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Effect Implementation of information Technology Software on Improving Performance Capacity Academic and Non Academic Service Sunan Ampel Islamic University of Surabaya 2

Effect Implementation of Information Technology Software on ...

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2nd Bukittinggi International Conference on Education, BICED 2020

作者： Ilham Eliyana, Anis Rizki Sridadi, Ahmad Usman, Indrianawati Purnomo, Agung Information Systems Study Program Department of Technology Faculty of Science and Technology Sunan Ampel Islamic University of Surabaya Indonesia Department of Management Faculty of Economics and Business Airlangga University Indonesia Bina Nusantara Institute of Creative Technology Malang Ahmad Yani 117 Street Surabaya East Java Indonesia

This research was conducted to examine the effect of applying information technology software to increase the capacity of academic and non-academic performance at the Sunan Ampel State Islamic University in Surabaya as a work support tool. The aim is to apply a software that is able to identify the needs of increasing performance capacity at Sunan Ampel State Islamic University in Surabaya, both academic and non-academic, so that systematic control and evaluation of all academic and non-academic operations can be carried out. The research respondents were 60 students and employees from the faculty of science and Technology of the Sunan Ampel State Islamic University in Surabaya. This research uses a quantitative approach with the analysis technique used is path analysis with SmartPLS software-based data processing and the overall results support the hypothesis. Based on the results of the study stated that information Technology has a positive and significant effect on performance, information Technology has a positive and significant effect on academic services, information Technology has a positive and significant effect on non-academic services, but performance has no effect on academic and non-academic services. The conclusion of the research is the influence of the application of information technology software can improve academic and non-academic performance and services at the Sunan Ampel State Islamic University of Surabaya © Published under licence by IOP Publishing Ltd.

关键词： Regression analysis

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Modeling the Percentage of NEET in Indonesia with Spatial Cauchy Regression through the Bayesian Analysis Approach

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IAENG International Journal of Applied Mathematics 2024年第7期54卷 1288-1295页

作者： Rantini, Dwi Fakhruzzaman, Muhammad Noor Ningrum, Ratih Ardiati Othman, Fazidah Choir, Achmad Syahrul Ramadan, Arip Alya, Najma Attaqiya Putri, Elfira Rahma Pratama, Muhammad Alfian Engineering Department Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Indonesia Engineering Department Data Science Technology Study Program Faculty of Advanced Technology andMultidiscipline Universitas Airlangga Indonesia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Malaysia Statistical Computing StudyProgram Politeknik Statistika STIS Indonesia Information System Study Program School of Industrial and System Engineering Telkom University Indonesia

Indonesia has entered a period of demographic bonus. Human resources must be optimized. The number of children who do not in employment, education or training (NEET) in each province needs attention. Several factors that could contribute to the decline in the NEET percentage are literacy rates and the number of adolescents with computer skills. Increasing these two factors is believed to be able to reduce the percentage of NEET in every province in Indonesia. To find out the relationship between these two factors and how much influence they have on the percentage of NEET, this research is modeled by Cauchy regression and includes spatial effects. The results of the analysis show that the best model is when the spatial effect is modeled by Fernandez Steel Skew Normal conditionally autoregressive (FSSN CAR). This result is seen from the smallest value of the Watanabe Akaike information Criterion (WAIC) in this model, which is 190.5. The parameter estimated shows that the higher the literacy rate and the number of adolescents with computer skills, the lower the percentage of NEET in each province in Indonesia. The results of this research can be useful for the Indonesian government to increase the number of educational facilities related to these two factors. © (2024), (International Association of Engineers). All rights reserved.

关键词： Bayesian CAR Cauchy Education NEET

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Classification of Land Cover from Sentinel-2 Imagery Using Supervised Classification Technique (Preliminary study)

Classification of Land Cover from Sentinel-2 Imagery Using S...

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International Conference on information Management and Technology (ICIMTech)

作者： Eka Miranda Achmad Benny Mutiara Ernastuti Wahvu Catur Wibowo Information Systems Department Doctoral Program in Information Technology Gunadarma University Jakarta Indonesia Faculty of Computer Science and Information Technology Gunadarma University Jakarta Indonesia Computer Science Faculty Universitas Jakarta Indonesia

This paper intended to classify land cover of high-resolution satellite image using supervised classification method. The object of this research was the land cover image of the central java area in Indonesia which chosen as an area observed with the cloud cover consideration. The Satellite image was obtained from Sentinel-2 through https://***. Supervised Classification and ArcMap 10.5 was used to classified image object. This research classified the land cover into four classifications class namely Water, Forest, Urban and Bare Land due to show the main classes in the Land Cover Classification of RSNI-l National Standardization Body of Indonesia, RSNI-l was used as reference for classification process. The confusion matrix used to calculate classification accuracy value. Subsequently, confusion matrix results compared to the truth information. The truth information was derived from the actual value of RASTERVALUE obtained from Google Earth. This research shown supervised classification maximum-likelihood classification has been classified land cover into four class (forest, water body, urban and bare land) with overall accuracy = 1 and kappa value = 0.4896. This result showed this research got moderate kappa accuracy value but high overall accuracy value. High accuracy value reached due to fully supervised experiment during classification process.

关键词： Satellites Forestry Training Java Probability Standardization Vegetation mapping

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Implementation of Mobile game for Religion Learning

Implementation of Mobile game for Religion Learning

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2019 IEEE International Conference on Engineering, Technology and Education, TALE 2019

作者： Sulistiyo, Edy Vindy Anwar, Nizirwan Warnars, Diana Teresia Spits Wibawa, Setya Chendra Brotosaputro, Goenawan Kristiadi, Dedy Prasetya Warnars, Harco Leslie Hendric Spits Hashimoto, Kiyota Universitas Negeri Surabaya Electrical Engineering Department Jawa Timur60213 Indonesia School of Computer Science Bina Nusantara University Game Application Technology Program Jakarta11480 Indonesia Esa Unggul University Faculty of Computer Science Jakarta11510 Indonesia Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Universitas Budi Luhur Information System Department Jakarta12260 Indonesia Raharja University Computer Science Department Tangerang15117 Indonesia Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Prince Songkla University Faculty of Technology and Environment Phuket Campus Thailand

ISBN: (纸本)9781728126654

Currently, the growth of information and technology is rapid. It makes a lot of things in various fields including education becoming more effective and efficient. In education, one of its implementation which is a game is proven to be a useful tool to support conventional teaching methods and bring a more natural understanding of learning materials. Moreover, as a product of the popular culture in modern society, video game mirrors the general culture practice in real life and reflects it via its own culture inside the game. This makes a video game can give a contribution to the social construction of reality as it affects the player's view towards learning in real life and vice versa. From there, we see that there is an opportunity for learning about religion to be supported by its utilization to provide an interactive and fun learning experience. In this paper, we discuss how a video game is implemented to support religious learning. The game was developed with the scrum method where we surveyed to gather the user requirements before the design step. The game design was made by using the use case diagram and storyboard, and it was built using Unity version 2017.3.0f3. © 2019 IEEE.

关键词： Serious games

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IoT for Water Quality Categorization 5

IoT for Water Quality Categorization

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5th International Conference on Cybernetics and Intelligent systems, ICORIS 2023

作者： Sastrohartono, Hermantoro Krisdiarto, Andreas Wahyu Uktoro, Arief Ika Rahutomo, Reza Suparyanto, Teddy Pardamean, Bens Institute of Agriculture Stiper Faculty of Agricultural Technology Agricultural Engineering Department Yogyakarta Indonesia Bina Nusantara University School of Information Systems Information System Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics & Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350369489

In agricultural water research, the adoption of Internet of Things (IoT) technology has emerged as a pivotal approach for large-scale data collection. Water availability in the context of water quality is very important, both for domestic and industrial purposes. For domestic purposes, drinking water and bathing water are separated. Meanwhile, for the palm oil industry, boiler filler is differentiated from additional process water (dilution water). Water quality parameters can be assessed from turbidity and Total Dissolve Solid (TDS). Measurements using measuring instruments separately and repeatedly require significant energy, time, and costs. This research was conducted with the primary objective of presenting a novel method for categorizing water quality with the approach of IoT sensor technology. The research methodology entailed the utilization of an integrated IoT water sensors system in conjunction with manual water categorization. The methods consist of (1) system design, (2) design and installation of sensor and IoT-based microcontrollers, and (3) accuracy and precision testing compared with laboratory measurements. The precision of the integrated IoT water sensors was assessed through a dedicated sensor precision test, resulting in an accuracy rate of 94.4% for the turbidity sensor and 97.5% for the TDS sensor. Notably, this approach successfully discriminated drinking water with valid categorization, while other water types, including groundwater, water with tea, and water with coffee, yielded null categorization results. © 2023 IEEE.

关键词： Internet of things

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The Application of AGNES Algorithm to Optimize Knowledge Base for Tourism Chatbot

The Application of AGNES Algorithm to Optimize Knowledge Bas...

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International Conference on information Management and Technology (ICIMTech)

作者： Albert Verasius Dian Sano Tanto Daud Imanuel Mega Intanadias Calista Hendro Nindito Andreas Raharto Condrobimo Computer Science Study Program Bina Nusantara Institute of Creative Technology Malang Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia

Most tourists have limited time and schedule when they are visiting a particular tourism area. One of the main issues faced by those tourists is that they can not make simple queries to search engines about, for example, which sites or places to visit optimally if we only have one day or two-day visit? Search engines are better and better in replying users' queries with relevant answers. However, search engines are not always able to respond queries suited to users' characteristics such as their styles, personalities, knowledge backgrounds, etc. Also, search engines are not as flexible as chatbots in enabling dialogical-communication-queries. This case study aims to respond aformentioned issue by applying hierarchical cluster analysis on a set of tourism sites around Malang city, Malang regency, and Batu city based on AGNES (Agglomerative Nesting) algorithm. The result, then, is fed into chatbot's knowledge base. This chatbot will assist tourists to get information on which possible sites they have to visit optimally if they are under limited vacancy-time constraints.

关键词： Urban areas Knowledge based systems Clustering algorithms Search engines Merging Data mining

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Implementation of Malaria Detection Using MobileNetV2 Pretrained Model for Improved Deep Learning Based Diagnostics

Implementation of Malaria Detection Using MobileNetV2 Pretra...

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International Conference on Computing, Engineering, and Design (ICCED)

作者： Rahmat Hidayat Achmad Solichin Adhitia Erfina Sudin Saepudin Muhamad Muslih Mohd Zainuri Saringat Master of Computer Science Budi Luhur University Jakarta Indonesia Information Systems Study Program Nusa Putra University Sukabumi Indonesia Department of Software Engineering Faculty of Computer Science and Information Technology Tun Hussein Onn Malaysia University

ISBN: (数字)9798331529376

ISBN: (纸本)9798331529383

The Plasmodium parasite, which causes malaria, is an acute fever illness that infects people when a female Anopheles mosquito bites them. It is predicted that malaria would claim 619,000 lives in 2021, with 96% of those deaths occurring in the African continent. We can achieve this by using a microscope to examine thick and thin blood smears. The proficiency of a microscope examiner is crucial for doing microscopic examinations. Consider how time-consuming, ineffective, and costly it would be to examine thousands of malaria cases. Consequently, Creating an automated method for detecting malaria parasites is the aim of this study. We employ a MobileNetV2 pretrained model with CNN technology. Because it has been trained on dozens or even millions of data points, this pretrained model is incredibly light but dependable. There are two main benefits of automatic malaria parasite detection: firstly, it can offer a more accurate diagnosis, particularly in locations with limited resources; secondly, it lowers diagnostic expenses. The optimizer utilizes Adam Weight, the criteria uses NLLLoss, and the model is trained using 32 for batch_size. In the fourteenth epoch, we obtained the maximum accuracy score of 96.26% based on the training data. The outcomes of the predictions demonstrate how excellent this score is. EfficienceNet, DenseNet, AlexNet, and other pretrained models are among the alternatives that scientists are advised to try training with.

关键词： Training Adaptation models Accuracy Costs Malaria Microscopy Data visualization Training data Cost function Data models

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Generating Activity Streams from Events occurring in company-internal IT infrastructures

Generating Activity Streams from Events occurring in company...

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2011 IEEE 13th International Conference on Communication Technology(ICCT 2011)

作者： Eng.S.M.Khaled Reza S.M.Mohsin Reza Masters Program in Computational Engineering (Distributed Systems Engineering) Faculty of Computer Science Dresden University of Technology Dresden Germany Masters Program in Information Technology (Embedded Systems Engineering) Faculty of Computer Science Electrical Engineering and Information Technology University of Stuttgart Germany

In the current era of technology,the Internet and web technologies become the center source of *** to the huge amount of contents,one of the main challenges of modern information technology is aimed at how to reduce and manage information in a structured way with mobilizing users to the similar kind of relevant ***,any intelligent system should be able to understand people's interest about a particular type of information and automatically mobilize him to the similar kind of available information *** idea of high level Activity Streams along with its standardized format can play a vital role to solve this problem in the broader *** paper introduces a novel system called CoASGen (Consolidation and Activity Streams Generator) which is able to automatically generate high level Activity Streams after aggregating and consolidating from different independent systems (*** a software company context:version management system,wikis,bug trackers etc.).It retrieves life time information as heterogeneous web feed by sensing user activities from those independent systems and then it transforms several similar types of atomic activities into high level Activity Streams using semantic technologies along with its specific standardized ***,it shows these high level Activity Streams to the user interface which is able to automatically motivate users to find relevant information easily without either missing any data or losing valuable *** system solves the problem "data silos" by reducing and managing information in a structured way.

关键词： Activity Streams,Atomic Activity,High Level Activity Stream,CoASGen System

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Web based Biblical library information system Lembaga Alkitab Indonesia — Jakarta

Web based Biblical library information system Lembaga Alkita...

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International Joint Conference on computer science and Software Engineering (JCSSE)

作者： Mira Ziveria Elvander Information Systems Studies Program Faculty of Computer Science and Communication Studies Kalbis Institute 13210 Jakarta - Indonesia

ISBN: (纸本)9781509020348

Lembaga Alkitab Indonesia (LAI or Indonesia Bible Society) is a nonprofit corporation that supports churches, organizations and Christians in Indonesia for the provision of the Bible and its parts. One of the facilities provided by LAI is the Biblical Library. The problem that faced is the library management is still done manually. This research aims to design and build a web-based information system that could facilitate Biblical library management system LAI Jakarta in managing the collection, circulation, membership and online visitor access. The method that used is the Software Development Life Cycle (SDLC) with implementation stages that using the programming Hypertext Preprocessor (PHP) and storage of data using MySQL and Apache as the web server.

关键词： Libraries Databases Data models computer science Software engineering Data collection

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Development of a Web Based Corruption Case Mapping Using Machine Learning with Artificial Neural Network 3

Development of a Web Based Corruption Case Mapping Using Mac...

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

作者： Noerlina Dewanti, Retno Mursitama, Tirta Nugraha Fairianti, Sheila Putri Kristin, Desi Maya Sasmoko Muqsith, Andi Muhammad Krishti, Nathasya Shesilia Makalew, Brillv Andro Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Management Department Bina Nusantara University BINUS Business School Undergraduate Program Jakarta11480 Indonesia International Relations Department Faculty of Humanities Bina Nusantara University Jakarta11480 Indonesia Psychology Department Faculty of Humanities Bina Nusantara University Jakarta11480 Indonesia Primary Teacher Education Department Faculty of Humanities Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Bina Nusantara University School of Computer Science Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Mobile Application Technology Program Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

Cumulative state loss over the years caused by corruption in Indonesia has reached a fantastic number of 15 Billion usn up until 2016 [1]. To imagine the severances of it, 10.000 KM of highway can be built with that much amount of fund. Several responses has been done by Indonesian government to fight corruption from both prevention and persecution. This work focuses on the development of a web application aimed to provide insight to corruption case per province in Indonesia. The web application was developed using Machine Learning, specifically Backpropagation Artificial Neural Network (ANN). Web crawling and web scraping techniques are used to gather news content from 7 major news portal in Indonesia. Accuracy is measured by comparing correct prediction by ANN to its true value. Upon finding corruption news, data is saved and further analysis is done to establish the number of corruption news per region. Finally, the output is visualized using Google Map API. The purpose of this work is to provide regional depiction of corruption case to give further insight to be used by decision makers. Upon using this web application, objectivity of program development is expected to increase. The final output of the web application is a map of corruption case in Indonesia per region. The accuracy of ANN used in this work to classify corruption and non-corruption news is 96.91 % using Sigmoid Activation Function. © 2018 IEEE.

关键词： Neural networks

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