Data Science Commons^™

Analisis Data Time Series Dan Vcr Kepadatan Lalu Lintas (Studi Kasus: Jalan Adisucipto Depan Ambarukmo Plaza), Arief Rachma Wibowo

Elinvo (Electronics, Informatics, and Vocational Education)

Kepadatan lalu lintas atau biasa dikenal dengan istilah kemacetan merupakan kondisi dimana terjadinya penumpukan kendaraan disuatu ruas jalan tertentu, hal ini bisa saja disebabkan oleh beberapa faktor, antara lain jumlah kendaraan yang berada dalam ruas jalan tersebut. Sumber data dari riset ini langsung diperoleh dari Dinas Perhubungan DIY. Analisis data time series digunakan untuk meramalkan jumlah kendaraan pada siang hari dan analisis VCR disini untuk klasifikasi kondisi jalan tersebut. Berdasarkan analisis data time series menggunakan metode trend, data jumlah motor yang melalui Jalan Adisucipto pada pukul 12.30-14.40 cenderung mengalami penurunan. Berdasarkan analisis VCR, jumlah kendaraan mencapai puncaknya pada pukul 15.30-17.00 …

Penerapan Data Mining Menggunakan Perbandingan Algoritma Greedy Dengan Algoritma Genetika Pada Prediksi Rentet Waktu Harga Crude Palm Oil, Desy Ika Puspitasari

Elinvo (Electronics, Informatics, and Vocational Education)

Penelitian ini menerapkan data mining pada prediksi harga CPO (Crude Palm Oil) dengan membandingkan pemodelan optimasi seleksi fitur algoritma genetika dan algoritma greedy pada metode neural network (NN). Prediksi harga CPO dilakukan untuk memenuhi kebutuhan investor kelapa sawit, melalui analisa masalah fluktuasi harga CPO time series yang tidak pasti. Guna mempermudah dalam melakukan perhitungan, langkah-langkah dari algoritma Genetika dan algoritma Greedy diimplementasikan dengan program komputer Rapid Miner Studio. Adapun tujuan penelitian ini yaitu mengetahui perbandingan akurasi dengan parameter evaluasi RMSE yang dihasilkan dan waktu eksekusi program yang dibutuhkan oleh algoritma Genetika dan algoritma Greedy dalam menyelesaikan masalah prediksi harga CPO. …

Pembagian Tingkat Kecanduan Game Online Menggunakan K-Means Clustering Serta Korelasinya Terhadap Prestasi Akademik, Yudi Prastyo

Elinvo (Electronics, Informatics, and Vocational Education)

Game online tidak hanya memberikan hiburan tetapi juga memberikan tantangan yang menarik untuk diselesaikan sehingga individu bermain game online tanpa memperhitungkan waktu demi mencapai kepuasan. Salah satu metode yang dapat digunakan untuk mengelompokkan tingkat kecanduan game online adalah metode K-Means Clustering. K-Means Clustering merupakan salah satu metode data clustering non hirarki yang berusaha mempartisi data yang ada ke dalam bentuk satu atau lebih cluster/kelompok.Penelitian ini mengambil data sample kuesioner dari mahasiswa di Universitas Ibn Khaldun Bogor dimana isian kuesioner akan diolah sebagai acuan pengelompokkan tingkat kecanduan game online.Hasil clusteringdigunakan untuk mengetahui hubungannya antara tingkat kecanduan game …

Interactive Visual Analytics Application For Spatiotemporal Movement Data Vast Challenge 2017 Mini-Challenge 1: Award For Actionable And Detailed Analysis, Yifei Guan, Tin Seong Kam

Research Collection School Of Computing and Information Systems

The Visual Analytics Science and Technology (VAST) Challenge 2017 Mini-Challenge 1 dataset mirrored the challenging scenarios in analysing large spatiotemporal movement tracking datasets. The datasets provided contains a 13-month movement data generated by five types of sensors, for six types of vehicles passing through the Boonsong Lekagul Nature Preserve. We present an application developed with the market leading visualisation software Tableau to provide an interactive visual analysis of the multi-dimensional spatiotemporal datasets. Our interactive application allows the user to perform an interactive analysis to observe movement patterns, study vehicle trajectories and identify movement anomalies while allowing them to customise the …

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

Supervised Classification Using Finite Mixture Copula, Sumen Sen, Norou Diawara

Mathematics & Statistics Faculty Publications

Use of copula for statistical classification is recent and gaining popularity. For example, statistical classification using copula has been proposed for automatic character recognition, medical diagnostic and most recently in data mining. Classical discrimination rules assume normality. But in this data age time, this assumption is often questionable. In fact features of data could be a mixture of discrete and continues random variables. In this paper, mixture copula densities are used to model class conditional distributions. Such types of densities are useful when the marginal densities of the vector of features are not normally distributed and are of a mixed …

Content Analysis Of Data Science Graduate Programs In The U.S., Duo Li, Elizabeth Milonas, Qiping Zhang

Publications and Research

Data science is an emerging academic field (Paul & Aithal, 2018), which has its origins in “Big Data/Cloud Computing” and complexity science domains. Data Science is about managing large and complex data (Big Data management) and analytics technologies (Paul & Aithal, 2018). Data, technology, and people are the three pillars of data science. In addition, Data Science is composed of three key areas: analytics, infrastructure, and data curation (Tang & Sae-Lim, 2016). Stanton (2012) defined data science as “an emerging area of work concerned with the collection, preparation, analysis, visualization, management, and preservation of large collections of information (Song & …

Constructing Interactive Visual Classification, Clustering And Dimension Reduction Models For N-D Data, Boris Kovalerchuk, Dmytro Dovhalets

Computer Science Faculty Scholarship

The exploration of multidimensional datasets of all possible sizes and dimensions is a long-standing challenge in knowledge discovery, machine learning, and visualization. While multiple efficient visualization methods for n-D data analysis exist, the loss of information, occlusion, and clutter continue to be a challenge. This paper proposes and explores a new interactive method for visual discovery of n-D relations for supervised learning. The method includes automatic, interactive, and combined algorithms for discovering linear relations, dimension reduction, and generalization for non-linear relations. This method is a special category of reversible General Line Coordinates (GLC). It produces graphs in 2-D that represent …

Devious Design: Digital Infrastructure Challenges For Experimental Ethnography, Lindsay Poirier

Statistical and Data Sciences: Faculty Publications

No abstract provided.

Programming For Data Science Csc 310, Amanda Izenstark

Library Impact Statements

No abstract provided.

Data Science Program, Amanda Izenstark

Library Impact Statements

No abstract provided.

Taking A Byte Out Of Corruption: A Data Analytic Framework For Cities To Fight Fraud, Cut Costs, And Promote Integrity, Center For The Advancement Of Public Integrity

Center for the Advancement of Public Integrity (Inactive)

In recent years, the emerging science of data analytics has equipped law enforcement agencies and urban policymakers with game-changing tools. Many leaders and thinkers in the public integrity community believe such innovations could prove equally transformational for the fight against public corruption. However, corruption control presents unique challenges that must be addressed before city watchdog agencies can harness the power of big data. City governments need to improve data collection and management practices and develop new models to leverage available data to better monitor corruption risks.

To bridge this gap and pave the way for a potential data breakthrough in …

So What Are You Going To Do With That? The Promises And Pitfalls Of Massive Data Sets, Sigrid Anderson Cordell, Melissa Gomis

UNL Libraries: Faculty Publications

This article takes as its case study the challenge of data sets for text mining, sources that offer tremendous promise for digital humanities (DH) methodology but present specific challenges for humanities scholars. These text sets raise a range of issues: What skills do you train humanists to have? What is the library’s role in enabling and supporting use of those materials? How do you allocate staff? Who oversees sustainability and data management? By addressing these questions through a specific use case scenario, this article shows how these questions are central to mapping out future directions for a range of library …

Special Issue: Neutrosophic Theories Applied In Engineering, Florentin Smarandache, Jun Ye

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophic sets and logic are generalizations of fuzzy and intuitionistic fuzzy sets and logic. Neutrosophic sets and logic are gaining significant attention in solving many real life decision making problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and indeterminacy. They have been applied in computational intelligence, multiple criteria decision making, image processing, medical diagnoses, etc. This Special Issue presents original research papers that report on state-of-the-art and recent advancements in neutrosophic sets and logic in soft computing, artificial intelligence, big and small data mining, decision making problems, and practical achievements.