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Journal of Applied Data Sciences
Published by Bright Publisher
ISSN : -     EISSN : 27236471     DOI : doi.org/10.47738/jads
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
One of the current hot topics in science is data: how can datasets be used in scientific and scholarly research in a more reliable, citable and accountable way? Data is of paramount importance to scientific progress, yet most research data remains private. Enhancing the transparency of the processes applied to collect, treat and analyze data will help to render scientific research results reproducible and thus more accountable. The datasets itself should also be accessible to other researchers, so that research publications, dataset descriptions, and the actual datasets can be linked. The journal Data provides a forum to publish methodical papers on processes applied to data collection, treatment and analysis, as well as for data descriptors publishing descriptions of a linked dataset.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
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Search results for , issue "Vol 1, No 2: DECEMBER 2020" : 5 Documents clear
Knowledge Management Strategy by Means of Virtualization in Covid-19 Eissa Mohammed Ali Qhal
Journal of Applied Data Sciences Vol 1, No 2: DECEMBER 2020
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v1i2.46

Abstract

In an era where companies, governmental programs, and the economy are knowledge-driven, they must understand the best ways to apply knowledge management to yield better results. Fortunately, technology is continuously evolving to better cope with knowledge management's arising challenges by innovating better problem-solving models. Cloud computing is one of the many technologies today that has revolutionized how different companies and economic sectors treat knowledge management by enabling this Knowledge's virtualization. The paper focuses on knowledge management transition to virtualization technology in supporting businesses during the COVID-19. Pandemic times despite many social restrictions being put in place to contain the virus. The text further presents the results of a study involving major firms in different sectors and how their applied virtualization technology is yielding results even during the toughest of times in any company or economy.
Diagnosis of Preeclampsia in Pregnant Women Based on K-Nearest Neighbor Algorithm Rifki Hidayat; Tri Astuti
Journal of Applied Data Sciences Vol 1, No 2: DECEMBER 2020
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v1i2.53

Abstract

Maternal deaths are divided into two namely direct and indirect deaths. Globally 80% of direct maternal deaths, preeclampsia are included in direct maternal deaths. Preeclampsia conditions of pregnancy with hypertension occur after the 20th week in women who previously had normal blood pressure. Preeclampsia can also be characterized by hypertension (systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg) accompanied by proteinuria (≥ 300 mg / dl in tamping urine 24 hours). In this study, an analysis of medical records in the Purbalingga and Banyumas areas using 8 attributes, namely age, body weight, blood pressure, edema, multiple pregnancy, history of hypertension, how many children, urine protein, and preeclampsia class. From calculations using the K-NN (K-Nearest Neighbor) algorithm, the Sensitivity performance value of 98.19%, Specificity 100%, and Accuracy 98.33%.
Analysis of Transaction Data for Modeling the Pattern of Goods Purchase Supporting Goods Location Linda Rosliadewi; Yusmedi Nurfaizal; Retno Waluyo; Mohammad Imron
Journal of Applied Data Sciences Vol 1, No 2: DECEMBER 2020
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v1i2.54

Abstract

Arlinda shop is a shop that sells daily necessities located in Salem, Brebes. Each day, this shop generates more and more data that is not used. The store layout which does not get enough attention will affect the level of sales. This study aimed to process the unused transaction data to obtain purchase patterns, some of the most frequently used algorithms were the apriori algorithm and FP-Growth algorithm to find relationship patterns, however, there was a technical constraint in the recommendation technique used which was frequently ignoring a large collection of items. To overcome this problem, the clustering process was carried out using the K-Medoids algorithm so that the association process became smaller. The test was carried out using RapidMiner with a minimum support of 10% - 30% and a minimum confidence of 70% and the results of recommendations for the layout of the goods with the highest lift ratio, namely if someone buys Nuvo BW then he buys pepsodent act, if someone buys wrapping papers then he buys mamy poko, and if someone buys cereal milo then he buys chitato.
Analysis of Heart Rate Variability of College Students in Altitude Training Based on Big Data Huiling Wang; Jingyuan Yang
Journal of Applied Data Sciences Vol 1, No 2: DECEMBER 2020
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v1i2.55

Abstract

Heart activity is regulated by sympathetic and parasympathetic autonomic nerves, which is a common method to measure and evaluate autonomic nerve activity. Collecting ECG data of college students and analyzing heart rate variability can evaluate autonomic nerve activity of college students. This paper discusses the influence of altitude training on students' heart rate variability, and the influence of altitude hypoxia and low pressure on students' autonomic nervous system, which provides a scientific basis for coaches to control the training intensity and amount and reduce the risk factors. The results show that good adaptability of altitude training can improve the activity ability of the vagus nerve.
Visual Design of Artificial Intelligence Based on the Image Search Algorithm Xiaobo Jiang; Zongren Chen; Jun Yu; Lixia Huang
Journal of Applied Data Sciences Vol 1, No 2: DECEMBER 2020
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v1i2.56

Abstract

With the rise of the wave of artificial intelligence and the development and popularization of intelligent technology, the digital images generated by the Internet and mobile intelligence terminals grow exponentially. As the most important information carrier of data content, pictures occupy immeasurable value in this era. To solve the shortage of image search engines, this paper uses the image browsing algorithm, which combines the semantic and image characteristics of the image, and organizes the returned images according to the visual characteristics similarity of the images. In addition, in order to reduce the computational time and improve the performance of similarity search, a near neighbor search algorithm based on key dimensions is applied. Experiments show that the AI visualization design based on the image search algorithm can not only overcome the semantic gap to some extent, but also strengthen the interaction between 88% systems and users to browse the search results more efficiently and naturally.

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