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INDONESIA
MEANS (Media Informasi Analisa dan Sistem)
Published by Universitas Katolik Santo Thomas
ISSN : 25486985     EISSN : 25993089     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal MEANS berdiri sejak Tahun 2016 dengan SK dari LIPI yaitu p-ISSN : 2548-6985 (Print) dan e-ISSN : 2599-3089 (Online) Terbit dua kali setiap Tahunnya yaitu Periode I Bulan Juni dan Periode II Bulan Desember Hasil Plagirisme Maksimal 25%, Lebih dari 25% Artikel Tidak Bisa Publish. Ruang lingkup publikasi ini adalah untuk bidang Ilmu Komputer seperti : 1. Sistem Informasi 2. Manajemen dan Audit Sistem Informasi 3. Aplikasi Dekstop 4. Web dan Mobile 5. Sistem Pendukung Keputusan 6. Sistem Pakar 7. Pembelajaran berbasis Komputer 8. Kriptografy 9. Bidang Ilmu Koputer yang lainnya.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 12 Documents
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Search results for , issue "Volume 10 Nomor 1" : 12 Documents clear
Estimasi Daya Keluaran Fotovoltaik Menggunakan Algortima Genetik Bago, Sri Intan; Irwanto, Muhammad
MEANS (Media Informasi Analisa dan Sistem) Volume 10 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

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Abstract

The development of renewable energy systems is a major focus in efforts to reduce environmental impacts and dependence on fossil energy sources. One promising renewable energy source is solar energy, which can be utilized through photovoltaic technology. However, to increase the efficiency of the photovoltaic system, an accurate estimate of the output power produced is required. This study aims to develop a photovoltaic output power estimation model using MATLAB-based Genetic Algorithm (GA). Genetic Algorithm was chosen because of its ability to find optimal solutions to a problem using the principles of natural selection. In this study, parameters that affect the performance of the photovoltaic system, such as sunlight intensity, cell temperature, and panel tilt angle, will be analyzed and modeled. The results of this photovoltaic output power estimation model are expected to provide more accurate predictions, so that they can be used for decision making in the planning and development of solar energy systems. Through simulation and data analysis, this study is expected to make a significant contribution to the development of photovoltaic technology in Indonesia and increase the efficiency of its use. Keyword : Photovoltaik, Output power, Genetic Algorithm, MATLAB, Renewable Energy
Optimalisasi Pemilihan Lapangan Badminton: Integrasi Metode SAW dan AHP dalam Sistem Pendukung Keputusan Lestariningsih, Endang; Nadila, Latifia; Handoko, Widiyanto Tri; Amin , Imam Husni Al
MEANS (Media Informasi Analisa dan Sistem) Volume 10 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Badminton is one of the most popular sports in the world, with Indonesia having achieved great success in international competitions. The high level of public interest in this sport requires the availability of adequate court facilities. However, the comfort of badminton court facilities still varies, so a decision support system is needed to help select the optimal court. This study develops a decision support system based on the integration of the Simple Additive Weighting (SAW) and Analytical Hierarchy Process (AHP) methods. SAW is used for criterion weighting, while AHP is applied in the ranking stage of alternatives. This combination of methods was chosen due to its ability to process qualitative data from player and athlete evaluations, as well as quantitative court data, while addressing complex issues through hierarchy-based prioritisation. The results of the study indicate that the system is capable of consistently weighting criteria (CR < 0.1). This study also produced a ranking of badminton courts in North Brebes based on seven criteria (price, floor type, lighting, bathrooms, scoreboards, cooperatives, and parking lots) and identified priority facilities. Court 33 in Brebes was selected as the best alternative with a preference value of 0.7485.

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