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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) ComEngApp : Computer Engineering and Applications Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Media Infotama Bulletin of Electrical Engineering and Informatics Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Informatika dan Teknik Elektro Terapan ICON-CSE Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Dinamisia: Jurnal Pengabdian Kepada Masyarakat International Journal of New Media Technology INTECOMS: Journal of Information Technology and Computer Science MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Linguistik Komputasional Journal of Information Systems and Informatics Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Computer Science and Information Technologies Journal of Intelligent Computing and Health Informatics (JICHI) Sriwijaya Journal of Informatics and Applications Jurnal Generic Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Abdiansah, Abdiansah
Universitas Sriwijaya
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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Journal : Sriwijaya Journal of Informatics and Applications

 1 
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.
NL2SQL For Chatbot with Semantic Parsing Using Rule-Based Methods Kurniawan, Adi; Abdiansah, Abdiansah; Utami, Alvi Syahrini
Sriwijaya Journal of Informatics and Applications Vol 5, No 1 (2024)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v5i1.66

Abstract

Structured Query Language (SQL) is a command language that allows users to access database information. Ordinary people generally donot know how to make queries with SQL to a database. The chatbot is acomputer program developed to interact with its users via text or voice. In this study, chatbots were developed to help and facilitate users intheNatural Language to Structured Query Language (NL2SQL) process tosearch for information in an Academic Information Systemdatabasewith semantic parsing using a rule-based method that accepts input inthe form of interrogative sentences or order. In the Natural Language toStructured Query Language (NL2SQL) process several problems arise, namely input problems with unique parameters for the knowledge base, and slow searching or translation processes, which make Natural Language to Structured Query Language (NL2SQL) inef icient, problems This problem will be solved using a semantic parsingapproach using a rule-based method that is proven to be ef icient insolving issues such as the Natural Language to Structured QueryLanguage (NL2SQL) process. The results showed that the semanticparsing approach using the rule-based method succeeded in obtainingan accuracy rate of 96.72% using 122 test data in the formof questionsentences or command data about the Academic Information Systemof the Department of Informatics Engineering, Sriwijaya University inIndonesian, and an average execution time of 50.68 milliseconds. seconds or 0.05 seconds.
Generating Indonesian Poem: A Fine-Tunning Approach Using Pretrained GPT-2 Models Kusuma, Arya Mulya; Abdiansah, Abdiansah
Sriwijaya Journal of Informatics and Applications Vol 5, No 2 (2024)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v5i2.96

Abstract

In recent years, text generation has become an important subfield within Natural Language Processing (NLP), gaining significant attention and focus. Over the past decade, text generation technology has expanded significantly, reaching diverse application domains, especially in creative areas such as poem. Generating poetic content is a unique challenge that requires combining linguistic knowledge, creativity, and originality to craft each poem. This study focuses on developing a text generator for Indonesian language poem, using fine-tuning methodology with the pre-trained GPT-2 model from the Flax community. The study conducted a comparative analysis, benchmarking the performance of the researcher's model against a baseline model developed by Muhammad Agung Hambali. The evaluation outcomes showed the researcher's model outperformed the baseline model, exhibiting a 73.68% improvement in perplexity value. Furthermore, the study conducted a survey involving 62 respondents to determine the reception of the generated poem. The results indicated the poem produced by the research model was marginally superior to that of the baseline model. 
Co-Authors Abidullah, M. Dzawil Fadhol Adi Kurniawan Ahmad Fali Oklilas Ahmad Gustano Aidil Putrasyah Al Farissi Alfath, Ahmad Riyo Ali Ibrahim Alvi Syahrini Utami Amalia, Syavira Anny K. Sari Ari Firdaus Ari Wedhasmara Arrasyid, Muhammad Raihan Aruda, Syechky Al Qodrin Arya Mulya Kusuma Astero Nandito Azzahra, Firna Fatima Azzikra, Muhammad Adlan Cahyani, Nyimas Sabilina Dahlan, Bulan Fitri Deris Stiawan Dian Palupi Rini Dian Palupi Rini Dian Palupi Rini Dwiyono, Aswin Edi Winarko Elza Fitriana Saraswita Elza Fitriana Saraswita Ermatita - Erwin, Erwin Fathan, Fathir Fathoni - Febrian, Evan Frendredi Muliawan Hallatu, Nathania Calista Harisatul Aulia Hastie Audytra Hidayahni, Putri Husain, Sulaiman Al Illahi, Aripili Rahman Julian Supardi Kanda Januar Miraswan Kusuma, Arya Mulya Marcelio, Ch Angga Marcellino, Fernanditho Mastura Diana Marieska Maulana, Jimmy Megah Mulya Melati, Risma Mira Afrina Mufazzal, Dimas Putra Muhammad Afif Muhammad Alfaris Oktavian Muhammad Fachrurrozi Muhammad Ikhsan Muhammad Qurhanul Rizqie Muhammad Rizky Akbar Muwafa, Fadhil Zahran Nazuli, Muhammad Furqan Noprisson, Handrie Novi Yusliani Novran, Novran Permana, Dendi Renaldo Plakasa, Gerald Primanita, Anggina Putra, Erwin Dwika Putri Patricia Rabani, Diaz Dafa Ridho Putra Sufa Rizka Dhini Kurnia Saputra, Danny Mathew Saputra, Danny Matthew Satrio, Bagus Sihaloho, Mutiara Anastasya Siti Annisa, Siti Soraya, Atika Sri Hartati Yadi Utama Yudoyono, Vellanindhita Noorprameswari Zanzabili, Muhammad Reyhan