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Sriwijaya Journal of Informatics and Applications
Published by Universitas Sriwijaya
ISSN : -     EISSN : 28072391     DOI : -
Core Subject :
Sriwijaya Journal of Informatics and Applcations (SJIA) is a scientific periodical researchs articles of the Informatics Departement Universitas Sriwijaya. This Journal is an open access journal for scientists and engineers in informatics and Applcations area that provides online publication (two times a year). SJIA offers a good opportunity for academics and industry professionals to publish high quality and refereed papers in various areas of Informatics e.q., Machine Learning & Soft Computing, Data Mining & Big Data Analytics, Computer Vision and Pattern Recognition and Automated Reasoning, and Distributed and security System
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Articles 5 Documents
 1 
Search results for , issue "Vol 2, No 1 (2021)" : 5 Documents clear
CLASSIFICATION METHODS ON SENTIMENT ANALYSIS OF TOURISTS ON AIRLINES IN TWITTER Elza Fitriana Saraswita; Dian Palupi Rini; abdiansah abdiansah
Sriwijaya Journal of Informatics and Applications Vol 2, No 1 (2021)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

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Abstract

Sentiment analysis is one of the knowledge to find the opinions of society towards a topic of discussion particular. Text mining is the science that many performed by individuals or companies to improve performance and fix complaints public against the services or brand trademarks that exist in the world of business. One of them is business flight or airline flights. One of them is public complaints against certain airlines posted on twitter. It is certainly going to greatly affect the airline 's own because , media social is one of the means of advertising and trade are extensive. Machine learning methods such as Logistics Regression, Kneighbors Classifier, Support Vector Classifier (SVC), Decision Tree Classifier, Random Forest Classifier, and Gaussian. Several classification methods are used to compare the performance of each method to see the best results.
The Effect of Brill Tagger on The Classification Results of Sentiment Analysis Using Multinomial Naïve Bayes Algorithm Astero Nandito; Abdiansah Abdiansah; Novi Yusliani
Sriwijaya Journal of Informatics and Applications Vol 2, No 1 (2021)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

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Abstract

Twitter is a good indicator for influence in research, the problem thatarises in research in the field of sentiment analysis is the large numberof factors such as the use of informal or colloquial language and otherfactors that can affect the results of sentiment classification. Toimprove the results of sentiment classification, an informationextraction process can be carried out. One part of the informationextraction feature is a part of speech tagging, which is the giving ofword classes automatically. The results of part of speech tagging areused for weighting words based on part of speech. This studyexamines the effect of Part of Speech Tagging with the method BrillTagger in sentiment analysis using the Naive Bayes Multinomialalgorithm. Testing were carried out on 500 twitter tweet texts andobtained the results of the sentiment classification with implementingpart of speech tagging precision by 73,2%, recall by 63,2%, f-measureby 67,6%, accuracy by 60,7% and without implementing part ofspeech tagging precision by 65,2%, recall by 60,6%, f-measure by62,4% accuracy by 53,3%. From the results of the accuracy obtained,it shows that the application of part of speech tagging in sentimentanalysis using the Multinomial Naïve Bayes algorithm has an effectwith an increase in classification performance.
Diagnosis Of Respiratory Tract Infections In Toddlers With Expert System Using Variable-Centered Intelligent Rule System And Certainty Factor Method Ahmad Gustano; Abdiansah Abdiansah; Kanda Januar Miraswan
Sriwijaya Journal of Informatics and Applications Vol 2, No 1 (2021)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

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Abstract

Expert system can help the experts in diagnose the Respiratory TractInfection For Toddlers. This research have a purpose to build anexpert system for Android with Kotlin language using Variable-Centered Intelligent Rule System and Certainty Factor method, alsoget the accuracy of it. System’s input is a yes or no answer from Yes-No Question with user. This research use 164 patient data of toddlersat UPTD Kenten Laut Banyuasin Health Center and variables which issymptoms that occurs in toddlers such as cough, cold, hard to breathe,fever, and the results of a physical examination conducted by theexpert. Based on test result, the system has 95,52% accuracy whendiagnose ISPA case, and 100% accuracy when diagnose Pneumoniacase. So, it can be concluded that Variable-Centered Intelligent RuleSystem and Certainty Factor method can be used to diagnoserespiratory infections in toddlers.
Determining The Quality and Production of Fresh Vegetables Using Simple Multi - Attributes Rating Technique (SMART) - Fuzzy Tsukamoto Dedi Irawan; Alvi Syahrini Utami; Desty Rodiah
Sriwijaya Journal of Informatics and Applications Vol 2, No 1 (2021)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

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Abstract

Vegetables are one of the most important needs in Indonesia. This is due to the increasing need for healthy food to meet daily needs. With the need for vegetables, the quality and production process are still hampered because it is done manually. Therefore created a system that can help someone determine the quality and production of the right vegetables. This system uses the SMART method and fuzzy Tsukamoto with the criteria and variables of vegetables used to get good quality and production. The SMART and fuzzy Tsukamoto method used a dataset of 20 vegetable commodities. In this study, 4 criteria and 3 variables were used, namely height, soil pH, temperature and age of harvest for quality determination. The production uses the variables of demand, supply and production.
Cross-Site Scripting Attack Detection using Rule-Based Signature deris Stiawan; Gonewaje gonewaje; Ahmad Heryanto; Rahmat Budiarto
Sriwijaya Journal of Informatics and Applications Vol 2, No 1 (2021)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v2i1.20

Abstract

Rule-Based Signature or also known as Misuse Detection is IDS which rely on matching data captured on retrieval of attack pattern which in system that allow attacks. If the attack activity detected according to existing signature, then it will be read by system and called as attack. The advantage of this Signature-Based IDS is the accuracy of detecting matched attack which in the system with low false-positive result and high true-positive. Cross-Site Scripting is type of attack which is perform by injecting code (usually) JavaScript to a site. XSS is very often utilized by attacker to steal web browser resource such as cookie, credentials, etc. Dataset which used in this research is dataset which created by injecting script into a website. Once obtained the dataset, then feature extraction is performed to separate the attribute which used. XSS attack pattern can be easily recognized from URI, and then detected using engine which has been created. Detection result of algorithm which used is evaluated using confusion matrix to determine detection accuracy value which performed. Obtained accuracy detection of research result reached 99.4% with TPR 98.8% and FPR 0%.

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