Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Teknologi dan Rekayasa TELKOMNIKA (Telecommunication Computing Electronics and Control) JURNAL MEDIA INFORMATIKA BUDIDARMA
Suryadi Harmanto
Universitas Gunadarma
Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
Background Estimation Using Principal Component Analysis Based on Limited Memory Block Krylov Subspace Optimization Ilmiyati Sari; Asep Juarna; Suryadi Harmanto; Djati Kerami
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (413.599 KB) | DOI: 10.11591/ijece.v8i5.pp2847-2856

Abstract

Given a video of ???? frames of size ℎ × ????. Background components of a video are the elements matrix which relative constant over ???? frames. In PCA (principal component analysis) method these elements are referred as “principal components”. In video processing, background subtraction means excision of background component from the video. PCA method is used to get the background component. This method transforms 3 dimensions video (ℎ × ???? × ????) into 2 dimensions one (???? × ????), where ???? is a linear array of size ℎ × ????. The principal components are the dominant eigenvectors which are the basis of an eigenspace. The limited memory block Krylov subspace optimization then is proposed to improve performance the computation. Background estimation is obtained as the projection each input image (the first frame at each sequence image) onto space expanded principal component. The procedure was run for the standard dataset namely SBI (Scene Background Initialization) dataset consisting of 8 videos with interval resolution [146 150, 352 240], total frame [258,500]. The performances are shown with 8 metrics, especially (in average for 8 videos) percentage of error pixels (0.24%), the percentage of clustered error pixels (0.21%), multiscale structural similarity index (0.88 form maximum 1), and running time (61.68 seconds). 
Business Process Reengineering on Customer Service and Procurement Units in Clinical Laboratory Dewi Agushinta R.; Anindito Yoga Pratama; Suryadi Harmanto S
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 2: June 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i2.509

Abstract

Existing business processes on a Clinical laboratory located in Bekasi is still run manually. It takes a lot of time to do more process, especially in customer service and procurement units. These inefficient processes are analyzed here. Utilization of information technology (IT) supports operations of company and even improves efficiency and effectiveness of a company. However, the use of information technology must be balanced with readiness of existing resources to operate. Without supporting resources, especially human resources available, information technology is nothing. Business Reengineering Process method used to comprehend the existing business process, determine processes to be reengineered, investigate alternative redesign, simulate the existing business processes and the proposed business processes, performed an analysis of simulation results, and seeking opportunities in corporate using information technology.This Business Process Reengineering (BPR) research helped Clinical laboratory especially in customer service and procurement in improving efficiency and effectiveness of existing processes that will ultimately reduce cost and time. Results showed that business processes increase with information technology utilization and minimize the use of employee.
Perancangan Sistem Otomatis Transaksi Pembayaran Pada Marketplace UMKM Menggunakan Metode Crawling Horspool Rifki Kosasih; Eko Sri Margianti; Suryadi Harmanto; Didin Mukodim; Hendri Dwi Putra
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4803

Abstract

UMKM MAPAN is one of the UMKM communities consisting of 300 UMKM entrepreneurs who are currently developing and located in the Depok area. These UMKM provide a wide variety of products to be marketed. In marketing these products, these UMKM group still uses the conventional method, is still by face-to-face with the buyer, so they have to rent a place first and are still limited in marketing online. This method has many weaknesses, such as the high cost of renting a place and the difficulty of finding a strategic location to market the product. Therefore, in this study, an e-commerce marketplace web system was created that could accommodate 300 UMKM MAPAN entrepreneurs in marketing their products. In addition, an automatic system for payment transactions on the UMKM marketplace was also created using the Horspool crawling method so that it could make it easier for UMKM entrepreneurs to print payment transaction reports. Based on the research results, the success rate of report printing is 100%. In this study, the complexity of the Horspool algorithm is O(n) with n is length of pattern while the time complexity of the Horspool algorithm is O(m+σ) with m is length of search string.
Store product classification using convolutional neural network I Made Wiryana; Suryadi Harmanto; Alfharizky Fauzi; Imam Bil Qisthi; Zalita Nadya Utami
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i3.pp1439-1447

Abstract

Stores sells consumer goods, mainly food products and other household products at retail. The products sold in stores vary greatly, in order to be time efficient in the fast-paced era and the current technological era requires artificial intelligence technology. In the artificial intelligence branch, there is a specific or detailed learning process known as deep learning. One of the branches of deep learning is the convolutional neural network (CNN). This research intends to employ a CNN architecture to facilitate and streamline the time and cost of the store’s product sorting process. The test is conducted with 1,050 product images divided into 35 labels and divided into three data, namely 80% data training 10% data validation and 10% data test. The image used is preprocessed with a size of 256×256 pixels. The data was trained with six convolution layers and an epoch of 50 with an execution time of 33 minutes so as to achieve an accuracy of 91.37%.
ENKRIPSI CITRA DIGITAL MENGGUNAKAN KOMPOSISI TRANSPOSISI CAT MAP DAN SUBTITUSI KEY STREAM LOGISTIC MAP Rama Dian Syah; Sarifuddin Madenda; Ruddy J. Suhatril; Suryadi Harmanto
Jurnal Ilmiah Teknologi dan Rekayasa Vol 28, No 3 (2023)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2023.v28i3.7951

Abstract

Transmisi pertukaran data digital melalui jaringan internat menjadi hal penting pada kemajuan teknologi. Risiko pembajakan oleh pihak yang tidak bertanggung jawab mungkin terjadi karena kemudahan dalam pertukaran data. Pengembangan metode enkripsi data yang andal dan kuat adalah solusi untuk risiko ini. Penelitian ini mengusulkan algoritma enkripsi data baru melalui komposisi enkripsi transposisi Cat Map dan enkripsi substitusi Logistic Map. Algoritma yang diusulkan secara bersamaan mengubah posisi data dan mengubah nilai data secara acak. Penelitian telah dilakukan dengan menggunakan beberapa citra dengan berbagai fitur dan ukuran yang berbeda. Analisis keacakan citra hasil enkripsi menunjukkan bahwa histogram intensitas warna piksel memiliki distribusi yang seragam dengan nilai korelasi rendah mendekati 0. Hasil analisis peak signal to noise ratio (PSNR) menunjukkan citra hasil dekripsi sama dengan citra asli . Algoritma yang diusulkan memiliki ruang kunci 3.24 × 1068. Hasil NPCR, UACI dan Entropi menunjukkan algoritma yang diusulkan tahan terhadap serangan diferensial dan serangan entropi.
Co-Authors Alfharizky Fauzi Anindito Yoga Pratama Asep Juarna Dewi Agushinta R. Didin Mukodim Djati Kerami Eko Sri Margianti Hendri Dwi Putra I Made Wiryana I Made Wiryana Ilmiyati Sari Imam Bil Qisthi Rama Dian Syah Rifki Kosasih Ruddy J Suhatril Sarifuddin Madenda Zalita Nadya Utami