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Edi Sutoyo
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Indonesian Scientific Journal (Jurnal Ilmiah Indonesia) Jl. Pasar Atas No 3, Kompleks Setramas Kota Cimahi, Bandung
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International Journal of Advances in Data and Information Systems
Published by Indonesian Scientific Journal
ISSN : -     EISSN : 27213056     DOI : https://doi.org/10.25008/ijadis
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Advances in Data and Information Systems (IJADIS) (e-ISSN: 2721-3056) is a peer-reviewed journal in the field of data science and information system that is published twice a year; scheduled in April and October. The journal is published for those who wish to share information about their research and innovations and for those who want to know the latest results in the field of Data Science and Information System. The Journal is published by the Indonesian Scientific Journal. Accepted paper will be available online (free access), and there will be no publication fee. The author will get their own personal copy of the paperwork. IJADIS welcomes all topics that are relevant to data science, and information system. The listed topics of interest are as follows: Data clustering and classifications Statistical model in data science Artificial intelligence and machine learning in data science Data visualization Data mining Data intelligence Business intelligence and data warehousing Cloud computing for Big Data Data processing and analytics in IoT Tools and applications in data science Vision and future directions of data science Computational Linguistics Text Classification Language resources Information retrieval Information extraction Information security Machine translation Sentiment analysis Semantics Summarization Speech processing Mathematical linguistics NLP applications Information Science Cryptography and steganography Digital Forensic Social media and social network Crowdsourcing Computational intelligence Collective intelligence Graph theory and computation Network science Modeling and simulation Parallel and distributed computing High-performance computing Information architecture
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 137 Documents
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An Investigation into the Challenges Preventing Students of Educational Administration and Planning from Using ICT for Learning in Nigeria Higher Institutions Ogunode Niyi Jacob
International Journal of Advances in Data and Information Systems Vol. 1 No. 2 (2020): October 2020 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v1i2.188

Abstract

The main purpose of this research work is to investigate the challenges preventing students of educational administration and planning from using ICT for learning in Nigeria higher institutions: a case study of university of Abuja, Nigeria. The sample for this study was all the students in university of Abuja. 50 students from each level of the department of educational administration and planning totaling 200 were randomly selected from the department using simple random sampling technique. One hypothesis and three research questions were postulated as a guide to this study and a seven sub-items questionnaire divided into two sections was used to get the required information. A simple percentage and chi-square were used to test the hypotheses at 0.95% level of significance. It was found out that there are challenges preventing students of educational administration and planning from using ICT for learning. The challenges preventing students of educational administration and planning from using ICT for learning includes; unstable power supply, lack of personal laptop or computer system, unstable ICT Network services, lack of computer literacy by the students, High cost of ICT services, poor infrastructural facilities of ICT in higher institutions and poor computer literacy of the lecturers. Base on the findings, the researchers recommends that the government should increase the funding of education in Nigeria to enable schools administrators provide necessary ICT facilities in their various schools.
Impact of Covid-19 Pandemic School Close Down on the Research Programme of Higher Institutions Ogunode Niyi Jacob
International Journal of Advances in Data and Information Systems Vol. 1 No. 1 (2020): April 2020 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v1i1.189

Abstract

The purpose of this study is to examine the impact of covid-19 pandemic school close down on the research programme of higher institutions in Abuja, Nigeria. Descriptive survey design was used for the study and 4 research questions was developed for the study. Random sampling method was used to select 120 researchers in the four sampled institutions. The instrument used for collection of data was a structured questionnaire. Result collected revealed that 100% of the respondents agreed that Covid-19 pandemic school closure have impact on research program of higher institutions in FCT, 100% of the respondents agreed that Covid-19 pandemic will affects the flow of international research grants into higher institutions in FCT, 92% of the respondents agreed that Covid-19 pandemic will affects government funding of research higher institutions in FCT and 100% agreed that higher institutions as part of their community services by creating awereness to the general public on prevention of covid-19.The study also showed that 100% of the respondents agreed that higher institutions in Federal Capital Territory are collaborating with other institutions on the research for covid-19 vaccine while 69.17% of the respondents agreed that higher institutions in FCT are producing face masks for free distributions for the people to protect them from containing the covid-19 in Abuja. Based on this finding, this paper thereby recommends that government should increase the funding of research programme in Abuja and other higher institutions in the country.
Self-Diagnosis of Web-Based Pregnancy and Childbirth Disorders Using Forward Chaining Methods I Putu Agus Eka Pratama
International Journal of Advances in Data and Information Systems Vol. 2 No. 1 (2021): April 2021 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v2i1.1198

Abstract

The high mortality rate for pregnant women and childbirth in Bali, Indonesia, is caused by a lack of initial diagnosis of the diseases and complaints experienced by pregnant women during pregnancy, as well as a lack of health medical personnel scattered throughout Bali, to be able to provide optimal health services. It is necessary to have an online information system that helps pregnant women to be able to independently and online diagnose diseases, complaints, and symptoms experienced during pregnancy. The system must be able to be accessed anytime and anywhere, with high reliability and availability, and provide fast diagnostic results. Focus of this research is design and implementation of an Information System for Diagnosis of Pregnancy Disorders Based on Cloud Computing based on Forward Chaining Method, using Design Science Research Methodology (DSRM) and tested using the Technology Acceptance Model (TAM) method. The application is placed on the Hybrid Cloud. The results of this research, can help pregnant women in diagnosing diseases and complaints online, to reduce the mortality rate for pregnant women and giving birth.
Multi-Attribute Decision Making using Hybrid Approach based on Benefit-Cost Model for Sustainable Fashion Adriyendi Adriyendi; Yeni Melia
International Journal of Advances in Data and Information Systems Vol. 2 No. 1 (2021): April 2021 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v2i1.1200

Abstract

Multi-Attribute Decision Making (MADM) is used to select the best alternative from multi-alternatives based on multi-attribute (fashion material) and multi-criteria (sustainable fashion). Multi-alternatives are cotton, linen, silk, wool, acrylic, nylon, polyester, rayon, spandex, and mixed. Multi-attributes are material, texture, color, characteristic, comfort, and wearability. Multi-criteria are material fiber, smooth texture, faded color, elastic clothing, useful long, chilly and comfortable. Hybrid approaches and optimal solutions are needed to determine the best choice in decision making for both producers and consumers. The hybrid approach in MADM used is Simple Multi-Attribute Rating (SMART), Multi-Factor Evaluation Process (MFEP), Multi-Object Optimization based on Ratio Analysis (MOORA), Simple Additive Weighting (SAW), and Weighted Product (WP). SMART and MFEP are based on the Non-Benefit Cost Model while MOORA, SAW, and WP are based on a Benefit-Cost Model. The experimental results show that the SMART model with the best alternative is the rayon with the highest value (2.8333). The selection of the MFEP Model with the best alternative is rayon with the highest value (2.8330). The choice of MOORA model with the best alternative is rayon with the highest value (0.2595). The selection of the SAW Model with the best alternative is rayon with the highest value (0.8932). The selection of the WP Model with the best alternative is rayon with the highest value (0.1285). MADM using SMART, MFEP, MOORA, SAW, and WP for sustainable fashion yields the best alternative for consumption and production for the middle-class population in Indonesia.
K-Nearest Neighbor with K-Fold Cross Validation and Analytic Hierarchy Process on Data Classification Zoelkarnain Rinanda Tembusai; Herman Mawengkang; Muhammad Zarlis
International Journal of Advances in Data and Information Systems Vol. 2 No. 1 (2021): April 2021 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v2i1.1204

Abstract

This study analyzes the performance of the k-Nearest Neighbor method with the k-Fold Cross Validation algorithm as an evaluation model and the Analytic Hierarchy Process method as feature selection for the data classification process in order to obtain the best level of accuracy and machine learning model. The best test results are in fold-3, which is getting an accuracy rate of 95%. Evaluation of the k-Nearest Neighbor model with k-Fold Cross Validation can get a good machine learning model and the Analytic Hierarchy Process as a feature selection also gets optimal results and can reduce the performance of the k-Nearest Neighbor method because it only uses features that have been selected based on the level of importance for decision making.
Greedy, A-Star, and Dijkstra’s Algorithms in Finding Shortest Path Muhammad Rhifky Wayahdi; Subhan Hafiz Nanda Ginting; Dinur Syahputra
International Journal of Advances in Data and Information Systems Vol. 2 No. 1 (2021): April 2021 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v2i1.1206

Abstract

The problem of finding the shortest path from a path or graph has been quite widely discussed. There are also many algorithms that are the solution to this problem. The purpose of this study is to analyze the Greedy, A-Star, and Dijkstra algorithms in the process of finding the shortest path. The author wants to compare the effectiveness of the three algorithms in the process of finding the shortest path in a path or graph. From the results of the research conducted, the author can conclude that the Greedy, A-Star, and Dijkstra algorithms can be a solution in determining the shortest path in a path or graph with different results. The Greedy algorithm is fast in finding solutions but tends not to find the optimal solution. While the A-Star algorithm tends to be better than the Greedy algorithm, but the path or graph must have complex data. Meanwhile, Dijkstra's algorithm in this case is better than the other two algorithms because it always gets optimal results.
Features Selection for Entity Resolution in Prostitution on Twitter Reisa Permatasari; Nur Aini Rakhmawati
International Journal of Advances in Data and Information Systems Vol. 2 No. 1 (2021): April 2021 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v2i1.1214

Abstract

Entity resolution is the process of determining whether two references to real-world objects refer to the same or different purposes. This study applies entity resolution on Twitter prostitution dataset based on features with the Regularized Logistic Regression training and determination of Active Learning on Dedupe and based on graphs using Neo4j and Node2Vec. This study found that maximum similarity is 1 when the number of features (personal, location and bio specifications) is complete. The minimum similarity is 0.025662627 when the amount of harmful training data. The most influencing similarity feature is the cellphone number with the lowest starting range from 0.997678459 to 0.999993523.  The parameter - length of walk per source has the effect of achieving the best similarity accuracy reaching 71.4% (prediction 14 and yield 10).
Sentiment Analysis Approach for Analyzing iPhone Release using Support Vector Machine Wasim Bourequat; Hassan Mourad
International Journal of Advances in Data and Information Systems Vol. 2 No. 1 (2021): April 2021 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v2i1.1216

Abstract

Sentiment analysis is a process of understanding, extracting, and processing textual data automatically to get sentiment information contained in a comment sentence on Twitter. Sentiment analysis needs to be done because the use of social media in society is increasing so that it affects the development of public opinion. Therefore, it can be used to analyze public opinion by applying data science, one of which is Natural Language Processing (NLP) and Text Mining or also known as text analytics. The stages of the overall method used in this study are to do text mining on the Twitter site regarding iPhone Release with methods of scraping, labeling, preprocessing (case folding, tokenization, filtering), TF-IDF, and classification of sentiments using the Support Vector Machine. The Support Vector Machine is widely used as a baseline in text-related tasks with satisfactory results, on several evaluation matrices such as accuracy, precision, recall, and F1 score yielding 89.21%, 92.43%, 95.53%, and 93.95, respectively.
Implementing Data Privacy of Cloud Data on a Remote Server using Symmetric Cryptographic Algorithms David Livingston; Ezra Kirubakaran; Eben Priya David
International Journal of Advances in Data and Information Systems Vol. 2 No. 1 (2021): April 2021 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v2i1.1217

Abstract

Cloud Computing is an excellent technology for Micro Medium and Small Enterprises, which operate under budget shortage for setting up their own Information Technology infrastructure that requires capital investment on resources such as computers, storage and networking devices. Now-a-days, major Cloud Providers like Google and Amazon provide cloud services to its customers for managing their email, contact list, calendar, documents, and their own websites. MSME can take advantage of the cloud-based solutions offered by various Cloud Service Providers for equipping their own employees in doing their day to day activities more effectively and on the cloud. Though cloud computing promotes less expensive and collaborative work environment among a group of employees, it involves risks in keeping the resources such as computing and data secured. Different mechanisms are available for securing the data on the cloud among which encryption of data using cryptographic algorithm is the widely used one. Among various encryption symmetric algorithms, Advanced Encryption Standard is the more secured symmetric encryption algorithm for implementing data privacy on the cloud. In this paper, the authors have discussed some of the issues involved in adopting the cloud in an organization and proposed solutions that will benefit an organization while uploading and managing data in files and databases on the cloud.
Use Ordinary Expressions to Learn How to Extract Code Feedback From the Software Program Upkeep Process Anggara Trisna Nugraha Angga; Muhammad Jafar Shiddiq; Moch Fadhil Ramadhan
International Journal of Advances in Data and Information Systems Vol. 2 No. 2 (2021): October 2021 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v2i2.1219

Abstract

Software engineering is the manner of making use of engineering studies and alertness packages to the design, improvement and renovation of software program. For software program builders or college students majoring in data engineering, the software program renovation manner is a totally complicated activity. Software renovation manner charges account for 40% to 80% of the whole software program engineering manner. The software program renovation manner is resulting from based programming, inadequate understanding domains, and application documentation. In this study, researchers attempted to apply the Java programming language and c / c ++ to deal with supply code truncation. After finishing this manner, this system code may be divided into code and remarks. This report could be used to gain data approximately the manner of knowledge this system from the software program renovation manner. For supply code slicing, the writer makes use of normal expressions, specifically textual content processing strategies or patterns. Using normal expressions can accelerate the manner of locating remarks to your application. The end result of this study is to construct software primarily based totally on open supply code (loose license) so that scholars and trendy programmers can use it to assist apprehend this system. According to the effects of the researchers' testing, the recuperation price is 100% and the accuracy is 100%.

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