cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Husni Teja Sukmana
Contact Email
husni@bright-journal.org
Phone
+62895422720524
Journal Mail Official
jads@bright-journal.org
Editorial Address
Gedung FST UIN Jakarta, Jl. Lkr. Kampus UIN, Cemp. Putih, Kec. Ciputat Tim., Kota Tangerang Selatan, Banten 15412
Location
Kota adm. jakarta pusat,
Dki jakarta
INDONESIA
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 463 Documents
 2   3   4   5   6 
Application of Hash Sha-256 Algorithm in Website-Based Sales Software Engineering Khasanah, Fauziah Nikmatul
Journal of Applied Data Sciences Vol 3, No 1: JANUARY 2022
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v3i1.50

Abstract

Rapid technological developments can spur changes in the cycle of human activities, one of which is software engineering activities that continue to develop in accordance with technological developments, the development of software engineering activities is also developing methods of data security to withstand attacks from irresponsible parties. answer. This research was conducted to analyze the performance and robustness of the sha-256 data security method with ciphertext customization. The steps that the researchers took in conducting the analysis were collecting theory and case examples, designing programs, implementing programs, testing and saving the results. Based on this process, it can be concluded that ciphertext customization on sha-256 is needed to strengthen security and resistance to attacks from irresponsible parties, besides that the performance of sha-256 calculations with customization on ciphertext and without ciphertext is not too much different where only 65 ms difference based on the results of performance testing that researchers did.
An Exemination Of The Effects Of Service Quality And Satisfaction On Customers Behavior Intentions In E-Shoping: An Empirical Study With Comparision Of Taiwan And Vietnam Tran, Van-Dat; Nguyen, Minh Dung; Linh Vo, Thi Ngoc; Dinh, Thu Quynh
Journal of Applied Data Sciences Vol 2, No 4: DECEMBER 2021
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v2i4.45

Abstract

The purpose of this paper to examine the relationship among e-service quality and e-satisfaction and behavioral intention, to reveal any difference across Taiwan and Vietnam. Data from a survey of 891 online consumers, 409 respondents in Taiwan and 482 respondents in Vietnam were used to test the research model. Confirmatory factor analysis was conducted to examine the reliability and validity of the measurement model, and the structural equation modeling technique was used to test the research model. Data analysis involved the comparison of two models using structural equations modeling. The prevailed model reveals that e-service quality has a positive effect on e-satisfaction in both Taiwan and Vietnam, explored the influence of customer e-satisfaction on behavioral intention in Vietnam and Taiwan. E-service quality played a stronger positive role for online shoppers in Taiwan as compared to their counterparts in Vietnam. Such differences in determinants of customer satisfaction may due to the market contexts in different parts of the world.
Diagnosis of Preeclampsia in Pregnant Women Based on K-Nearest Neighbor Algorithm Hidayat, Rifki; Astuti, Tri
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 Rosliadewi, Linda; Nurfaizal, Yusmedi; Waluyo, Retno; Imron, Mohammad
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 Wang, Huiling; Yang, Jingyuan
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 Jiang, Xiaobo; Chen, Zongren; Yu, Jun; Huang, Lixia
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.
Big Data Classification of Personality Types Based on Respondents’ Big Five Personality Traits Chi, Jennifer
Journal of Applied Data Sciences Vol 3, No 2: MAY 2022
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v3i2.32

Abstract

A mixed model was introduced in this study, k-means clustering analysis for data examination, discriminant analysis for classification, and multilayer perceptron neural network analysis for prediction. After deleted inadequate samples and outliers, total number of observations was 1,009,998 for this study that was collected through on interactive online personality (i.e., big five personality traits) test in 2018. Empirical results based on the k-means clustering analysis identified four different personality clusters using the total score of big five personality traits (Extraversion, Neuroticism, Agreeableness, Conscientiousness, and Openness to Experience). Results of the k-means clustering analysis were tested for accuracy using the discriminant analysis indicated that cluster means were significantly different, and showed that 95.8% of original grouped cases correctly classified. The multilayer perceptron neural network framework was utilized as a predictive model, showed a 5-5-4 neural network construction, in deciding the personality classification of participants: Training 99.5% of training grouped cases and 99.5% of testing grouped cases correctly classified. Results of this study may provide insight into the understanding of the personality of participants for further psychological, social, cultural, and economic considerations.
The Mechanical and System Design of Finger Training Rehabilitation Device Based on Speech Recognition Wei, Xiaoxuan; Dong, Chen; Xu, Yang
Journal of Applied Data Sciences Vol 3, No 2: MAY 2022
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v3i2.58

Abstract

Aiming at the problem of long diagnosis and treatment recovery period and low recovery efficiency of traditional stroke patients, a finger rehabilitation training control system based on speech recognition is designed to help patients carry out finger exercise training and obtain the perception ability of finger angle, speed and position, and provide rehabilitation physicians with finger rehabilitation evaluation and training data reference. In order to realize the finger rehabilitation training control system, based on the finger movement perception system, the system is divided into hardware circuits, lower computer control systems, and voice recognition human computer interaction systems. Combining the unique advantages of the HMM algorithm, the HMM algorithm is applied to the voice interaction system for pattern matching, and the simulation test of the finger rehabilitation system is performed. The application results show that the rehabilitation training system based on speech recognition proposed in this study meets the design requirements, has good safety and reliability, and has high application value for future finger rehabilitation training.
Research on Short Video Publishing Algorithm and Recommendation Mechanism Based on Artificial Intelligence An, Lei
Journal of Applied Data Sciences Vol 3, No 2: MAY 2022
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v3i2.59

Abstract

Aiming at the problem of poor feature expression ability and model representation effect of traditional video recommendation mechanism, combined with the characteristics of traditional recommendation algorithm, this paper deeply studies the short video publishing algorithm and recommendation mechanism under artificial intelligence, and constructs a two-layer feature representation model BIFR based on attention. Firstly, the basic principle of recommendation algorithm is introduced in detail, and then the internal representation of features is studied through a multi head self attention mechanism to deeply mine the correlation between features and further improve the expressiveness of features. Then adjust the input feature crossover to learn the feature crossover more effectively. Finally, combine the two, add DNN to get the final output results, and then use the corresponding evaluation indicators to test the constructed recommendation model. The test results show that the video recommendation model constructed in this study has high accuracy, strong expressiveness and effectiveness.
Elevator Group Scheduling by Improved Dayan Particle Swarm Algorithm in Computer Cloud Computing Environment Yu, Jie; Hu, Bo
Journal of Applied Data Sciences Vol 3, No 2: MAY 2022
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v3i2.60

Abstract

The world is entering the era of cloud computing. Due to the rapid development of computer technology, as the core content of elevator transportation technology, elevator group control dispatching systems and group intelligent algorithms will have a wide range of application prospects due to their significant advantages. The purpose of this paper is to study the elevator group scheduling problem of the improved Dayan particle swarm algorithm in the computer cloud computing environment.This article first summarizes the research status of elevator group control technology and algorithms, and then analyzes and studies the basic theory of cloud computing task scheduling. Combined with the improved Dayan particle swarm algorithm, the elevator prediction model is established. This paper systematically expounds the theory and algorithm principle of the basic particle swarm algorithm, and analyzes the Dayan particle swarm algorithm on this basis. In this paper, the experimental research is carried out by comparing the two algorithms on the simulation software. Research shows that the improved Dayan particle swarm algorithm has better scheduling performance than the traditional basic particle swarm algorithm.

Page 4 of 47 | Total Record : 463

 2   3   4   5   6 

Filter by Year

2020 2025


Reset
Filter By Issues
All Issue Vol 6, No 4: December 2025 Vol 6, No 3: September 2025 Vol 6, No 2: MAY 2025 Vol 6, No 1: JANUARY 2025 Vol 5, No 4: DECEMBER 2024 Vol 5, No 3: SEPTEMBER 2024 Vol 5, No 2: MAY 2024 Vol 5, No 1: JANUARY 2024 Vol 4, No 4: DECEMBER 2023 Vol 4, No 3: SEPTEMBER 2023 Vol 4, No 2: MAY 2023 Vol 4, No 1: JANUARY 2023 Vol 3, No 4: DECEMBER 2022 Vol 3, No 3: SEPTEMBER 2022 Vol 3, No 2: MAY 2022 Vol 3, No 1: JANUARY 2022 Vol 2, No 4: DECEMBER 2021 Vol 2, No 3: SEPTEMBER 2021 Vol 2, No 2: MAY 2021 Vol 2, No 1: JANUARY 2021 Vol 1, No 2: DECEMBER 2020 Vol 1, No 1: SEPTEMBER 2020 More Issue