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All Journal Mutiara: Jurnal Penelitian dan Karya Ilmiah
Rizki Risdah Sitorus
Universitas Negeri Medan
Religion Humanities Computer Science & IT Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Other

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Penggunaan Algoritma CNN untuk Mengidentifikasi Jenis Anjing Menggunakan Metode Supervised Learning: Penggunaan Algoritma CNN untuk Mengidentifikasi Jenis Anjing Menggunakan Metode Supervised Learning Rini Andriani; Rizki Risdah Sitorus; Samuel Anaya Putra Zai; Yesika Syalomi Pasaribu
Mutiara : Jurnal Penelitian dan Karya Ilmiah Vol. 1 No. 6 (2023): Desember: Mutiara : Jurnal Penelitian dan Karya Ilmiah
Publisher : STAI YPIQ BAUBAU, SULAWESI TENGGARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59059/mutiara.v1i6.741

Abstract

Penelitian ini bertujuan membangun model Convolutional Neural Network (CNN) untuk mengklasifikasi 5 jenis anjing populer yaitu Siberian Husky, Samoyed, Dalmatians, Schnauzer dan Bull Terrier berdasarkan citra digital. Metode supervised learning digunakan dengan dataset 250 gambar yang terdiri dari 50 gambar tiap kelas. Data latih sebanyak 90% dan data uji 10%. Model CNN terbaik menghasilkan akurasi 72% dalam mengklasifikasi kelima jenis anjing. Hasil ini menunjukkan CNN cukup handal mengenali perbedaan visual masing-masing ras anjing meski masih perlu peningkatan kualitas data latih.
Penerapan Metode K-Means Clustering pada Hasil Produksi Beras di Wilayah Sumatera Utara Rizki Risdah Sitorus; Rafiqi Aidil Fitra
Mutiara : Jurnal Penelitian dan Karya Ilmiah Vol. 1 No. 6 (2023): Desember: Mutiara : Jurnal Penelitian dan Karya Ilmiah
Publisher : STAI YPIQ BAUBAU, SULAWESI TENGGARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59059/mutiara.v1i6.749

Abstract

This research aims to apply the method K-Means Clustering on rice production results in the region North Sumatra. K-Means Clustering is a data analysis technique that is useful for grouping data into several groups based on similar characteristics. This research uses rice production data from several districts/cities in North Sumatra as samples. The K Means method is used to group these regions into several clusters based on rice production they. The research results show that the K Means Clustering method can be used for identification rice production patterns in the North Sumatra region. The hope is, research results can be a valuable contribution, provide recommendations, and support initiatives for the North Sumatra provincial government in improving rice production throughout the region, with the aim of ensuring a more stable food supply for the community.
Co-Authors Rafiqi Aidil Fitra Rini Andriani Samuel Anaya Putra Zai Yesika Syalomi Pasaribu