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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Nusantara Journal of Computers and its Applications
Nur Aeni Widiastuti
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Other

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APLIKASI MOBILE PADA SENTRA INDUSTRI SENI PATUNG DAN UKIR DI DESA MULYOHARJO UNTUK MENINGKATKAN POTENSI PASAR Nur Aeni Widiastuti
NJCA (Nusantara Journal of Computers and Its Applications) Vol 3, No 1 (2018): Juni 2018
Publisher : Computer Society of Nahdlatul Ulama (CSNU) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36564/njca.v3i1.66

Abstract

Mulyoharjo is the center of wood sculpture and sculpture industry which is included in Jepara regency, Central Java. Mulyoharjo is now developed into a tourist village of creative industries that began to favor a lot of local and foreign tourists. Mulyoharjo has excellent potential such as sculpture or wood carving. Local tourists and foreign tourists need information about the carving industry in Mulyoharjo to be visited. But to find the carving industry in Mulyoharjo is still limited in the website that takes a long time in the search process. So to know the carving industry information is less effective and efficient. Utilization of the progress of smartphone technology is one solution to this problem. Therefore, researchers apply an information-based android mobile app that provides information about the potential of existing industries in Mulyoharjo Village, based on location/map. Development method used in making this application is waterfall method using the ionic framework which is devoted to building a hybrid mobile application with HTML5, AngularJS, and CSS. The development of this application in the form of images, data and map location is included into the firebase database so that application renewal becomes young, fast and efficient. Based on the assessment by the respondents as a whole, the New Jepara application scored 81.3% with criteria very feasible to use.Keywords: Mobile application, waterfall method, carving industry center.
Multiclass Sentiment Analysis of Electric Vehicle Incentive Policies Using IndoBERT and DeBERTa Algorithms Muhammad Bayu Nugroho; Akhmad Khanif Zyen; Nur Aeni Widiastuti
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9511

Abstract

The electric vehicle (EV) incentive policy in Indonesia has generated various public reactions, particularly on social media platforms. This study aims to classify public sentiment using the IndoBERT and DeBERTa transformer models. A total of 6,758 comments were collected from YouTube, filtered, preprocessed, and labeled into three sentiment categories: positive, negative, and neutral. From this, 1,711 clean data points were used and analyzed in two phases: before and after applying the Random Oversampling technique to address class imbalance. Model performance was evaluated using accuracy, precision, recall, F1-score, and training time. In the initial phase, IndoBERT achieved 96% accuracy with 603.71 seconds of training time, while DeBERTa reached 93% in 439.19 seconds. After balancing and applying 5-Fold Cross Validation, IndoBERT maintained 96% accuracy with balanced metric distribution, while DeBERTa recorded 93% accuracy. IndoBERT performed better in recognizing neutral sentiment, whereas DeBERTa was more time-efficient. These results highlight the effectiveness of local transformer models and data balancing techniques in improving sentiment classification performance on imbalanced datasets.
Co-Authors Akhmad Khanif Zyen Muhammad Bayu Nugroho