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All Journal Brilliance: Research of Artificial Intelligence Jurnal Pengabdian Masyarakat Bangsa
Ilham Sahputra
Universitas Malikussaleh, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Pengabdian Kepada Masyarakat: Implementasi Artificial Intelligence Generatif sebagai Upaya Peningkatan Literasi Digital di Sekolah Ilham Sahputra; Fadasrsyah Fadasrsyah; Bustami Bustami; Fauzan Fauzan; T Iqbal Faridiansyah; Defi Irwansyah
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 11 (2026): Januari
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i11.3766

Abstract

Perkembangan teknologi digital, khususnya AI Generatif, telah memotivasi sekolah untuk meningkatkan literasi digital peserta didik. Program pengabdian ini bertujuan mendampingi sekolah dalam memanfaatkan AI Generatif untuk meningkatkan literasi digital dan memperkenalkan prinsip etika penggunaan teknologi secara bertanggung jawab. Metode yang diterapkan meliputi survei kebutuhan, pelatihan, workshop interaktif, pendampingan di kelas, serta evaluasi dampak. Hasil menunjukkan peningkatan pemahaman siswa tentang AI, etika digital, dan kemampuan verifikasi informasi. Siswa dapat mengintegrasikan AI dalam materi ajar dan evaluasi secara lebih efisien, serta mengembangkan keterampilan berpikir kritis. Penggunaan AI juga meningkatkan efisiensi waktu pengerjaan tugas hingga 60-70% dan memperkaya pembelajaran melalui penjelasan kontekstual adaptif. Meskipun ada kendala teknis, program ini memberikan dampak positif signifikan, meningkatkan literasi digital secara holistik dan mendukung pembelajaran yang lebih inklusif dan kreatif.
Decision Support System for Potential Stock Selection Recommendations Using AHP and Profile Matching Methods Ilham Sahputra; Veri Ilhadi; Angga Pratama; Syukriah Syukriah; Tiara Minda Arifa
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.5981

Abstract

This study presents the design and implementation of a Decision Support System (DSS) aimed at facilitating the selection of potential banking stocks by novice investors. The system integrates two well-established decision-making methodologies: the Analytical Hierarchy Process (AHP) and Profile Matching. The objective is to provide a structured, data-driven approach that assists users in making informed and objective investment decisions based on critical financial performance indicators. These indicators include Price to Earnings Ratio (PER), Price to Book Value (PBV), Return on Assets (ROA), Return on Equity (ROE), Earnings Per Share (EPS), Book Value Per Share (BVPS), Debt Ratio (DR), and Dividend Yield (DY). In this system, AHP is employed to calculate the relative weight or importance of each financial criterion through pairwise comparisons, incorporating users judgment in the weighting process. Once the weights are determined, the Profile Matching method is used to assess and rank the alternative banking stocks based on how closely they align with the ideal profile defined by the criteria. The results of the analysis identified Bank Mandiri (BMRI) as the top-ranked stock, followed by Bank Rakyat Indonesia (BBRI) and Bank Central Asia (BBCA), indicating their strong fundamental performance according to the selected indicators. To validate the system's functionality, black-box testing was conducted on 21 different modules, all of which yielded valid outcomes. This confirms that the application operates correctly and reliably. Overall, the study concludes that the DSS is effective, user-friendly, and valuable as a decision support tool, especially for beginner investors targeting the banking sub-sector.
Co-Authors Angga Pratama Bustami Bustami Defi Irwansyah Fadasrsyah Fadasrsyah Fauzan Fauzan Syukriah Syukriah T Iqbal Faridiansyah Tiara Minda Arifa Veri Ilhadi