Article Per Year (5 Year)
p-Index From 2020 - 2025
2.743
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Muh. Arif Rahman
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 33 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 33 Documents
Search

 1   2   3   4 
Ekstraksi Ciri Pada Telapak Tangan Dengan Metode Local Binary Pattern (LBP) Dwi Retnoningrum; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (442.826 KB)

Abstract

Feature extraction can be done on an objects in the form of images using several features. Feature extraction can be combined with the science of biometrics. Biometrics are unique dan measurable physical or biological characteristics. Biometric identification can be used to improve security dan avoid using fake identities. In this case, uses the palm of the object of research because palm has unique features that are different for each individual. In addition to unique features, the palm surface area is one of the authors' considerations in determining the object of research. The surface area of ​​the palm is greater than the surface area of ​​one finger. One method that can be utilized in the identification process is the LBP (Local Binary Pattern) feature extraction method that applies neighboring distances dan the number of neighbors compared. It starts with the Pre-processing stage or the preparation stage of the color image which will be transformed into a gray image dan then followed by a regioning process or image sharing process into several sub-regions. Followed by feature extraction stages with the LBP method. The highest accuracy results obtained from this study amounted to 92.31% with neighboring distance 2, number of neighbors compared = 8, number of regions = 16 dan number of shares height = 4 dan width = 4.
Optimasi Penjadwalan Pegawai Balai Penelitian Tanaman Jeruk Dan Buah Subtropika (Balitjestro) Untuk Wisata Edukasi Petik Jeruk Menggunakan Algoritme Genetika Annisa Amalia Nur'aini; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (548.731 KB)

Abstract

Educational tourism is an activity where tourists can interact directly with certain tourist objects related to tourist attractions. Balitjestro is one of the technical implementing units under the Ministry of Agriculture which opens “Wisata Edukasi Petik Jeruk” every time the harvest arrives. This activity requires the allocation of resources as officers taken from all employees at Balitjestro. In one day, ideally this activity requires 106 officers while the total number of employees is only 75 (Sutopo, 2018). Because of limited human resources, it is necessary to do the optimal scheduling to allocate tourism officers. Manually scheduling takes a long time because it has to match the availability of free time for each employee. Apart from that, several roles are needed, including tour guides, guards, cashiers and grapefruit weighers. One method that can be used for optimization problems is a genetic algorithm. This method consists of several stages including initial population initialization, reproduction, evaluation and selection. The results of this study state that genetic algorithms are able to provide results of employee scheduling for duty during tourism activities with the highest accuracy value that can be achieved at 92.72%. While the overall system accuracy is 91.90%.
Pemilihan Fitur Berbasis Wavelet untuk Klasifikasi Denyut Jantung dari Rekaman Elektrokardiogram Yosafat Vincent Saragih; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (429.611 KB)

Abstract

To diagnose heart disease, especially arrhythmia, the procedure to classify heartbeat pattern is important to do. The pattern can be find by analyze the patient Electrocardiogram (ECG) record. The change of the pattern can be the sign for more serious disease. For today, there are many research conducted to explore the method for classify the beat, but the problem still found to determine the best features set to identify and classify heartbeat pattern. In this research, a feature extraction method, based from wavelet transformation using Haar coefficients was proposed, from segmented ECG record, which represented one beat cycle. Feature was built from each decomposition's coefficients of ECG segment, with simple statistical approach, mean, standard deviation, kurtosis and skewness. MIT-BIH was used as the dataset for this research. Feature evaluation and selection are conducted using Weka software. With using Random Forest classifier, the combination of mean, standard deviation and skewness from each wavelet coefficient, are the best features, which gave the result 84% for Normal class, 98% for Premature Ventricular Contraction (PVC) and 86 % for Atrial Premature Contraction (APC).
Optimasi Penjadwalan Sidang Skripsi Menggunakan Algoritme Genetika Terdistribusi (Studi Kasus : Prodi Teknik Informatika Fakultas Ilmu Komputer Universitas Brawijaya) Putri Bunga Rahmalita; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (369.844 KB)

Abstract

There are several problems on thesis scheduling in Informatics Engineering Study Program Faculty of Computer and Science Brawijaya University that makes thesis scheduling ineffective. Significant differences in the number of students and lecturers in 2017 as well as thesis trial registration in the adjacent time is often a problem in scheduling thesis hearings. Ineffective scheduling will take a long time. Therefore, need a system that can be made using a distributed genetic algorithm method to do thesis trial scheduling. The first step in system is randomize chromosomes and then the population will be divided into several subpopulations, and will go through the reproductive stage, then through evaluation to calculate the fitness value. Selection process will be selected for the next generation. In the distributed genetic algorithm a migration process will be carried out to increase the diversity of individuals by exchanging individuals from one subpopulation to another. Based on the test, the optimal parameter value in the thesis trial scheduling is 11 populations, 1750 generations, the crossover rate is 0.7 mutation rate 0.3 and sub-populations with an average fitness value of 0.00010232. From the results of the test, if there is more population and generation, the wider and bigger the search area for the solution will be, but a cost of a longer computing time.
Penerapan Metode Gray Level Cooccurence Matrix (GLCM) untuk Ekstraksi Ciri pada Telapak Tangan Grace Theresia Situmorang; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (435.926 KB)

Abstract

The increasing use of technology requires a security in the identification of individuals to avoid the access rights that can be known or compromised by others. One that can be utilized in maintaining information security required a science of biometrics. Biometrics is a natural human characteristic that is measurable and accurate, one of which, namely the palms became the object of this study is due to have unique characteristics of each individual whom the Palm's surface than with fingerprint pattern of the main lines, the pattern of tangled line/weak are stable. This can be combined with biometric extraction characteristics by using the various features. Extraction methods can be used namely Gray Level Cooccurence Matrix (GLCM) on the identification process by comparing the size and distance of the region of neighbornood. Beginning with the palm of the hand image capture a number of 208 image where 130 as a trainer and 78 data as test data. On the image of hands done pre-launch stage processing to change the color to grayscale image further divided into several sizes of the regions. The size of each region, performed the extraction phase characterized the Gray Level Cooccurence Matrix (GLCM) with a distance of neighbornood. This research get best accuracy percentage of 87.17% in the size of the region of 7 grids and the neighbornood distance d = 7.
Prediksi Harga Saham menggunakan Metode Backpropagation dengan Optimasi Ant Colony Optimization David Bernhard; Muhammad Tanzil Furqon; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (566.403 KB)

Abstract

Stocks are a sign of a person's or party's investment contribution to a company or limited liability company. Movement of stock prices affects the profits and losses that will be obtained by the investor. The obstacle is stock prices can change in every minute on weekdays. It takes a method that is able to predict stock prices accurately and consistently, so that it can minimize the risk of stock investment. Besides its advantages, BPNN has shortcoming, such as slow convergence time, easy convergence to local minimum points, and poor generalization capabilities. ACO has advantages in distributed computing, positive feedback, and metaheuristic properties that can improve the weaknesses of BPNN. This study uses time series data from the stock price of Bank Rakyat Indonesia (Persero) Tbk. period 1 January 2018 until 31 December 2018. ACO serves to optimize the value combination of learning rate, momentum, and number of hidden nodes for BPNN training phase. Best combination of ACO parameter values was obtained, namely the ant cycle constant worth 0.8, the control constant of pheromone intensity worth 0.1, the visibility control constant worth 0.1, the local pheromone evaporation constant worth 0.5, global pheromone evaporation constant worth 0.1, number of ants 5, and number of iterations 7. That combination produces an average of MAPE 1.745, while BPNN only reached 3.024.
Optimasi Beban Mengajar Dosen Teknik Informatika Menggunakan Algoritme Genetika Femilia Nopianti; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (848.86 KB)

Abstract

Determining lecturers' burden of teaching is a routine activity in all universities, especially for department administrator in each faculty. This matter done as the number of classes taken by students in each semester is always different, yet the number of lecturers are relatively fixed. Determining lecturers' burden of teaching must be done so that the lecturer does not exceed the maximum limit and the teaching process will not deviate from lecturer's interest. The Informatics Engineering program of the Faculty of Computer Science, Brawijaya University Malang is still carrying out the process of determining lecturers' burden of teaching manually, so that it requires a lot of time because it has to adjust between the interest of the subject with lecturer's interest. One optimization method that can be used to overcome this problem is a genetic algorithm. The genetic algorithm process in this study uses integer number representation, crossover method with one cut point crossover, mutation method with reciprocal exchange mutation and random mutation, and selection method with elitism selection. Based on the tests performed, optimal parameters were obtained, the number of population was 70, the combination of cr and mr respectively 0.5, and the number of generations was 4000 with the highest fitness value produced was 0.090909.
Optimasi Pengadaan Buku Perpustakaan Menggunakan Metode Algoritme Genetika (Studi Kasus: Perpustakaan Universitas Brawijaya) Witriana Sumarni; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (871.818 KB)

Abstract

Every year at Library of Brawijaya University procures books to increase the attractiveness of readers or to provide the best service for readers. However, to carry out a maximum book procurement, an adequate budget is needed for the needs of all books needed by each department in Brawijaya University. Therefore, in this study a system was created which was able to optimize the number of books obtained with the budget set in the library of Brawijaya University by applying the genetic algorithm method. Genetic algorithms generate chromosomes with permutation genetic algorithms, each gene represents 1 book title per department. After chromosome generation is carried out, a crossover reproduction process and mutation reproduction will be carried out to produce new individuals. Then an individual evaluation and selection is based on the highest fitness value. After testing, the results of the parameters of the best population were obtained = 160, parameters of many generations = 2000, crossover rate 0.5 and mutation rate 0.5 which gave the opyimal results of the library book procurenment by the number of book purchased 1077 books.
Segmentasi Citra Kue Tradisional menggunakan Otsu Thresholding pada Ruang Warna CIE LAB Putri Harnis; Yuita Arum Sari; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (591.228 KB)

Abstract

Traditional cakes are one of the cultural products that deserve to be treated equally like other cultural assets, including by acknowledging them and preserving their existence. One way is to reintroduce traditional food through digital image processing technology. Taking an image allows us to get the information contained in it. Image segmentation is a technique developed to extract information contained in images which can be used as a reference source. This study proposes the application of traditional cake image segmentation using otsu thresholding method in the CIE LAB color space as extraction of color features. RGB images are used as initial images which are converted into LAB images, each LAB channel then converted into an otsu image. The results of the otsu thresholding image will be compared with the image of ground truth. The results of the study showed that the test values on groundtruth images have different effects on spesific colour of each channel. Of the three channels tested, channel A has the highest accuracy value of 89.65% as well as its specificity and sensitivity values of 87.825 and 95.818%. This indicates that channel A is a channel that can be used on common objects for segmentation with good results than L and B channels.
Klasifikasi Gender berbasis Wajah menggunakan Metode Local Binary Pattern dan Random KNN Ruri Armandhani; Randy Cahya Wihandika; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 8 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (514.082 KB)

Abstract

Automatic gender classification based on facial image is one of the interesting research topics in the world of computer vision. The automatic gender classification system has an important role in developing applications such as surveillance system and monitoring system. However, computers find it difficult to find a special characteristics that can distinguish someone's gender so that a feature extraction is needed. In addition, the selection of classification method is also important to get a better accuracy. The initial stage in this research is to do face detection. After that, pre-processing is done to get the face image only and the size of the image is normalized to 100x100 pixels. Then, the feature extraction process with Local Binary Pattern (LBP) method is done on the pre-processing image. Then, the texture image produced by LBP is divided into several small parts called region. The 32-bin histogram is extracted from each region. All of the histograms from each region are concatenated into a single vector which become the histogram feature used to classify gender. The classification was performed by Random KNN method. Based on the results of testing in this research, the best features produced from the LBP feature extraction which has 7x6 regions. The highest average accuracy produced by Random KNN is 72.5%. The optimal parameter value used for Random KNN in this research is k = 11 and r = 29.
Co-Authors Achmad Dewanto Aji Wibisono Agus Wahyu Widodo Aisha Laras Angelika Trivena Lodong Angga Wahyudi Kurniawan Pratama Anggita Nurfadilla Mahardika Anne Diane Rachmadani Annisa Amalia Nur'aini Arya Agung Andika Ayuda Dhira Pramadhari Bayu Rahayudi David Bernhard Diantarakita Diantarakita Dwi Retnoningrum Faiz Abiyandani Fatwa Reza Rizqika Femilia Nopianti Feris Adi Kurnia Sadiva Ferry Jiwandhono Grace Theresia Situmorang Hafiz Ari Putra Haidar Azmi Rabbani Laviana Agata Muhamad Wahyu Budi Santoso Muhammad Fahmi Wibawa Muhammad Tanzil Furqon Muhammad Tegar Kanugroho Natassa Anastasya Nur Faiqoh Laely Ambarwati Putri Bunga Rahmalita Putri Harnis Putu Satya Cahyani Randy Cahya Wihandika Ruri Armandhani Witriana Sumarni Yosafat Vincent Saragih Yuita Arum Sari Yunita Kristanti Emilia