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APLIKASI KAMUS ELEKTRONIK BAHASA ISYARAT BAGI TUNARUNGU DALAM BAHASA INDONESIA BERBASIS WEB Yuli Fauziah; Bambang Yuwono; Cornelius DWP
Telematika Vol 9, No 1 (2012): Edisi Juli 2012
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v9i1.297

Communication is the key to conquering this globalization era. And there is no doubtthat the language is the most important part of communication. One can communicate wellwhen using the same language or understanding the language used to each other.Signlanguage is the language of communication priority manually, body language and lip motion incommunicating. Sign language has been standardized by the name Sibi (Cue SystemIndonesian). Sibi is one of the media in the form of books, can help communication among thedeaf in the community. His form is setting a systematic set of fingers, hands, and othermovements that symbolize Indonesian vocabulary. Media book seems less easily understoodby the user, so the need for an application that is able to provide an image that is moving,making it easier to learn the sign language.Keywords: Communication, Systems cues Indonesian language, Sign Language

Knowledge representation of drug using ontology alignment and mapping techniques Herlina Jayadianti; Alisya Amalia Putri Hasanah; Yuli Fauziah; Shoffan Saifullah
Science in Information Technology Letters Vol 2, No 1: May 2021
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v2i1.561

Drug searches are still based on drug names and brands, making it difficult for patients to come looking for a cure by saying that they feel sick. Likewise, when looking for drugs and information about their content to avoid overdose errors when changing drugs when drugs are supposed to be unavailable. Based on the issues raised, a study was conducted on applying semantic web ontology to search for drugs that can appear based on patients’ names, compositions, or complaints of diseases. Protégé 5.5 serves to represent drug information based on knowledge. The application uses Netbeans with Jena API as a library and creates data and drug information on the semantic web. Drug search also uses similar in-formation meaning based on user knowledge. By representing knowledge on the search for drug and disease information with semantic web ontology technology, it can meet the purpose of research, namely to improve drug and disease information search following the user’s wishes.

PENDAMPINGAN UMKM KWT SUKA MAJU UNTUK MENINGKATKAN PRODUKSI DAN PEREKONOMIAN MASYARAKAT DUSUN PALIHAN Heriyanto Heriyanto; Yuli Fauziah; Dyah Ayu Irawati
Dharma: Jurnal Pengabdian Masyarakat Vol 1, No 2 (2020): November
Publisher : Universitas Pembangunan Nasional "Veteran" Yogyakarta

The SUKAMAJU Women's Farmer Group (KWT) is a group of women craftsmen of banana tree processing. During the Covid-19 pandemic, sales and marketing of processed banana food were very limited. Online marketing in times of the Covid-19 pandemic is urgently needed and requires support. Community service from UPN Veteran Yogyakarta, in this case, is programmed to help solve problems during the pandemic. Marketing through the internet and social media is very much needed, while the ability of mothers to master social media and the internet is very limited. The service team from UPN Veteran Yogyakarta is trying to help with solutions going into the field to help provide full assistance and also assistance for production equipment so that food processing craftsmen maintain production in KWT. The hope of the community service team is that there will be an increase in sales results by providing full assistance in both marketing media and increasing production equipment with an average increase of 8-9 pieces per day.

Enhancing Sentiment and Emotion Classification with LSTM-Based Semi-Supervised Learning Husaini, Rochmat; Cahyana, Nur Heri; Wisnalmawati, Wisnalmawati; Mardiana, Tri; Fauziah, Yuli
Compiler Vol 14, No 1 (2025): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i1.2965

The evolution of sentiment analysis has increasingly relied on semi-supervised learning (SSL) models, particularly due to their efficiency in utilizing large amounts of unlabeled data. This study employed four Indonesian datasets—Ridife (sentiment classification), Emotion Indonlu (emotion classification), Sentiment Indonlu (sentiment classification), and Hate Speech (offensive content detection). The LSTM model was trained using labeled data and used to generate pseudo-labels for unlabeled data across three iterations. The performance of the pseudo-labels was evaluated using Random Forest, Logistic Regression, and Support Vector Machine (SVM). The LSTM model demonstrated varying effectiveness across different datasets. For the Sentiment Ridife dataset, LSTM achieved an accuracy of 70.23%, slightly lower than Random Forest but higher than Logistic Regression and SVM. In the Sentiment IndoNLU dataset, LSTM's accuracy was 86.12%, showing strong performance but slightly below Random Forest and Logistic Regression. The Emotion IndoNLU dataset revealed similar performance across models, while the Hate Speech dataset saw LSTM perform well with an accuracy of 86.49%. The results indicate that while LSTM-based SSL can effectively generate pseudo-labels and enhance model performance, its performance varies depending on the dataset and task. This study underscores the need for further research into optimizing pseudo-labeling techniques and exploring advanced NLP models to improve sentiment and emotion analysis in diverse languages.

PENDAMPINGAN UMKM KWT SUKA MAJU UNTUK MENINGKATKAN PRODUKSI DAN PEREKONOMIAN MASYARAKAT DUSUN PALIHAN Heriyanto, Heriyanto; Fauziah, Yuli; Irawati, Dyah Ayu
Dharma: Jurnal Pengabdian Masyarakat Vol. 1 No. 2 (2020): November
Publisher : Universitas Pembangunan Nasional "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/dlppm.v1i2.4043

The SUKAMAJU Women's Farmer Group (KWT) is a group of women craftsmen of banana tree processing. During the Covid-19 pandemic, sales and marketing of processed banana food were very limited. Online marketing in times of the Covid-19 pandemic is urgently needed and requires support. Community service from UPN Veteran Yogyakarta, in this case, is programmed to help solve problems during the pandemic. Marketing through the internet and social media is very much needed, while the ability of mothers to master social media and the internet is very limited. The service team from UPN Veteran Yogyakarta is trying to help with solutions going into the field to help provide full assistance and also assistance for production equipment so that food processing craftsmen maintain production in KWT. The hope of the community service team is that there will be an increase in sales results by providing full assistance in both marketing media and increasing production equipment with an average increase of 8-9 pieces per day.

Analysis Of Factors Affecting Interest Kai Access Application Users Using Models Unified Theory Of Acceptance And Use Of Technology 2 (UTAUT 2) Firmansyah, Rifki; Fauziah, Yuli; Perwira, Rifki Indra
Telematika Vol 20 No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.8482

Purpose: This study aims to analyze the factors that influence user interest in the KAI Access application using the Unified Theory Of Acceptance And Use Of Technology 2 (UTAUT 2) model.Methodology: This study used the Structural Equation Modeling (SEM) method with two tests, namely the outer model and the inner model with the help of the SmartPLS Version 3 software. A total of 406 respondent data were used from the Special Region of Yogyakarta and also users of the KAI Access application.Results: The results of the study show that of the fourteen hypotheses proposed in the study, only seven were accepted, namely social influence, facilitating conditions, hedonic motivation, price value, and habit. The strongest factors that have a significant effect are hedonic motivation and habit.State of the art: based on previous research, this study has quite similar characteristics but different cases, variables, and research samples.

User Experience Analysis on Student Services Website using User Experience Questionnaire (UEQ) KPI and Importance Performance Analysis (IPA) (Case Study: UPN "Veteran" Yogyakarta) Wenerda, Vivo Putri; Fauziah, Yuli
Telematika Vol 20 No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.10216

Purpose: This study aims to obtain an end-user assessment of User Experience on the Student Services website so that it can be used as a priority material for improvement for the Bureau of Academic, Student Affairs, Planning, and Cooperation (AKPK) of the National Development University (UPN) "Veteran" Yogyakarta, when developing a website further.Design/methodology/approach: The User Experience Assessment on the Student Services website refers to 6 aspects of the assessment of the User Experience Questionnaire (UEQ) KPI method. The existing results will be mapped into an IPA (Importance Performance Analysis) diagram.Findings/result: The results of user experience testing on the Student Services website using the UEQ method, get the Good category for the Efficiency (1.56) and Dependability (1.57) aspects, the Above average category for the Attractiveness aspect (1.28), Perspicuity (1.57), and Stimulation (1.15) and the Bad category on Novelty (-0.27). Mapping the results of the UEQ KPI to the IPA quadrant, getting the results of the Attractiveness, Perspicuity, Efficiency, and Dependability aspects are in Quadrant 1, the Stimulation aspect is in Quadrant 2, the Novelty aspect is in Quadrant 3, and no aspect is in Quadrant 4. Based on the results of the study, it can be concluded that the user experience value of the end user is good. Recommendations for improvement priorities for the Student Services website can further prioritize Novelty aspels that are in Quadrant 3 and in Bad condition.Originality/value/state of the art: The focus of this research is the same as previous research, namely analyzing User Experience with reference to the assessment aspects of the KPI User Experience Questionnaire (UEQ) and IPA (Importance Performance Analysis) methods. The difference that can be seen in this study is from the implementation of the method into different case studies with the objectives and urgency and problems described in accordance with the existing research object.

Analysis of Factors Affecting Intention to Use and User Satisfaction of Paylater Using DeLone & McLean Adoption Model Utari, Ulil Azmi; Fauziah, Yuli
Telematika Vol 20 No 3 (2023): Edisi Oktober 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i3.10643

Purpose: This study aims to determine the factors that affect the intention to use and satisfaction of GoPayLater users in Yogyakarta, by assessing the relationship between variables so that recommendation for improvent can be given.Design/methodology/approach: This study uses the DeLone & McLean adoption model by Seddon which includes 5 constructs namely system quality, information quality, perceived usefulness, intention to use and user satisfaction. Primary data collection was conducted by distributing questionnaires using likert scale measurement to 128 GoPayLater users. The data analysis technique used is SEM-PLS to test the measurement model, structural model and test the hypothesis via SmartPLS software.Findings/results:Based on the results of hypothesis testing in this study, two hypotheses were rejected from eight hypothesises. These findings indicate that perceived usefulness has a positive and significant effect on intention to use, while the variables of system quality and information quality do not have a significant effect directly on intention to use GoPayLater. The R-Square test results show that system quality, information quality and perceived usefulness simultaneously have an effect of 34,4% on intention to use GoPayLater. This study also proves that variables of system quality, information quality and perceived usefulness have a positive and significant effect on GoPayLater user satisfacion, with the level of influence given simultaneously is 51,7% .Originality/value/state of the art: Several previous studies have tested GoPayLater from various aspects, but no research has been found that assesses the relationship and effect of system quality, information quality and perceived usefulness on intention to use and user satisfaction using the DeLone & McLean adoption model by Seddon.

The Evaluation of Effects of Oversampling and Word Embedding on Sentiment Analysis Cahyana, Nur Heri; Fauziah, Yuli; Wisnalmawati, Wisnalmawati; Aribowo, Agus Sasmito; Saifullah, Shoffan
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1077

Generally, opinion datasets for sentiment analysis are in an unbalanced condition. Unbalanced data tends to have a bias in favor of classification in the majority class. Data balancing by adding synthetic data to the minority class requires an oversampling strategy. This research aims to overcome this imbalance by combining oversampling and word embedding (Word2Vec or FastText). We convert the opinion dataset into a sentence vector, and then an oversampling method is applied here. We use 5 (five) datasets from comments on YouTube videos with several differences in terms, number of records, and imbalance conditions. We observed increased sentiment analysis accuracy with combining Word2Vec or FastText with 3 (three) oversampling methods: SMOTE, Borderline SMOTE, or ADASYN. Random Forest is used as machine learning in the classification model, and Confusion Matrix is used for validation. Model performance measurement uses accuracy and F-measure. After testing with five datasets, the performance of the Word2Vec method is almost equal to FastText. Meanwhile, the best oversampling method is Borderline SMOTE. Combining Word2Vec or FastText with Borderline SMOTE could be the best choice because of its accuracy score and F-measure reaching 91.0% - 91.3%. It is hoped that the sentiment analysis model using Word2Vec or FastText with Borderline SMOTE can become a high-performance alternative model.

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