scholarly journals Educational Applications Of The Portland, Oregon Regional Archived Data User Service (Adus)

2020 ◽  
Author(s):  
Robert Bertini ◽  
Steven Hansen
Keyword(s):  
Data User ◽  
Educational Applications ◽  
Archived Data

PERANCANGAN SISTEM PAKAR DIAGNOSA KERUSAKAN SEPEDA MOTOR HONDA BEBEK BERKARBURATOR DENGAN MENGGUNAKAN METODE TEOREMA BAYES BERBASIS WEB MOBILE

2018 ◽  
Vol 3 (1) ◽  
pp. 58
Author(s):  
Joni Karman ◽  
Julius Saputra
Keyword(s):  
Modelling Language ◽  
Unified Modelling Language ◽  
Data Basis ◽  
Data User

AbstrakDalam penulisan penelitian ini penulis akan menjelaskan tentang pembuatan program sistem pakar diagnosa kerusakan pada sepeda motor honda bebek berkarburator dengan menggunakan metode teorema bayes berbasis web Mobile. Dengan bahasa pemrograman php. Kebutuhan-kebutuhan yang diperlukan dalam membangun suatu perangkat yaitu menggunakan UML (Unified modelling language). Database yang digunakan MySQL dan dikembangkan menggunakan sublime text. Hasil pengembangan meliputi data kerusakan, data gejala, data basis aturan, data solusi, data user dan data admin. Berdasarkan penelitian tersebut dapat disimpulkan bahwa perangkat lunak yang dibangun adalah perancangan sistem pakar diagnosa kerusakan pada sepeda motor honda bebek berkarburator dengan menggunakan metode teorema bayes berbasis web Mobile. Hasil dari perangkat lunak ini diharapkan mampu memberikan kemudahan dalam mendiagnosa kerusakan pada sepeda motor dalam memproses data menjadi informasi cepat, tepat dan akurat. Kata Kunci : Sistem pakar, Teorema Bayes, Web Mobile

Justifying the data analytical choice in single case research in relation to the expected data pattern

2019 ◽  
Author(s):  
Rumen Manolov
Keyword(s):  
Data Analysis ◽  
Visual Analysis ◽  
Multilevel Models ◽  
Single Case ◽  
Analytical Techniques ◽  
Real Data ◽  
Small Scale ◽  
Data User ◽  
Single Case Research ◽  
User Friendly

The lack of consensus regarding the most appropriate analytical techniques for single-case experimental designs data requires justifying the choice of any specific analytical option. The current text mentions some of the arguments, provided by methodologists and statisticians, in favor of several analytical techniques. Additionally, a small-scale literature review is performed in order to explore if and how applied researchers justify the analytical choices that they make. The review suggests that certain practices are not sufficiently explained. In order to improve the reporting regarding the data analytical decisions, it is proposed to choose and justify the data analytical approach prior to gathering the data. As a possible justification for data analysis plan, we propose using as a basis the expected the data pattern (specifically, the expectation about an improving baseline trend and about the immediate or progressive nature of the intervention effect). Although there are multiple alternatives for single-case data analysis, the current text focuses on visual analysis and multilevel models and illustrates an application of these analytical options with real data. User-friendly software is also developed.

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