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All Journal CESS (Journal of Computer Engineering, System and Science) IJISTECH (International Journal Of Information System & Technology) IJISTECH
Rianda, Kiki Rizki
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

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Sistem Pendukung Keputusan Menggunakan Metode Fuzzy Mamdani Untuk Menentukan Badan Eksekutif Mahasiswa (BEM) Saleh, Khairul; Muhazir, Ahmad; Rianda, Kiki Rizki
CESS (Journal of Computer Engineering, System and Science) Vol 9, No 1 (2024): January 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i1.53341

Abstract

Badan Eksekutif Mahasiswa merupakan wadah dari seluruh mahasiswa untuk mengembangkan bakat dan kemampuan di Fakultas Teknik Universitas Asahan. Keberadaan ketua BEM selaku ketua organisasi merupakan suatu yang harus benar-benar di pertimbangkan dikarenakan ketua organisasi merupakan salah satu kunci keberhasilan dari suatu organisasi. Namun, dalam menentukan ketua BEM, Universitas Asahan belum memiliki sistem yang akurat dalam melakukan proses seleksi calon ketua BEM. Logika fuzzy merupakan suatu cara untuk memetakan masalah dengan tahapan-tahapan dari pembentukan himpunan fuzzy, pembentukan rule fuzzy dan proses inferensi madani. Tujuan penelitian ini yaitu dengan Logika fuzzy akan mendapatkan hasil yang akurat dan jelas dalam melakukan proses seleksi dalam Kasus penentuan Calon Ketua BEM sesuai variable yang sudah didapatkan.
Analysis of the Potential and Business Development Opportunities in Catfish Farming Using Artificial Neural Networks Rianda, Kiki Rizki; Apdillah, Dicky
IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i6.384

Abstract

In recent years, there has been a significant increase in catfish consumption. The average consumer demand reaches 50 to 100 kg with a catfish harvest age of about 2.5 months. Catfish farming has not only increased the income of the community but has also transformed those who previously had no knowledge of how to farm catfish and the potential of utilizing yard land into successful catfish farmers. In connection with this, the author intends to recognize more deeply the potential and opportunities of catfish farming in Air Hitam Village, Kualuh Leidong District. In this research, the author applies the Learning Vector Quantization (LVQ) method, which is one of the approaches in Artificial Neural Networks. Learning Vector Quantization (LVQ) is a competitive layer training technique with a supervised learning approach, which uses a network structure with a single layer. The use of Artificial Neural Network (ANN) is a sophisticated way that can be applied to manage catfish farming business. The results showed that the use of the LVQ method in analyzing catfish farming data can help farmers make more informed decisions, predict business development, and increase yields and profits.
Analysis of the Potential and Business Development Opportunities in Catfish Farming Using Artificial Neural Networks Rianda, Kiki Rizki; Apdillah, Dicky
IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i6.384

Abstract

In recent years, there has been a significant increase in catfish consumption. The average consumer demand reaches 50 to 100 kg with a catfish harvest age of about 2.5 months. Catfish farming has not only increased the income of the community but has also transformed those who previously had no knowledge of how to farm catfish and the potential of utilizing yard land into successful catfish farmers. In connection with this, the author intends to recognize more deeply the potential and opportunities of catfish farming in Air Hitam Village, Kualuh Leidong District. In this research, the author applies the Learning Vector Quantization (LVQ) method, which is one of the approaches in Artificial Neural Networks. Learning Vector Quantization (LVQ) is a competitive layer training technique with a supervised learning approach, which uses a network structure with a single layer. The use of Artificial Neural Network (ANN) is a sophisticated way that can be applied to manage catfish farming business. The results showed that the use of the LVQ method in analyzing catfish farming data can help farmers make more informed decisions, predict business development, and increase yields and profits.
Sistem Pendukung Keputusan Menggunakan Metode Fuzzy Mamdani Untuk Menentukan Badan Eksekutif Mahasiswa (BEM) Saleh, Khairul; Muhazir, Ahmad; Rianda, Kiki Rizki
CESS (Journal of Computer Engineering, System and Science) Vol. 9 No. 1 (2024): January 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i1.53341

Abstract

Badan Eksekutif Mahasiswa merupakan wadah dari seluruh mahasiswa untuk mengembangkan bakat dan kemampuan di Fakultas Teknik Universitas Asahan. Keberadaan ketua BEM selaku ketua organisasi merupakan suatu yang harus benar-benar di pertimbangkan dikarenakan ketua organisasi merupakan salah satu kunci keberhasilan dari suatu organisasi. Namun, dalam menentukan ketua BEM, Universitas Asahan belum memiliki sistem yang akurat dalam melakukan proses seleksi calon ketua BEM. Logika fuzzy merupakan suatu cara untuk memetakan masalah dengan tahapan-tahapan dari pembentukan himpunan fuzzy, pembentukan rule fuzzy dan proses inferensi madani. Tujuan penelitian ini yaitu dengan Logika fuzzy akan mendapatkan hasil yang akurat dan jelas dalam melakukan proses seleksi dalam Kasus penentuan Calon Ketua BEM sesuai variable yang sudah didapatkan.
Co-Authors Apdillah, Dicky Khairul Saleh Muhazir, Ahmad