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All Journal Jurnal Momentum Jurnal Minfo Polgan (JMP)
Yuhendra Yuhendra
Institut Teknologi Padang
Computer Science & IT Education Library & Information Science Mathematics Social Sciences

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REKAYASA PERANGKAT LUNAK PENGOLAHAN DATA DISTRIBUSI OBAT- OBATAN DI PT. ANUGRAH PHARMINDO LESTARI BERBASIS WEB Yuhendra Yuhendra; Riza Eko Yulianto
Jurnal Momentum ISSN 1693-752X Vol 17, No 2 (2015): Volume 17 No. 2 Tahun 2015
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1369.623 KB)

Abstract

PT. Anugrah Pharmindo Lestari (APL) is a company engaged in the distribution of pharmaceuticals to be distributed to outlets (hospitals, pharmacies etc.). Currently the data processing distribution of pharmaceuticals PT. Anugrah Lestari Pharmindo done manually, in addition to the company is also difficult to assess the type of pharmaceuticals most consumers need. As for the book party of pharmaceuticals outlets should come to the company making it less effective and efficient in terms of cost and time. This study aims to build a data processing system of distribution of pharmaceuticals that can process data with good distribution and facilitate the outlet in making reservations and obtain information of pharmaceuticals data. The system is built using the programming language PHP, MySQL database and Apache webserver. With this system the data processing distribution of pharmaceuticals PT. Pharmindo Anugrah Lestari becomes easier with the purchase and sales reports. There was also a chart that is used to monitor the pharmaceuticals most needed, as well as the outlet no longer need to come to the company to order the pharmaceuticals
SCENES CHANGE ANALYSIS OF MULTI-TEMPORAL IMAGES FUSION Yuhendra Yuhendra
Jurnal Momentum ISSN 1693-752X Vol 14, No 1 (2013): Volume 14 No 1 Februari 2013
Publisher : ITP Press

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Abstract

Image fusion and subsequent scene analysis are important for studying Earth surface conditions from remotely sensed imagery. The fusion of the same scene using satellite data taken with different sensors or acquisition times is known as multi-sensor or multi-temporal fusion, respectively. The purpose of this study is to investigate the effects of the multi-sensor, multi-temporal fusion process when a pan-sharpened scene is produced from low spatial resolution multispectral (MS) images and a high spatial resolution panchromatic (PAN) image. It is found that the component substitution (CS) fusion method provides better performance than the multi-resolution analysis (MRA) scheme. Quantitative analysis shows that the CS-based method gives a better result in terms of spatial quality (sharpness), whereas the MRA-based method yields better spectral quality, i.e., better color fidelity to the original MS images.
Penerapan Deteksi Sobel Berbasis Algoritma Backpropagation pada Pengenalan Pola Huruf Vokal Minarni Minarni; Khaira Rizka; Yuhendra Yuhendra; Dede Wira Trise Putra; Indra Warman
Jurnal Minfo Polgan Vol. 12 No. 2 (2023): Artikel Penelitian 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v12i2.13019

Abstract

Pengenalan pola merupakan salah satu bidang dalam pembelajaran mesin yangmenitikberatkan pada metode klasifikasi objek ke dalam kelas-kelas tertentu untukmenyelesaikan masalah tertentu. Penelitian ini menggunakan pengenalan pola tulisantangan pada huruf vokal tulisan tangan anak usia 6-7 tahun. Tujuan penelitian ini untuk menerapkan metode deteksi tepi Sobel untuk ekstraksi ciri dan jaringan syaraf tiruan backpropagation untuk proses klasifikasi pada aplikasi pengenalan pola huruf vokal tulisan tangan. Sistem pengenalan pola huruf vokal tulisan tangan ini menggunakan data citra huruf vokal sebanyak 480 citra terdiri dari huruf besar dan huruf kecil. Ekstraksi ciri yang diambil dari citra berupa nilai matriks deteksi tepi Sobel pada pola huruf vokal. Sebelum dilakukan proses ekstraksi ciri, citra terlebih dahulu melewati tahap preprocessing yang terdiri dari input citra berukuran 30x30 piksel, pengubahan menjadi grayscale dan citra biner menggunakan thresholding. Parameter yang digunakan untuk mendapatkan nilai akurasi terdiri dari lapisan input 900, lapisan tersembunyi 100, lapisan output 1, fungsi aktifasi sigmoid biner (logsig), minimal error 0,01, iterasi maksimum 1000. Hasil rata-rata akurasi yang diperoleh menggunakan metode backpropagation dengan variasi learning rate 0,1 sampai 0,9 berhasil diidentifikasi dengan benar pada pelatihan dengan data latih sebanyak 380 data sebesar 99.36%, sedangkan pada pengujian dengan 100 data uji sebesar 80,38%.
Co-Authors Indra Warman Khaira Rizka Minarni Minarni Putra, Dede Wira Trise Riza Eko Yulianto