Game Data Science: An Introduction

2021 ◽  
pp. 1-32
Author(s):  
Magy Seif El-Nasr ◽  
Truong Huy Nguyen Dinh ◽  
Alessandro Canossa ◽  
Anders Drachen
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Data Collection ◽  
Data Processing ◽  
Data Science ◽  
Data Driven ◽  
Game Development ◽  
Collection Data ◽  
Support Decision Making ◽  
Over Time

This chapter introduces the topic of this book: Game Data Science. Game data science is the process of developing data-driven techniques and evidence to support decision-making across operational, tactical, and strategic levels of game development, and this is why it is so valuable. This chapter introduces this topic as well as outlines the process of game data science from instrumentation, data collection, data processing, data analysis, to reporting. Further, the chapter also discusses the application of game data science, as well as its utility and value, to the different stakeholders. The chapter also includes a section discussing the evolution of this process over time, which is important to situate the field and the techniques discussed in the book. The chapter also outlines established industry terminologies and defines their use in the industry and academia.

scholarly journals Feasibility Study of Company Investment on Public Cigarette Manufacturing Companies

2019 ◽  
Vol 3 (1) ◽  
pp. 128
Author(s):  
Syamsul Huda ◽  
Heikal Muhammad Zakaria Hakim
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Data Processing ◽  
Feasibility Study ◽  
Preliminary Data ◽  
The State ◽  
Research Use ◽  
Manufacturing Companies ◽  
Collection Data ◽  
Cigarette Manufacturing

The number of tobacco manufacturing companies is decreasing significantly, above 60 (sixty) companies on average every year. However, the cigarette companies contribute a significant amount to the state revenues, with an increase of more than 5 (five) trillion rupiah every year. Based on the data, we want to know the feasibility of investing in a cigarette company in the future. The method used includes four stages starting from data collection, data analysis, preliminary data processing, and concluding. This research use three sample companies: PT. Bentoel Internasional Investama Tbk, PT. Gudang Garam Tbk, and PT. HM Sampoerna Tbk. The results showed that based on the ROI, NPV, IRR, and BEP, PT. Gudang Garam Tbk. is the most feasible, followed by PT. HM Sampoerna Tbk. Meanwhile, PT. Bentoel Internasional Investama Tbk not feasible for investment.

scholarly journals Information Systems in Support of the Decision-Making Tools

2021 ◽  
pp. 127-131
Author(s):  
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Information Systems ◽  
Data Analysis ◽  
Data Collection ◽  
Information Exchange ◽  
Specific Information ◽  
The World ◽  
Collection Data ◽  
Reporting Data

AbstractDevelopment and dissemination of the information technology throughout the world, as well as the convention potentials for rapid information exchange, primarily via Internet-based platforms, enable for rapid reporting, data collection, data analysis and situation-based decision-making. Such a workflow is especially important in management of rapidly developing emergencies, including NREs. IAEA has already established several such platforms and is intensively working on the improvements and upgrades of the existing ones, as well as on the development of new, sector-specific information platforms. This chapter gives information on the currently existing/developing IAEA platforms for management of NREs.

Transparent Aspect-Level Sentiment Analysis Based on Dependency Syntax Analysis and Its Application on COVID-19

2022 ◽  
Vol 14 (2) ◽  
pp. 1-24
Author(s):  
Bin Wang ◽  
Pengfei Guo ◽  
Xing Wang ◽  
Yongzhong He ◽  
Wei Wang
Keyword(s):  
Data Collection ◽  
Natural Language ◽  
Data Processing ◽  
Sentiment Analysis ◽  
Natural Language Semantic ◽  
Syntax Analysis ◽  
Collection Data ◽  
Dependency Syntax ◽  
Over Time ◽  
Target Words

Aspect-level sentiment analysis identifies fine-grained emotion for target words. There are three major issues in current models of aspect-level sentiment analysis. First, few models consider the natural language semantic characteristics of the texts. Second, many models consider the location characteristics of the target words, but ignore the relationships among the target words and among the overall sentences. Third, many models lack transparency in data collection, data processing, and results generating in sentiment analysis. In order to resolve these issues, we propose an aspect-level sentiment analysis model that combines a bidirectional Long Short-Term Memory (LSTM) network and a Graph Convolutional Network (GCN) based on Dependency syntax analysis (Bi-LSTM-DGCN). Our model integrates the dependency syntax analysis of the texts, and explicitly considers the natural language semantic characteristics of the texts. It further fuses the target words and overall sentences. Extensive experiments are conducted on four benchmark datasets, i.e., Restaurant14, Laptop, Restaurant16, and Twitter. The experimental results demonstrate that our model outperforms other models like Target-Dependent LSTM (TD-LSTM), Attention-based LSTM with Aspect Embedding (ATAE-LSTM), LSTM+SynATT+TarRep and Convolution over a Dependency Tree (CDT). Our model is further applied to aspect-level sentiment analysis on “government” and “lockdown” of 1,658,250 tweets about “#COVID-19” that we collected from March 1, 2020 to July 1, 2020. The experimental results show that Twitter users’ positive and negative sentiments fluctuated over time. Through the transparency analysis in data collection, data processing, and results generating, we discuss the reasons for the evolution of users’ emotions over time based on the tweets and on our models.

CULTURAL CENTER KABUPATEN LANDAK

2021 ◽  
Vol 9 (1) ◽  
pp. 312
Author(s):  
Alef Experancio Ximenes Dasilelo ◽  
Emilya Kalsum ◽  
Bontor Jumaylinda Br. Gultom
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Data Processing ◽  
Cultural Heritage ◽  
Design Method ◽  
Cultural Value ◽  
Cultural Center ◽  
West Kalimantan ◽  
Processing Data ◽  
Collection Data

Landak Regency is one of the areas in West Kalimantan that is rich in cultural heritage. Various forms of cultural heritage come from 2 large ethntic, it is Dayak and Malay ethnic. Nevertheless, all the wealth and cultural heritage has not been integrated and has a special container. From the potential and problems, it is necessary to hold a container that can shelter and accommodate all components of cultural activities in the landak regency. This refers to the Cultural Center of Landak Regency. The design method used in the design of the Cultural Center is a seven-step design method, which starts from the search for ideas, data collection, data processing, data analysis, determining concepts and deciding the design results. This method refers to an area-scale Cultural Center design whose all variants of activities will be sheltered by the composition of several building times implemented based on their functions and activities, this Cultural Center will be supported by the application of a sheath system that will be implemented through the typical patterns of culture of Landak Regency with the emphasis of the concept more to modern minimalist buildings but rich in cultural value.

Challenges and Solutions of Big Data and IoT

2019 ◽  
pp. 264-272
Author(s):  
Jayashree K. ◽  
Abirami R. ◽  
Rajeswari P.
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Collection ◽  
Internet Of Things ◽  
Data Processing ◽  
The Internet ◽  
Huge Amount ◽  
Collection Data ◽  
Different Sources ◽  
The Internet Of Things

The successful development of big data and the internet of things (IoT) is increasing and influencing all areas of technologies and businesses. The rapid increase of more devices that are connected to IoT from which enormous amount of data are consumed indicates the way how big data is related with IoT. Since huge amount of data are obtained from different sources, analysis of these data involves much of processing at each and every level to extract knowledge for decision making process. To manage big data in a continuous network that keeps expanding leads to few issues related to data collection, data processing, analytics, and security. To address these issues, certain solution using bigdata approach in IoT are examined. Combining these two areas provides several opportunities developing new systems and identify advanced techniques to solve challenges on big data and IoT.

Biased Data

2020 ◽  
pp. 106-122
Author(s):  
Abigail Christina Fernandez
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Data Analysis ◽  
Data Collection ◽  
Data Science ◽  
Analysis Data ◽  
Relevant Field

Data is just data if it is not put to proper comprehensive usage. Information is Knowledge and Knowledge gets upgraded to wisdom pertaining to insight in the relevant field of analysis. Data Science has become the key that unravels many pitches of interest in diversified fields of quest. It is of optimal stipulation that the solutions that the Artificial Intelligence Algorithms provide should do justice to the intent for which what it was built. But at times, inadvertently the word bias is declaimed, which has become an implicit or explicit inclusion in the Algorithms and the data collection methodologies incorporated. IT companies manoeuvring this technology need to treat this hushed underplay in prediction and decision making with top-notch priority to epitomise this imminent episode of Machine Learning in Data Analysis.

scholarly journals BITOUR: A Business Intelligence Platform for Tourism Analysis

2020 ◽  
Vol 9 (11) ◽  
pp. 671
Author(s):  
Alexander Bustamante ◽  
Laura Sebastia ◽  
Eva Onaindia
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Data Processing ◽  
Data Visualization ◽  
Business Intelligence ◽  
Data Sources ◽  
Data Driven ◽  
Decision Making Process ◽  
The Core ◽  
Processing Data

Integrating collaborative data in data-driven Business Intelligence (BI) system brings an opportunity to foster the decision-making process towards improving tourism competitiveness. This article presents BITOUR, a BI platform that integrates four collaborative data sources (Twitter, Openstreetmap, Tripadvisor and Airbnb). BITOUR follows a classical BI architecture and provides functionalities for data transformation, data processing, data analysis and data visualization. At the core of the data processing, BITOUR offers mechanisms to identify tourists in Twitter, assign tweets to attractions and accommodation sites from Tripadvisor and Airbnb, analyze sentiments in opinions issued by tourists, and all this using geolocation objects in Openstreetmap. With all these ingredients, BITOUR enables data analysis and visualization to answer questions like the most frequented places by tourists, the average stay length or the view of visitors of some particular destination.

scholarly journals METONIMI PANDERAN “PEMBICARAAN” DI WARUNG BAHASA BANJAR

Multilingual ◽  
2019 ◽  
Vol 18 (1) ◽  
pp. 22-32
Author(s):  
Rissari Yayuk
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Data Processing ◽  
Semantic Approach ◽  
Distribution Method ◽  
Data Analysis Technique ◽  
Analysis Technique ◽  
Language Data ◽  
Collection Data ◽  
Descriptive Method

The research that will be raised is the metonymy of the "speaking" in the Banjar language in a traditional store (warung). Issues discussed included how the metonym structure of the "speaking" in Banjar was in store? The purpose of this study is to describe the metonym of the Banjar language "conversation" in the warung. The method used is descriptive method with a semantic approach. Data collection is done through reference and recording techniques. The author takes three steps of work, namely the stage of data collection, data processing, and the stage of presenting the results of data analysis. The data analysis technique is the distribution method. The presentation of data analysis describes conversations containing metonymy in Banjar language. Data presentations are written in ordinary words. The population of this study is the Banjar community located in the Gambah neighborhood, South Hulu Sungai Regency, South Kalimantan Province. The time of data collection is from January 2017 to March 2017. The results of this study include metonymy based on part elements with the whole, metonymy based on place attributes, metonymy based on objects for content or function and metonymy based on time attributes.Penelitian yang akan diangkat adalah metonimi panderan “pembicaraan” di warung bahasa Banjar. Masalah yang dibahas meliputi bagaimana struktur  metonimi panderan “pembicaraan” berbahasa Banjar di warung? Tujuan penelitian ini adalah mendeskripsikan struktur metonimi panderan “pembicaraan” di warung bahasa Banjar. Metode yang digunakan adalah metode deskriptif dengan pendekatan semantik. Pengumpulan data dilakukan melalui teknik simak dan catat. Penulis menempuh tiga langkah kerja, yaitu tahap pengumpulan data, pengolahan data, dan tahap penyajian  hasil analisis data. Teknik analisis data adalah metode agih. Sajian analisis data mendeskripsikan ujaran yang mengandung makna metonimi dalam bahasa Banjar. Penyajian data ditulis dengan kata-kata biasa. Populasi penelitian ini adalah masyarakat Banjar yang berlokasi  di lingkungan Gambah, Kabupaten Hulu Sungai Selatan, Provinsi Kalimantan Selatan.Waktu pengambilan data dari bulan Januari 2017 sampai dengan bulan Maret 2017. Hasil penelitian meliputi metonimi berdasarkan unsur bagian dengan keseluruhan, metonimi berdasarkan atribut tempat, metonimi berdasarkan objek untuk isi/fungsi dan metonimi berdasarkan atribut waktu.

Pertimbangan Hakim Dalam Menetapkan Itsbat Nikah di PA Bekasi (Studi Analisis Nomor 010/Pdt.P/2018/PA.Bks).

2021 ◽  
Vol 11 (2) ◽  
pp. 1-11
Author(s):  
Afifuddin - ◽  
Yoyo Hambali
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Data Processing ◽  
Government Regulation ◽  
Islamic Law ◽  
Field Research ◽  
Processing Data ◽  
Collection Data ◽  
Husband And Wife ◽  
Legal Force

This study describes the procedure for requesting a marriage determination at the Bekasi ReligiousCourt, as well as analyzing judges’ considerations in deciding a marriage determination case. Thisresearch is a field research, using descriptive methods. To find the results of this study, the researcherstook several steps, namely data collection, data processing, data analysis, and drawing conclusions.From the results of this study it can be concluded that the judges considerations refer to, 1) LawNumber 1 Year 1974 Article 2. 2) Government Regulation Number 9 Year 1975. 3) Articles 14 and7 paragraph 3 letter E Compilation of Islamic Law. 4) the book “I’anatut Tholibin volume 10, page254. In addition, the Judge is also flexible in seeing other factors for the benefit and legal certaintyof the petitioners. The procedure for requesting a marriage determination at the Bekasi ReligiousCourt is the same as the procedure for filing other cases, which are registered at the Religious Court.What distinguishes only the Application Conditions. Meanwhile, the results of the case of marriagedetermination that have been signed (with permanent legal force) can be used as evidence for theparties to register and register their marriage with the Marriage Registration Officer (PPN), at theOffice of Religious Affairs where the husband and wife live.

scholarly journals EFEKTIFITAS GAYA KEPEMIMPINAN DALAM MEMANAJEMEN RODA PEMERINTAHAN MASYARAKAT DESA TORJUNAN KABUPATEN SAMPANG

2015 ◽  
Vol 5 (1) ◽  
pp. 23
Author(s):  
Arnanda Ajisaputra
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Data Collection ◽  
Leadership Style ◽  
Situational Leadership ◽  
Data Input ◽  
Data Presentation ◽  
Government Institutions ◽  
Collection Data ◽  
The Village

The research objective was to clarify the effectiveness of leadership style of Torjunan  headman in terms of bureaucratic leadership that leads to its function as part of the Indonesian government institutions at the village level, and in terms of Situational Leadership leading to its function as the leader and protector of society. The instruments used in data collection were interviews, observation, and documentation; which further examined using three methods of data analysis namely; Miles analysis, which covered: data collection, data reduction, data presentation, and conclusion; Reddin analysis consisting of synchronization, data input, as well as the calculation of the average; and Hersey and Blanchard analysis comprising: synchronization, data input and drawing conclusions based on the accumulative column. The results showed: 1) Torjunan headman was seem less flexible in terms of managing the issues related to government affairs, especially regarding the bureaucratization of Robatal sub-district; 2) based on Blanchard Situational Leadership II model, Torjunan headman style were classified into G4 category, which means that Torjunan headman would be able to work more effective if he delegated the decision-making, as well execution, to society

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