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All Journal Jurnal Penelitian Rumpun Ilmu Teknik Mutiara: Jurnal Penelitian dan Karya Ilmiah
Rini Andriani
Universitas Negeri Medan
Religion Humanities Computer Science & IT Electrical & Electronics Engineering 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.
Rancang Bangun Prototype Sistem Informasi Pipe Reporting Berbasis Web pada SKK Migas Rini Andriani; Samuel Anaya Putra Zai; Sindy Fitriani Margaret Sihaloho
Jurnal Penelitian Rumpun Ilmu Teknik Vol. 2 No. 4 (2023): November : Jurnal Penelitian Rumpun Ilmu Teknik
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juprit.v2i4.3016

Abstract

This research aims to develop an information system for 2 types of web-based Pipe Reporting, namely PVC Pipe Report and Steel Pipe Report which meets SKK Migas' needs in pipe data management. SKK Migas, as an institution managing oil and gas activities, requires an efficient and integrated solution for tracking, reporting and analyzing pipeline-related information. The proposed system is designed with a focus on ease of use, accessibility, and data reliability. The system development approach uses web-based technology to facilitate access from various locations. This research includes in-depth requirements analysis stages, measurable system architecture design, and prototype implementation. The success of the system is measured through increased efficiency in the pipeline data reporting, monitoring and analysis processes. It is hoped that the results of this research will not only meet SKK Migas' needs directly, but can also become a basis for developing similar systems in the oil and gas industry more broadly.
Co-Authors Rizki Risdah Sitorus Samuel Anaya Putra Zai Sindy Fitriani Margaret Sihaloho Yesika Syalomi Pasaribu