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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika KOMPUTEK Jurnal Komtekinfo
Darnis, Febriyanti
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Optimasi Perutean Jalur Kendaraan Terdekat Traveling Salesman Problem dengan Artificial Bee Colony Algorithm Setiadi, Teguh; Darnis, Febriyanti; Ilhami, Susanti Dwi
Jurnal KomtekInfo Vol. 11 No. 2 (2024): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v11i2.502

Abstract

Pada penelitian ini membahas tentang Algoritma Bee Colony Optimization (Optimasi Koloni Lebah) untuk permasalahan travelling salesman. Optimasi ABC adalah algoritma pencarian berbasis populasi yang menerapkan konsep interaksi sosial untuk pemecahan masalah. biologis ini fenomena ketika diterapkan pada proses masalah perencanaan jalur untuk kendaraan, ditemukan unggul dalam kualitas solusi serta waktu komputasi. Simulasi telah digunakan untuk mengevaluasi banyaknya jalur yang ditemukan oleh Optimasi ABC. Efektivitas jalur telah dievaluasi dengan parameter seperti panjang jalur, waktu tempuh dengan Algoritma Koloni Lebah Buatan. Pembahasan pepergian penjual masalah untuk masalah rute kendaraan (Vehicle routing problem) VRP dioptimalkan dengan menggunakan metode tetangga terdekat; disajikan hasil evaluasi yang kemudian dibandingkan dengan algoritma koloni lebah buatan. Pendekatan yang ditempuh memberikan hasil terbaik untuk menemukan jalur terpendek dalam waktu sesingkat-singkatnya untuk bergerak menuju tujuan belanja. Dengan demikian diperoleh jarak optimal dengan lama waktu dengan cara yang lebih efektif.
Usability Testing on the Simponik Website using the System Usability Scale (SUS) Saputra, Deni; Ardiyan Syah, Edo; Darnis, Febriyanti
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 4 (2022): Article Research: Volume 6 Number 4, October 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i4.11916

Abstract

SIMPONIK is one of the websites developed by the Furniture and Wood Processing Industry Polytechnic to answer the challenges during online learning due to covid 19 and the large number of guests visiting because it is located in an Industrial Estate. To improve the website's service and user experience, there must be testing of the website's usability. The purpose of this study is to test the usability of the SIMPONIK website as a basis for improving the appearance and services available on the website. This study uses the System Usability Scale (SUS) method by distributing questionnaires to 100 respondents. From the results of this study, the SUS score was 76,025, which means the SUS category is acceptable (71-100). Although the results are categorized as acceptable, there must be improvements must be made, especially in terms of practicality and convenience for users.
Perbandingan Algoritma LBP dan Cascading LBP-GLCM untuk Ekstraksi Fitur pada Citra Beras Rahman, Arief; Darnis, Febriyanti; Ansori, Yulian
KOMPUTEK Vol 8, No 2 (2024): Oktober
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v8i2.2962

Abstract

This study compares two image feature extraction algorithms: Gray Level Co-occurrence Matrix (GLCM) and a combination of Local Binary Pattern with GLCM (LBP GLCM), for rice image classification. The objective is to evaluate the effectiveness of both methods in generating features such as ASM, contrast, correlation, entropy, and energy, as well as to measure the computational time. The results show that the LBP GLCM algorithm significantly improves classification accuracy compared to pure GLCM, but requires 13-17 times longer computational time. While GLCM is more efficient in terms of time, its classification accuracy is relatively lower. These findings align with previous studies indicating that adding LBP to GLCM enhances classification performance. In conclusion, LBP GLCM is superior in accuracy, making it a better choice for applications that prioritize precise classification results. However, the trade-off in computational time should be considered, especially for applications requiring fast processing. These findings are relevant for further development in agriculture and image processing. 
Perbandingan Algoritma LBP dan Cascading LBP-GLCM untuk Ekstraksi Fitur pada Citra Beras Rahman, Arief; Darnis, Febriyanti; Ansori, Yulian
KOMPUTEK Vol. 8 No. 2 (2024): Oktober
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v8i2.2962

Abstract

This study compares two image feature extraction algorithms: Gray Level Co-occurrence Matrix (GLCM) and a combination of Local Binary Pattern with GLCM (LBP GLCM), for rice image classification. The objective is to evaluate the effectiveness of both methods in generating features such as ASM, contrast, correlation, entropy, and energy, as well as to measure the computational time. The results show that the LBP GLCM algorithm significantly improves classification accuracy compared to pure GLCM, but requires 13-17 times longer computational time. While GLCM is more efficient in terms of time, its classification accuracy is relatively lower. These findings align with previous studies indicating that adding LBP to GLCM enhances classification performance. In conclusion, LBP GLCM is superior in accuracy, making it a better choice for applications that prioritize precise classification results. However, the trade-off in computational time should be considered, especially for applications requiring fast processing. These findings are relevant for further development in agriculture and image processing. 
Co-Authors Ansori, Yulian Ardiyan Syah, Edo Arief Rahman Deni Saputra Susanti Dwi Ilhami Teguh Setiadi