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All Journal Brilliance: Research of Artificial Intelligence Jurnal Pengabdian Masyarakat Bangsa
Syukriah Syukriah
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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PKM Pemberdayaan Masyarakat melalui Pendampingan Teknologi IoT dalam Pemantauan Kualitas Air Kolam berbasis Ramah Lingkungan Teuku Multazam; Syukriah Syukriah; Asran Asran; Edi Yusuf; Ezwarsyah Ezwarsyah; Mochamad Ari Saptari
Jurnal Pengabdian Masyarakat Bangsa Vol. 4 No. 5 (2026): Juli
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v4i4.4562

Abstract

Kegiatan Pengabdian kepada Masyarakat ini bertujuan untuk meningkatkan kapasitas Kelompok Pembudidaya Ikan (Pokdakan) Mina Ujong Blang, Kecamatan Muara Dua, Kota Lhokseumawe dalam pemanfaatan teknologi Internet of Things (IoT) untuk pemantauan kualitas air kolam budidaya ikan secara real-time. Permasalahan utama mitra adalah masih terbatasnya sistem monitoring kualitas air yang dilakukan secara manual sehingga proses pengambilan keputusan bersifat reaktif dan kurang akurat. Metode pelaksanaan kegiatan meliputi implementasi sistem IoT berbasis sensor suhu, pH, kekeruhan, dan oksigen terlarut, pendampingan penggunaan sistem, serta evaluasi peningkatan pemahaman mitra. Hasil kegiatan menunjukkan bahwa sistem IoT yang diterapkan mampu memberikan data kualitas air secara real-time dan meningkatkan efektivitas monitoring kolam. Selain itu, terjadi peningkatan kemampuan mitra dalam mengoperasikan sistem digital serta perubahan pola pengelolaan budidaya dari berbasis pengalaman menjadi berbasis data. Dengan demikian, kegiatan ini berkontribusi dalam meningkatkan efisiensi pengelolaan budidaya ikan sekaligus mendorong penerapan teknologi digital yang lebih ramah lingkungan dan berkelanjutan.
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 Asran Asran Edi Yusuf Ezwarsyah Ezwarsyah Ilham Sahputra Mochamad Ari Saptari Teuku Multazam Tiara Minda Arifa Veri Ilhadi