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All Journal Jurnal Syntax Imperatif : Jurnal Ilmu Sosial dan Pendidikan Journal of Artificial Intelligence and Engineering Applications (JAIEA) QISTINA: Jurnal Multidisiplin Indonesia
Fali, Rifki
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Religion Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Nursing Social Sciences

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Pentingnya Pemahaman Ideologi Pancasila dan Dampak Ketidaktahuan Terhadap Stabilitas Sosial Politik Sitorus, Andika; Fali, Rifki; Sarumaha, Matius Irvan; Putri, Safira Nazwa; Tarigan, Gabriel Frandika
JURNAL SYNTAX IMPERATIF : Jurnal Ilmu Sosial dan Pendidikan Vol. 5 No. 6 (2025): Jurnal Syntax Imperatif: Jurnal Ilmu Sosial dan Pendidikan
Publisher : CV RIFAINSTITUT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntaximperatif.v5i6.536

Abstract

Pancasila, sebagai dasar negara Indonesia, memegang peranan penting dalam kehidupan berwarga negara. Artikel ini bertujuan untuk menyoroti pentingnya pemahaman ideologi Pancasila dan bagaimana ketidaktahuan terhadapnya dapat mengancam stabilitas sosial dan politik. Metode penelitian yang digunakan meliputi pengumpulan data melalui form survei dan tinjauan pustaka. Form survei disebarkan untuk mengukur tingkat pemahaman masyarakat terhadap Pancasila dan dampaknya terhadap perilaku berwarga negara. Tinjauan pustaka dilakukan untuk mengkaji literatur yang relevan tentang ideologi Pancasila dan implikasinya dalam konteks sosial-politik. Hasil penelitian menunjukkan bahwa pemahaman yang rendah terhadap Pancasila berpotensi menimbulkan konflik sosial dan mengurangi kohesi nasional. Artikel ini menyarankan pentingnya edukasi Pancasila yang lebih intensif dan integrasi nilai-nilai Pancasila dalam kehidupan sehari-hari untuk menjaga stabilitas sosial dan politik. Temuan ini memberikan wawasan bagi pembuat kebijakan dan pendidik untuk memperkuat pemahaman ideologi Pancasila demi menjaga keutuhan dan kedamaian bangsa Indonesia
Design of Desktop-Based Student Learning Style and Personality Quiz Application with Microsoft Visual Basic Net 8.0 Syahputra, Fahmy; Putri, Tansa Trisna Astono; Fali, Rifki; Tanzila, Laili; Sarumaha, Matius Irvan; Zai, Frans Pratamarifai Doya
QISTINA: Jurnal Multidisiplin Indonesia Vol 3, No 2 (2024): December 2024
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/qistina.v3i2.4222

Abstract

In education, learning style and personality play an important role because they influence how individuals perceive and absorb information. Educators can build more inclusive and successful learning environments by implementing strategies to accommodate a variety of learning styles and personalities. The learning style and personality quiz application was created with Microsoft Visual Basic 8.0. The purpose of this application is to find out the learning style and personality of students. By knowing their learning style and personality, students can understand themselves and make it easier to choose the learning method to use. The method used in designing this application is the waterfall method. The method begins with the analysis, design, coding, testing and maintenance stages. The learning style and personality quiz application has been tested on several students of the Information Technology and Computer Education Study Program, Medan State University for three weeks, the results show that the learning style and personality quiz application can help in selecting effective learning methods and understanding one's own character.
Literature Review: Transitioning usage from BFS and DFS to Heuristic Search in the Modern AI Era Syahputra, Fahmy; Sabrina, Elsa; Sahendra Chan, M Fajar; Fali, Rifki; Fattah, Muhammad; Hendratmo, Joko; Ardiansyah, Fadhil
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1856

Abstract

Uninformed search algorithms, specifically Breadth-First Search (BFS) and Depth-First Search (DFS), encounter significant scalability limitations when addressing complex problem spaces in modern Artificial Intelligence (AI) ecosystems. This study investigates the paradigm shift toward intelligent heuristic algorithms through a systematic literature review and comparative analysis of 24 recent academic sources. The evaluation focuses on three primary domains: logical problem solving, robotic navigation, and data infrastructure management. Results demonstrate that heuristic methods, such as A-Star and hybrid variants like PrunedBFS, offer superior time efficiency and memory optimization for autonomous navigation and massive computing tasks. Nevertheless, classic algorithms retain functional relevance for specific scenarios requiring exhaustive exploration. Furthermore, this study reveals that algorithmic evolution has fundamentally transformed digital infrastructure, driving a shift from Search Engine Optimization (SEO) to Answer Engine Optimization (AEO) and necessitating adaptive cybersecurity architectures. The research concludes that the future of AI development relies not on substitution, but on a collaborative synthesis integrating the robustness of classic methods with the adaptability of modern heuristics.
Co-Authors Ardiansyah, Fadhil Fattah, Muhammad Hendratmo, Joko Putri, Safira Nazwa Putri, Tansa Trisna Astono SABRINA, ELSA Sahendra Chan, M Fajar Sarumaha, Matius Irvan Sitorus, Andika Syahputra, Fahmy Tanzila, Laili Tarigan, Gabriel Frandika Zai, Frans Pratamarifai Doya