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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer EMITTER International Journal of Engineering Technology Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Knowledge Engineering and Data Science JICTE (Journal of Information and Computer Technology Education) Applied Information System and Management Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Information System,Graphics, Hospitality and Technology Teknika Journal of Applied Data Sciences International Journal of Engineering, Science and Information Technology Insyst : Journal of Intelligent System and Computation Jurnal Nasional Teknik Elektro dan Teknologi Informasi Eduvest - Journal of Universal Studies Jurnal Inovasi Teknologi dan Edukasi Teknik Bulletin of Social Informatics Theory and Application
Esther Irawati Setiawan
Institut Sains Dan Teknologi Terpadu Surabaya
Aerospace Engineering Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Transportation Other

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Journal : Journal of Applied Data Sciences

 1 
Long short-term memory-based chatbot for vocational registration information services Langgeng, Yudo Sembodo Hastoro; Setiawan, Esther Irawati; Imron, Syaiful; Santoso, Joan
Journal of Applied Data Sciences Vol 4, No 4: DECEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i4.128

Abstract

The development of chatbots can communicate fluently like humans thanks to the Natural Language Processing (NLP) technology. Using this technology, chatbots can provide more accurate and natural responses, providing an almost the same experience as human interaction. Therefore, chatbot technology is in great demand by companies and government agencies as a cost-effective solution for information and administrative services that require little human effort and can operate 24/7. The registration information service at BLK Surabaya still uses an operator who serves prospective trainees and answers questions via social media or chat. However, these operators have limitations in terms of time and effort. The purpose of this study is to examine how to use chatbots to answer questions about registration information training at BLK Surabaya using the Long Short Term Memory (LSTM) algorithm with a dataset of questions collected in the form of Frequently Asked Questions (FAQ) in Indonesian. The dataset consists of 2,636 labeled samples of questions, which were divided into three sets: 60% for training (1,581 pieces), 20% for validation (527 samples), and 20% for testing (528 samples) to evaluate the model's performance. Several steps were taken in implementing this research, including changing the list of questions and answers into the JSON data format, preprocessing, creating LSTM modeling, data training, and data testing. The test results show that Chatbot can provide accurate solutions related to training registration questions with Precision of 88.4%, Accuracy of 87.6%, and Recall of 87.3%.
Aspect-Based Sentiment Analysis of Healthcare Reviews from Indonesian Hospitals based on Weighted Average Ensemble Setiawan, Esther Irawati; Tjendika, Patrick; Santoso, Joan; Ferdinandus, FX; Gunawan, Gunawan; Fujisawa, Kimiya
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.328

Abstract

Public assessments are essential for evaluating hospital quality and meeting patient demand for superior medical treatment. This study offers a novel approach to aspect-based sentiment analysis (ABSA), which consists of aspect extraction, emotion categorization, and aspect classification. The goal is to examine patient reviews (6,711 reviews) from Google assessments of 20 Indonesian hospitals, broken down by categories including cost, doctor, nurse, and other categories. For example, there are 469 good, 66 negative, and 7 neutral ratings for cleanliness and 93 positive, 125 negative, and 19 neutral reviews for pricing in the sample, which covers a range of attitudes. Using the Conditional Random Field (CRF) approach, aspect phrase extraction was refined and word characteristics and positional tags were adjusted, resulting in an improvement in the F1-score from 0.9447 to 0.9578. The Support Vector Machine (SVM) model had the greatest F1-score of 0.8424 out of two strategies used for aspect categorization. With the addition of sentiment words, sentiment classification improved and led by SVM to an ideal F1-score of 0.7913. For aspect and sentiment classification, a Weighted Average Ensemble approach incorporating SVM, Naïve Bayes, and K-Nearest Neighbors was employed, yielding F1-scores of 0.7881 and 0.8413, respectively. The use of an ensemble technique for sentiment and aspect classification and the incorporation of hyperparameter optimization in CRF for aspect term extraction, which led to notable performance gains, are the innovative aspects of this work.
Co-Authors Adi Sutanto Adriel Ferdianto Aidil Aji Prasetya Wibawa Albertus Josef Andika Arif Priyambodo Arya Tandy Hermawan Christian Nathaniel Purwanto Dhaniswara, Erwin Edwin Pramana Edwin Pramana Effendy Hadi Sutanto Eko Mulyanto Yuniarno Endang Setyati F.X. Ferdinandus Fachrul Kurniawan Ferdinandus, F. X. Fitria Fitria Fujisawa, Kimiya Gunawan Gunawan Gunawan Halim, Kevin Jonathan Hans Juwiantho Hans Keven Budi Prakoso Harianto, Reddy Alexandro Harits Ar Rosyid Hartono, Luluk Setiawati Hartono, Patrick Heppi Siswanto Herman Budianto Herman Thuan To Saurik Honoris Setiahadi I Ketut Eddy Purnama Ika Lestari Imron, Syaiful Joan Santoso Johanes, Sugiharto Kimiya Fujisawa Kristian, Yosi Langgeng, Yudo Sembodo Hastoro Leonel Hernandez Lim, Ernest Lukman Zaman Machfudin, Mohammad Farid Mauridhi Hery Purnomo Mauridhi Hery Purnomo Mohamad Fahmi Yusuf Muhammad Arief Rahman Mustaqin, Farhan Faisal Zainul Nagari, Widean Natalie, Valerynta Putra, Adi Surya Rachmatullah, Sholeh Rahmatullah, Dewangga Ramadhan Ramadhan Safitri, Lia Samuel Budi Wardhana Kusuma Santoso , Joan Saputra, Daniel Gamaliel Setya Ardhi Singh, Vrijraj Sugiono, Judi Prajetno Surya Sumpeno Syaiful Imron Syaiful Imron Titis Arwindarti Tjendika, Patrick Tjwanda Putera Gunawan Vu, Tong Nam Tuan Wardoyo, Nikko Riestian Putra Yosi Kristian Yuliana Yuliana YUNI YAMASARI Zaman, Lukman