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All Journal JTP - Jurnal Teknologi Pendidikan BHAKTI PERSADA Jurnal Aplikasi IPTEKS (Journal of Applied Sciences and Technology) Bulletin of Social Informatics Theory and Application
Dewinta Ayuni, Ni Wayan
P3M Politeknik Negeri Bali
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Nursing Public Health Social Sciences Transportation

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Predicting financial distress of property and real estate companies using optimized support vector machine - particle swarm optimization (SVM-PSO) Ayuni, Ni Wayan Dewinta; Lasmini, Ni Nengah; Dewi, Kadek Cahya
Bulletin of Social Informatics Theory and Application Vol. 8 No. 1 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i1.667

Abstract

Financial distress is a critical phenomenon in a company that has significant implications for the business itself, employees, investors, and creditors, and can also impact the economy of a country. Predicting the financial distress of a company, including property and real estate companies, becomes one of the crucial things to be studied. The Support Vector Machine (SVM) is said to be the most effective model for prediction and classification among other machine learning methods. However, it is difficult to determine the parameters of the SVM model. Thus, the SVM model's parameters must be improved for higher accuracy results. This research aims to increase the accuracy of the SVM model in predicting the financial distress of property and real estate companies. The optimization method used is Particle Swarm Optimization (PSO). PSO is one of the most well-known techniques for enhancing SVM parameters. The PSO approach takes its cues from how a group of insects or birds interacts to maintain life. Initialized in a D-dimensional search space, the PSO algorithm uses a population of random particles that are considered as points. Each particle modifies its direction using the best experience it discovers (pbest) and the best experience discovered by all other members (gbest) to arrive at the ideal outcome. As a result, throughout the search process, particles will move through multidimensional space to more advantageous locations. The result of this research showed that the SVM model has the highest accuracy at 80.47% while when the PSO method was implemented in the SVM model, the accuracy increased into 83.16%. It can be concluded that the PSO method successfully optimized the parameters and increased the accuracy of SVM model in predicting the financial distress of property and real estate companies listed in Indonesian Stock Exchange.
Optimalisasi Objek Wisata Edukasi di Dusun Petapan Kabupaten Klungkung Ciptayani, Putu Indah; Ayuni, Ni Wayan Dewinta; Kariati, Ni Made; Adiaksa, I Made Anom
Bhakti Persada Jurnal Aplikasi IPTEKS Vol. 8 No. 1 (2022): Bhakti Persada Jurnal Aplikasi IPTEKS
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/bp.v8i1.46-52

Abstract

Dusun Petapan merupakan salah satu dusun di Desa Aan yang terletak di Kabupaten Klungkung. Desa Aan memiliki potensi wisata yang sedang dikembangkan, akan tetapi pengelolaan kawasan belum optimal. Tujuan dari kegiatan pengabdian ini adalah mengoptimalkan objek wisata yang telah ada dengan membangun infrastruktur wisata edukasi. Metode pelaksanaan kegiatan meliputi sosialisasi, penyiapan lokasi, pengerjaan pembangunan, pemantauan lapangan dan evaluasi. Hasil dari kegiatan ini berupa dipasangnya papan penunjuk objek wisata, papan nama objek wisata, wahana permainan edukasi anak-anak dan penataan jalan menuju kawasan wisata. Survey yang dilakukan menunjukkan persepsi masyarakat terhadap objek wisata sebesar 78%, dengan tiga aspek yang masih perlu ditingkatkan yaitu variasi permainan edukasi (75%), papan penunjuk (69%) dan staf (65%).
Interactive Animation Learning Media on Android as a Creative Learning in Regression Analysis Topic Ayuni, Ni Wayan Dewinta
JTP - Jurnal Teknologi Pendidikan Vol. 24 No. 1 (2022): Jurnal Teknologi Pendidikan
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jtp.v24i1.22567

Abstract

Technology has a significant role to build the quality of education which is one of the world’s purpose in sustainable development goals in 2015-2030 by United Nations. The implementation of technology in education is to develop the learning media. The purpose of this study is to create interactive animation learning media that can be accessed using Android Smartphone as one of creative learning alternative in online learning. This media was applied in Statistics Subject, Regression Analysis Topic, Accounting Department of Politeknik Negeri Bali. The method used in this research was research and development (R&D). There were some steps in this research which are (1) planning and designing; (2) production and editing; (3) validating and revision; (4) implementation; and (5) evaluation step. The first step was planning and designing. In this step, the animation characters, background, color theme, and storyboard were determined. The next step was production and editing step. After that the validation steps were done. There were three validators in this research, which were Statistics Expert, Statistics Lecturer, and Media expert. The validation score of this media was 95.33 that was classified as a very good learning media and proper to be implemented. The next step was revising step as the validators’ suggestion. The learning media then was implemented in experiment class using hybrid learning environment. And as the last step, the evaluation step was done by comparing the analysis test score of experiment class and the control class. The method used in evaluation step was two independent sample t-test. As conclusion, this media can improve the ability of student in Statistical Analysis.
Co-Authors Adiaksa, I Made Anom Kadek Cahya Dewi Kariati, Ni Made Lasmini, Ni Nengah Putu Indah Ciptayani