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All Journal Antivirus : Jurnal Ilmiah Teknik Informatika Buletin Ilmiah Sarjana Teknik Elektro
Novia Ratnasari
Universitas Negeri Malang
Computer Science & IT Electrical & Electronics Engineering

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DECISSION SUPPORT SYSTEM DI AMERIKA: SEBUAH EKISTENSI GLOBAL DAN MASADEPAN Novia Ratnasari; Dhani Wahyu Wijaya; Akrom Tegar Khomeiny; Aji Prasetya Wibawa
Antivirus : Jurnal Ilmiah Teknik Informatika Vol 14 No 1 (2020): Mei 2020
Publisher : Universitas Islam Balitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/antivirus.v14i1.1139

Abstract

The Industrial Revolution in America was influenced by technological development to become a highly developed country. Information technology combined with the Decision Support System (DSS) is able to give a new face to the application of technology in several fields, including: 1). Industry; 2). Health; 3). Agriculture; 4). Living environment ; 5). Military; and 6). Education. DSS was known in 1970 due to limitations in the development of technology for the military field. However, gradually the development of DSS can be applied in several fields. In this study using the Systematic Literature Review method with 4 stages of research, including: a). Research Questions; b). Inclusion Criterl; c). Identification of Papers; and D). Conclusions are carried out by grouping according to categories in certain years, including: 1). 1980-1990; 2). 1990-2000; 3). 2000-2010; and 4). 2010-2020. This research outlines an analysis of how the development of the use of DSS in various fields from year to year in America can be used as a policy maker and evaluating the use of technological trends in several fields. The results of this study are. The conclusion of this research is the field of industry and the health field is more dominant in use in the decision support system. Because the decision support system is very needed in the field. And as the time goes by, the use of the decision support system is increasingly reduced, even in the year 2010 to 2020, the use of a decision support system is called as artificial intelligence. Because artificial intelligence technology includes a decision support system in it. And artificial intelligence has a broader meaning is not merely a decision support system.
Language as the Semantic Bridge in Audio, Music, and Multimodal Artificial Intelligence: A Systematic Review (2021-2025) Novia Ratnasari; Aji Prasetya Wibawa
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 2 (2026): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i2.15564

Abstract

This study presents a systematic review of research in Audio, Music, and Multimodal Artificial Intelligence published between 2021 and 2025, investigating how language operates as a semantic mediation layer between acoustic signals and high-level meaning. The research addresses the fragmentation of existing surveys by introducing a Domain; Modality; Technique; Task (D-M-T-T) taxonomy that systematically differentiates domain focus, modality configuration, modeling techniques, and task objectives. The research contribution is a structured analytical framework that offers a more granular perspective than architecture-centered surveys of Multimodal Large Language Models. Following the PRISMA 2020 protocol, 2,197 Scopus-indexed publications were screened, yielding 369 eligible studies. Language is defined as a representational layer encompassing natural language and structured symbolic encodings that connect acoustic embeddings to semantic interpretation and generative reasoning. Multimodal systems aligning audio and vision without explicit textual grounding are included and analyzed as non-linguistic alignment architectures within the taxonomy. The findings reveal a shift from recognition-based models toward unified multimodal systems in which language conditions alignment, reasoning, and generative synthesis. For instance, text-conditioned music generation demonstrates how linguistic prompts guide compositional structure and emotional expression. These developments reflect an epistemic transition from signal recognition paradigms to language-mediated generative intelligence. Emerging gaps include limited explainability in generative audio systems and insufficient low-resource cross-modal semantic grounding.
Co-Authors Aji Prasetya Wibawa Akrom Tegar Khomeiny Dhani Wahyu Wijaya