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Pengembangan Modul Klasifikasi Apel Envy dan Pasific Rose Menggunakan Jaringan Saraf Tiruan (JST) Rahmanti, Farah Zakiyah; Adi, Prajanto Wahyu; Ataka, Ion; Sukmana, Septian Enggar
JURNAL NASIONAL TEKNIK ELEKTRO Vol 5, No 2: Juli 2016
Publisher : Jurusan Teknik Elektro Universitas Andalas

The variety of apple has similarity with each other, therefore it makes human visual perception difficult to differentiate some of them. Â The conventional way is often carried out human vision Â subjective perception, this way makes classification result becomes less. Apple classificationÂ using information technology is one step to classify apple more accurate and to help human in apple plantations processing. The goal of this research is developing classification stage on envy and pasific rose apple. The major goal is to classify envy and pacific rose apple using Artificial Neural Network (ANN). Doing feature extraction of training and testing apple images aims that Â images can be recognized as envy or pasific rose. The way of getting feature extraction is using statistical approach of RGB color histogram from an image. The feature extraction values of RGB color histogram of apple images are intensity, standard deviation, skewness, energy, entropy, and smoothness. Then, those values as an input of classification step using ANN feed-forward backpropagation. The results of this research are consists of three scenario of experiment, first skenario is using 50 training data 10 testing data, it has accuracy value 80%. Second scenario is using 70 training data 10 testing data, it also has accuracy value 80%. Third scenario is using 90 training data 10 testing data, it has accuracy value 90%. This experiment result shows that the highest accuracy value is in third scenario.Keywords : Apple, Feature extraction, Artificial neural network, BackpropagationAbstrak â€” Jenis apel yang beragam dan beberapa diantaranya memiliki kemiripan membuat persepsi pandang manusia sulit membedakan jenis-jenis apel tertentu. Cara konvensional yang sering dilakukan adalah penilaian subyektif dari persepsi pandang manusia. Penilaian subyektif tersebut bisa menghasilkan pengelompokan jenis apel yang kurang tepat. Teknik pengenalan jenis apel berbasis teknologi informasi menjadi salah satu langkah untuk membantu pengelompokan jenis apel supaya lebih tepat dan akurat serta lebih meringankan tugas manusia pada bidang pengolahan hasil perkebunan apel. Penelitian ini bertujuan untuk mengembangkan tahapan klasifikasi apel envy dan pasific rose. Tujuan utamanya adalah mengklasifikasi buah apel jenis envy dan pasific rose dengan menggunakan Jaringan Saraf Tiruan (JST) atau sering disebut dengan Artificial Neural Network (ANN). Citra apel terlebih dahulu dilakukan ekstraksi fitur yang unik dari citra latih dan citra uji, agar citra tersebut dapat dikenali. Â Salah satu cara ekstraksi fitur adalah dengan menggunakan pendekatan statistik dari histogram warna RGB sebuah citra. Nilai-nilai yang bisa diambil dari histogram warna RGB citra apel adalah nilai rerata intensitas, standar deviasi, skewness, energi, entropi, dan smoothnes. Â Kemudian nilai-nilai tersebut sebagai nilai masukan untuk tahapan klasifikasi menggunakan JST feed-forward backpropagation. Hasil pengujian dibagi menjadi tiga skenario, pertama dengan data latih 50 data uji 10 memiliki nilai akurasi sebesar 80%. Skenario pengujian kedua dengan data latih 70 data uji 10 memiliki nilai akurasi sebesar 80%. Skenario pengujian ketiga dengan data latih 90 data uji 10 memiliki akurasi sebesar 90%. Hasil pengujian tersebut menunjukan bahwa nilai akurasi tertinggi terletak pada pengujian ketiga.Kata Kunci : Apel, Ekstraksi fitur, Jaringan saraf tiruan, Backpropagation

Robust Watermarking through Dual Band IWT and Chinese Remainder Theorem Prajanto Wahyu Adi; Farah Zakiyah Rahmanti; Edy Winarno
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

CRT was a widely used algorithm in the development of watermarking methods. The algorithm produced good image quality but it had low robustness against compression and filtering. This paper proposed a new watermarking scheme through dual band IWT to improve the robustness and preserving the image quality. The high frequency sub band was used to index the embedding location on the low frequency sub band. In robustness test, the CRT method resulted average NC value of 0.7129, 0.4846, and 0.6768 while the proposed method had higher NC value of 0.7902, 0.7473, and 0.8163 in corresponding Gaussian filter, JPEG, and JPEG2000 compression test. Meanwhile the both CRT and proposed method had similar average SSIM value of 0.9979 and 0.9960 respectively in term of image quality. The result showed that the proposed method was able to improve the robustness and maintaining the image quality.

ROBUST INTEGER HAAR WAVELET BASED WATERMARKING USING SINGULAR VALUE DECOMPOSITION Prajanto Wahyu Adi; Farah Zakiyah Rahmanti
Jurnal Ilmu Komputer dan Informasi Vol 9, No 1 (2016): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

This paper proposed a hybrid watermarking method that used dither quantization of Singular Value Decomposition (SVD) on average coefficients of Integer Haar Wavelet Transform (IHWT). The watermark image embeds through dither quantization process on singular coefficients value. This scheme aims to obtain the higher robustness level than previous method which performs dither quantization of SVD directly on image pixels value. The experiment results show that the proposed method has proper watermarked images quality above 38dB. The proposed method has better performance than the previous method in term of robustness against several image processing attacks. In JPEG compression with Quality Factor of 50 and 70, JPEG2000 compression with Compression Ratio of 5 and 3, average filtering, and Gaussian filtering, the previous method has average Normalized Correlation (NC) values of 0.8756, 0.9759, 0.9509, 0.9905, 0.8321, and 0.9297 respectively. While, the proposed method has better average NC values of 0.9730, 0.9884, 0.9844, 0.9963, 0.9020, and 0.9590 respectively.

Robust Watermarking through Dual Band IWT and Chinese Remainder Theorem Prajanto Wahyu Adi; Farah Zakiyah Rahmanti; Edy Winarno
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v7i4.690

CRT was a widely used algorithm in the development of watermarking methods. The algorithm produced good image quality but it had low robustness against compression and filtering. This paper proposed a new watermarking scheme through dual band IWT to improve the robustness and preserving the image quality. The high frequency sub band was used to index the embedding location on the low frequency sub band. In robustness test, the CRT method resulted average NC value of 0.7129, 0.4846, and 0.6768 while the proposed method had higher NC value of 0.7902, 0.7473, and 0.8163 in corresponding Gaussian filter, JPEG, and JPEG2000 compression test. Meanwhile the both CRT and proposed method had similar average SSIM value of 0.9979 and 0.9960 respectively in term of image quality. The result showed that the proposed method was able to improve the robustness and maintaining the image quality.

Color Variation from Vehicle on The Road and Its Environment Through Subtle Motion Study Case Septian Enggar Sukmana; Farah Zakiyah Rahmanti
Journal of Applied Intelligent System Vol 3, No 1 (2018): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v3i1.1835

Road accident has been serious case in Indonesia, the big number of the cases is not decreasing for six years. Many ways have been done, one of example is exploiting smart camera or CCTV to observe mocement estimation explicitly or implicitly. One problem is when explicit-based technique is applied, the computation process would take more resource. Implicit-based technique like exploitting processing-based frequency domain must be tried to make a better study and produce more knowledge in this study field. Color magnification can helpful information to support better movement estimation. This eulerian-based technique may be the one useful method to help this study. This paper implements eluerian video magnification to get color magnification on road as observed environment. This technique produces unexpected result that unknown black color appears, it still ambiguous because some scene can be described as black color object magnification result and another is shocking camera effect so that the technique is difficult to obtain color magnfication result. PSNR results quite better value because in spite of color magnification result distraction, the scenery of the road is not covered fully. SSIM shows that some mapping in each video data can not results same pattern, it is suspicious that SSIM mapping is affected by this color magnification result.

Plasmodium Falciparum Identification in Thick Blood Preparations Using GLCM and Support Vector Machine (SVM) Farah Zakiyah Rahmanti; Novita Kurnia Ningrum; Septian Enggar Sukmana; Prajanto Wahyu Adi
Journal of Applied Intelligent System Vol 2, No 1 (2017): April 2017
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v2i1.1388

Malaria is one of the serious diseases that require rapid handling, otherwise it can lead to death. One of the causes of malaria parasites is plasmodium falciparum which can cause severe or fatal malaria. Handling a medical late can increase the risk of death. Therefore, it takes a rapid identification system with a high percentage of accuracy to reduce the risk of death. This research aims to build an identification system of plasmodium falciparum in thick blood film using Gray Level Co-occurrence Matrix (GLCM) and Support Vector Machine (SVM). The GLCM is used to get texture feature values such as contrast, correlations, energy, and homogeneity from images. Those values is processed and as an input of classification using SVM. The research result using SVM for accuracy value ofÂ plasmodium falciparum identification can reach 93.33%.

Pengembangan Modul Klasifikasi Apel Envy dan Pasific Rose Menggunakan Jaringan Saraf Tiruan (JST) Farah Zakiyah Rahmanti; Prajanto Wahyu Adi; Ion Ataka; Septian Enggar Sukmana
JURNAL NASIONAL TEKNIK ELEKTRO Vol 5 No 2: Juli 2016
Publisher : Jurusan Teknik Elektro Universitas Andalas

The variety of apple has similarity with each other, therefore it makes human visual perception difficult to differentiate some of them. The conventional way is often carried out human vision subjective perception, this way makes classification result becomes less. Apple classification using information technology is one step to classify apple more accurate and to help human in apple plantations processing. The goal of this research is developing classification stage on envy and pasific rose apple. The major goal is to classify envy and pacific rose apple using Artificial Neural Network (ANN). Doing feature extraction of training and testing apple images aims that images can be recognized as envy or pasific rose. The way of getting feature extraction is using statistical approach of RGB color histogram from an image. The feature extraction values of RGB color histogram of apple images are intensity, standard deviation, skewness, energy, entropy, and smoothness. Then, those values as an input of classification step using ANN feed-forward backpropagation. The results of this research are consists of three scenario of experiment, first skenario is using 50 training data 10 testing data, it has accuracy value 80%. Second scenario is using 70 training data 10 testing data, it also has accuracy value 80%. Third scenario is using 90 training data 10 testing data, it has accuracy value 90%. This experiment result shows that the highest accuracy value is in third scenario.Keywords : Apple, Feature extraction, Artificial neural network, BackpropagationAbstrak — Jenis apel yang beragam dan beberapa diantaranya memiliki kemiripan membuat persepsi pandang manusia sulit membedakan jenis-jenis apel tertentu. Cara konvensional yang sering dilakukan adalah penilaian subyektif dari persepsi pandang manusia. Penilaian subyektif tersebut bisa menghasilkan pengelompokan jenis apel yang kurang tepat. Teknik pengenalan jenis apel berbasis teknologi informasi menjadi salah satu langkah untuk membantu pengelompokan jenis apel supaya lebih tepat dan akurat serta lebih meringankan tugas manusia pada bidang pengolahan hasil perkebunan apel. Penelitian ini bertujuan untuk mengembangkan tahapan klasifikasi apel envy dan pasific rose. Tujuan utamanya adalah mengklasifikasi buah apel jenis envy dan pasific rose dengan menggunakan Jaringan Saraf Tiruan (JST) atau sering disebut dengan Artificial Neural Network (ANN). Citra apel terlebih dahulu dilakukan ekstraksi fitur yang unik dari citra latih dan citra uji, agar citra tersebut dapat dikenali. Salah satu cara ekstraksi fitur adalah dengan menggunakan pendekatan statistik dari histogram warna RGB sebuah citra. Nilai-nilai yang bisa diambil dari histogram warna RGB citra apel adalah nilai rerata intensitas, standar deviasi, skewness, energi, entropi, dan smoothnes. Kemudian nilai-nilai tersebut sebagai nilai masukan untuk tahapan klasifikasi menggunakan JST feed-forward backpropagation. Hasil pengujian dibagi menjadi tiga skenario, pertama dengan data latih 50 data uji 10 memiliki nilai akurasi sebesar 80%. Skenario pengujian kedua dengan data latih 70 data uji 10 memiliki nilai akurasi sebesar 80%. Skenario pengujian ketiga dengan data latih 90 data uji 10 memiliki akurasi sebesar 90%. Hasil pengujian tersebut menunjukan bahwa nilai akurasi tertinggi terletak pada pengujian ketiga.Kata Kunci : Apel, Ekstraksi fitur, Jaringan saraf tiruan, Backpropagation

Real-Time Accident Detection Using KNN Algorithm to Support IoT-based Smart City Khodijah Amiroh; Bernadus Anggo Seno Aji; Farah Zakiyah Rahmanti
JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022
Publisher : Jurusan Teknik Elektro Universitas Andalas

Surabaya is a city with an area of 326.81 km2 and is the center of land transportation in the eastern part of Java Island. The construction of digital infrastructure in the Surabaya area will make it easier for the City Government to make efficient services. Traffic accidents that occurred in Surabaya until 2017 recorded 1,365 incidents. EVAN (Emergency Vehicle Automatic Notification) is a research topic that focuses on the field of transportation, especially in real-time traffic accidents which can be integrated with city information centers and hospitals for primary assistance in accidents. The purpose of this research is to make it easier for the Surabaya city government to provide first aid in the event of an accident. The design of the device on the user side is made using the Arduino, the accelerometer sensor and the gyroscope in the form of the MPU6050 sensor and the u-blox gps module. Crash detection on the system using the k-Nearest neighbors algorithm (KNN). On the operator side, the design is done on a web basis by utilizing the ReactJs framework which is integrated with the Google Maps APIs. The results of the accuracy of the accident detection system reached 97% and the detection of accident locations and the nearest hospital from the location reached 100%. Thus, real-time accident detection can be implemented in Surabaya city to support the smart city.

Analisis Kualitas Udara untuk Monitoring Kesehatan Lingkungan Rumah Sakit Khodijah Amiroh; Oktavia Ayu Permata; Farah Zakiyah Rahmanti
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 4, No 1 (2019): InfoTekJar September
Publisher : Universitas Islam Sumatera Utara

Kualitas udara merupakan faktor penting dalam kesehatan sanitasi rumah sakit.Rumah sakit merupakan instasi pelayanan kesehatan dengan inti kegitan promotive, preventif, kuratif, dan rehabilitative. Gas CO dan CO2 merupakan salah satu indikator dalam penilaian kesehatan lingkungan sanitasi rumah sakit sesuai dengan Kepmenkes 1204 tahun 2004. Alat monitoring yang dibuat fokus untuk melihat kondisi gas CO dan CO2 secara real-time. Analisis deskriptif dilakukan dengan menggunakan 10 parameter statistik. Selain analisis deksriptif juga menggunakan analisa histrogram. Hasil pengujian yang dilakukan pada tiga kondisi yakni kamar pasien, area parkir, dan pada ruang tunggu mendapat hasil yang bervariasi. Pada kamar pasien didapatkan hasil kualitas udara yang paling baik. Sedangkan pada area parkir mendapatkan hasil yang paling buruk. Pada area ruang tunggu rumah sakit hasil yang didapatkan kadar CO2 yang buruk. Alat pengukuran berdasarkan hasil kalibrasi mengalami error sebesar 15,11% untuk sensor CO dan 24,08% untuk 24,08%. Hasil pengujian pengiriman informasi dari mikrokontroller ke aplikasi meunjukkan hasil error sebesar 2,3%.

Robust Watermarking through Dual Band IWT and Chinese Remainder Theorem Prajanto Wahyu Adi; Farah Zakiyah Rahmanti; Edy Winarno
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

CRT was a widely used algorithm in the development of watermarking methods. The algorithm produced good image quality but it had low robustness against compression and filtering. This paper proposed a new watermarking scheme through dual band IWT to improve the robustness and preserving the image quality. The high frequency sub band was used to index the embedding location on the low frequency sub band. In robustness test, the CRT method resulted average NC value of 0.7129, 0.4846, and 0.6768 while the proposed method had higher NC value of 0.7902, 0.7473, and 0.8163 in corresponding Gaussian filter, JPEG, and JPEG2000 compression test. Meanwhile the both CRT and proposed method had similar average SSIM value of 0.9979 and 0.9960 respectively in term of image quality. The result showed that the proposed method was able to improve the robustness and maintaining the image quality.

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