no crowdsourcing system able to effectively collect necessary data. To tackle this problem, we develop a crowdsourcing system to annotate image for object counting dataset. This system is also equipped with validation system to ensure the quality of collected dataset. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Crowdsourcing

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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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