scholarly journals ANALISIS SENTIMEN TAGAR #INDONESIATERSERAH DI MASA COVID-19 MENGGUNAKAN METODE SENTISTRENGTH

2021 ◽  
Vol 9 (2) ◽  
pp. 207-213
Author(s):  
Bisma Aulia ◽  
Pradita Eko Prasetyo Utomo ◽  
Ulfa Khaira ◽  
Tri Suratno
Keyword(s):  
Data Preprocessing

Penggunaan sosial media di kala pandemi saat ini menjadi pilihan masyarakat dalam mengekspresikan pikirannya, salah satunya adalah Twitter. Dengan adanya fitur tagar di aplikasi Twitter, masyarakat dapat mengetahui informasi terbaru yang sedang tren. Dengan kondisi pandemi saat ini yang memunculkan banyak masalah sosial, politik, ekonomi dan sebagainya,  membuat Twitter menjadi tempat masyarakat mengekspresikan emosinya. Belum lama ini, tagar #IndonesiaTerserah menjadi buah bibir di masyarakat karena menggambarkan kekecewaan masyarakat terhadap penanganan virus Corona (COVID-19) di Indonesia. Penelitian ini bertujuan melihat bagaimana sentimen masyarakat Indonesia melalui tagar #IndonesiaTerserah. Sentimen tersebut dianalisis melalui algoritma sentistrength, dan diklasifikasikan menjadi 3 kelas, yakni positif, netral, dan negatif. Algoritma ini menggunakan dasar leksikon sebagai penghitungan bobot kekuatan sentimennya. Tahapan yang dilakukan dalam penelitian ini yakni tahap crawling data,  preprocessing data dan pembobotan kata. Hasil dari penelitian ini didapatkan 236 tweet data dengan 41,5% bersentimen netral, 32,2% bersentimen negatif, dan 26,3% bersentimen positif. Penelitian ini diharapkan dapat menjadi tolak ukur pemangku kepentingan dalam mengambil sebuah keputusan

Data Mining in Analysis of Biomechanical Signals

2009 ◽  
Vol 147-149 ◽  
pp. 588-593 ◽  
Author(s):  
Marcin Derlatka ◽  
Jolanta Pauk
Keyword(s):  
Data Mining ◽  
Principal Component Analysis ◽  
Cerebral Palsy ◽  
Spina Bifida ◽  
Decision Tree ◽  
Principal Component ◽  
Data Preprocessing ◽  
Component Analysis ◽  
Kernel Principal Component Analysis

In the paper the procedure of processing biomechanical data has been proposed. It consists of selecting proper noiseless data, preprocessing data by means of model’s identification and Kernel Principal Component Analysis and next classification using decision tree. The obtained results of classification into groups (normal and two selected pathology of gait: Spina Bifida and Cerebral Palsy) were very good.

Data Preprocessing for Chromatographic Fingerprint of Herbal Medicine with Chemometric Approaches

2005 ◽  
Vol 38 (14) ◽  
pp. 2475-2492 ◽  
Author(s):  
Fan Gong ◽  
Bo‐Tang Wang ◽  
Foo‐Tim Chau ◽  
Yi‐Zeng Liang
Keyword(s):  
Herbal Medicine ◽  
Data Preprocessing ◽  
Chromatographic Fingerprint

scholarly journals Data preprocessing workflow for exhaled breath analysis by GC/MS using open sources

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rosa Alba Sola Martínez ◽  
José María Pastor Hernández ◽  
Gema Lozano Terol ◽  
Julia Gallego-Jara ◽  
Luis García-Marcos ◽  
...  
Keyword(s):  
Biomarker Discovery ◽  
Data Preprocessing ◽  
Exhaled Breath ◽  
Sample Collection ◽  
Clinical Tool ◽  
Chronic Respiratory Diseases ◽  
Current State ◽  
Exhaled Breath Analysis ◽  
High Prevalence ◽  
Volatile Organic

AbstractThe noninvasive diagnosis and monitoring of high prevalence diseases such as cardiovascular diseases, cancers and chronic respiratory diseases are currently priority objectives in the area of health. In this regard, the analysis of volatile organic compounds (VOCs) has been identified as a potential noninvasive tool for the diagnosis and surveillance of several diseases. Despite the advantages of this strategy, it is not yet a routine clinical tool. The lack of reproducible protocols for each step of the biomarker discovery phase is an obstacle of the current state. Specifically, this issue is present at the data preprocessing step. Thus, an open source workflow for preprocessing the data obtained by the analysis of exhaled breath samples using gas chromatography coupled with single quadrupole mass spectrometry (GC/MS) is presented in this paper. This workflow is based on the connection of two approaches to transform raw data into a useful matrix for statistical analysis. Moreover, this workflow includes matching compounds from breath samples with a spectral library. Three free packages (xcms, cliqueMS and eRah) written in the language R are used for this purpose. Furthermore, this paper presents a suitable protocol for exhaled breath sample collection from infants under 2 years of age for GC/MS.

Application of Data Pre-Processing Method in Web Mining

2014 ◽  
Vol 687-691 ◽  
pp. 1592-1595
Author(s):  
Yun Peng Duan ◽  
Chun Xi Zhao ◽  
Ying Shi
Keyword(s):  
Data Mining ◽  
Web Mining ◽  
Early Stage ◽  
Data Preprocessing ◽  
Web Technology ◽  
Processing Method ◽  
Web Log Mining ◽  
Web Log ◽  
User Access ◽  
Log Mining

With the widely application of the WWW and the emergence of Web technology, make the research of data mining has entered a new stage. Web log mining is based on the idea of data mining to analyze the server log processing. Paper aimed at the early stage of the data mining is put forward based on log data preprocessing methods, the purpose is to divide server logs into multiple unique user access sequence at a time, and to give a good algorithm.

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