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All Journal Jurnal Sains dan Teknologi Jurnal Informatika Ekonomi Bisnis Jurnal Informatika Ekonomi Bisnis
Deri Marse Putra
Universitas Putra Indonesia YPTK Padang
Computer Science & IT Economics, Econometrics & Finance Education

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MULTIPLE LINEAR REGRESSI PADA FUZZY NEURAL NETWORK (FNN) PENENTUAN KUALITAS DAGING SAPI Musli Yanto; Syafri Arlis; Deri Marse Putra
JST (Jurnal Sains dan Teknologi) Vol. 11 No. 1 (2022)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (520.682 KB) | DOI: 10.23887/jstundiksha.v11i1.38267

Abstract

Tujuan penelitian ini membahas proses identifikasi kualitas daging sapi dengan implementasi metode multiple linear regressi (MLR) pada fuzzy neural network (FNN). Metode ini dikembangkan untuk menyempurnakan proses identifikasi yang sudah ada sebelumnya. MLR mampu melakukan proses pengukuran korelasi variable (X) dengan hasil keluaran (Y). Pendekatan dalam proses analisis tersebut menggunakan pendekatan kuantitatif untuk melakukan pengukuran dari beberapa aspek indikator yang digunakan dalam penentuan kualitas daging sapi.  Berdasarkan hasil uji korelasi dengan MLR membuktikan bahwa variabel kandungan zat kimia (X1), bau (X2), warna (X3), dan tekstur daging (X4) menghasilkan hubungan yang signifikan terhadap kualitas daging sapi (Y) dengan nilai sebesar 96.5%. Hasil analisis MLR mampu memberikan gambaran indikator variable yang tepat dalam proses analisis. Keluaran FNN juga menyajikan hasil yang cukup akurat dengan nilai sebesar 99.88%. Dengan hasil keluaran yang didapat, maka secara keseluruhan dapat disimpulkan bahwa model analisis MLR dan FNN memberikan hasil analisis dengan tingkat akurasi yang lebih baik dan efektif. Hasil tersebut mampu memberikan implikasi berupa sebuah rekomendasi dalam bentuk pengetahuan dan informasi yang didapat kepada masyarakat guna menentukan daging sapi yang baik dikonsumsi.
Objektivitas Sumber Daya Dosen Menggunakan Metode Weight Product Deri Marse Putra; Gunadi Widi Nurcahyo
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 1 (2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (273.777 KB) | DOI: 10.37034/infeb.v2i1.20

Abstract

Lecturers as one of the human resources who have an important role in higher education activities need to be maintained the quality of their performance. One of the activities carried out is evaluating and ranking lecturers to improve the quality of performance. There needs to be a Decision Support System that can help in assessing and evaluating lecturer performance. One method in decision support is the Weight Product Method. The purpose of this research is to create a decision support system to determine the best lecturers and rank of each lecturer. The subjects of this study were lecturers at Putra Indonesia University YPTK Padang using a data sample of 5 lecturers. Data collection techniques used in this study were observation and interviews. Comparison of the results of calculations carried out manually with the results of calculations using the Weight Product method of 5 sample data used found the best lecturer with a vector V value of 0.0819. This decision support system was created using the PHP programming language and MySQL database. So that this research is more efficient because the time required in the calculation is shorter and produces the best lecturer choice that matches the criteria.
Objektivitas Sumber Daya Dosen Menggunakan Metode Weight Product Deri Marse Putra; Gunadi Widi Nurcahyo
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 1 (2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (273.777 KB) | DOI: 10.37034/infeb.v2i1.20

Abstract

Lecturers as one of the human resources who have an important role in higher education activities need to be maintained the quality of their performance. One of the activities carried out is evaluating and ranking lecturers to improve the quality of performance. There needs to be a Decision Support System that can help in assessing and evaluating lecturer performance. One method in decision support is the Weight Product Method. The purpose of this research is to create a decision support system to determine the best lecturers and rank of each lecturer. The subjects of this study were lecturers at Putra Indonesia University YPTK Padang using a data sample of 5 lecturers. Data collection techniques used in this study were observation and interviews. Comparison of the results of calculations carried out manually with the results of calculations using the Weight Product method of 5 sample data used found the best lecturer with a vector V value of 0.0819. This decision support system was created using the PHP programming language and MySQL database. So that this research is more efficient because the time required in the calculation is shorter and produces the best lecturer choice that matches the criteria.
Co-Authors Gunadi Widi Nurcahyo Musli Yanto Syafri Arlis