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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Journal of Applied Engineering and Technological Science (JAETS)
Agus Wahyu Widodo
Fakultas Ilmu Komputer, Universitas Brawijaya
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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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

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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.
Optimasi Penempatan Ruang Sidang Skripsi Menggunakan Algoritme Genetika Nelli Nur Rahma; Budi Darma Setiawan; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The main problem that often happen in room placement final presentation for thesis in Computer Science Faculty is where lecturer examine more than one sessions continuously with different room which far away. Does not rarely in room placement, lecturer will placement in different building with far away in continuous sessions so raises final presentation for skripsi process will be late from initial scheduling because moving process. With the development of science and technology management, scheduling process should be done better. One of algoritm can use for recommendation of optimal final presentation for thesis is genetic algoritm where this algorithm can use for finished complex problems with many variable and result set of optimal solutions. In the formation of chromosome that used is permutation representation, the crossover process that used is one cut point crossover method, the mutation process that used is one random mutation method, the evaluation process with get fitness value each individual, the selection method that used is elitism. In the test result of room placement final presentation for thesis in one day obtained highest average fitness value is 1,000 in combination of cr 0,5 and mr 0,5, population size is 90, and generation size is 90. Room placement solution that use system can offer optimal scheduling with does not break the constraint at all.
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

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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.
Klasifikasi Jenis Makanan menggunakan Neighbor Weighted K-Nearest Neighbor dengan Seleksi Fitur Information Gain Vriza Wahyu Saputra; Yuita Arum Sari; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Smartphones with powerful camera sensor capabilities can be used to analyze photos and object recognition. Food is one of the popular photography objects and seeing it makes you want to cook or taste it. Cooking requires recipes as a tool to make dishes because not everyone knows how to make dishes. Food recipe search techniques with food image input are needed because not everyone knows the name of the food made. There are several steps in the method carried out to do the introduction of food types namely preprocessing, feature extraction using the Color Moments and Gray Level Counseling Matrix (GLCM) method, feature selection using the Information Gain method and classification using the Weighted K-Nearest Neighbor (NWKNN) method. Tests were carried out to determine the accuracy of the NWKNN method and also to know the effect of the Information Gain feature selection. The results of testing with the K-Fold Cross Validation method obtained the highest average accuracy of 92.37% by dividing the test data by 30, the number of features by 10, the value of k on the NWKNN by 3 and calculating distances using Cosine Similarity. On other hands, the testing of the Information Gain effect resulted in the highest accuracy of 86.96% with the 15 best features. It can be concluded that the NWKNN method can answer the problem of unbalanced data and Information Gain can find out the best features for classification.
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

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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

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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.
Klasifikasi Genus Karang Keras (Scleractinia) dengan Metode Gray Level Co-Occurrence Matrix Muh. Ihsan As Sauri; Agus Wahyu Widodo; Oktiyas Muzaky Luthfi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Coral reef ecosystems are very important for the source of life for a variety of marine biota. Coral reefs have ecological and economical benefits, so it is necessary to carry out regular monitoring so that the ecosystem is well maintained. This monitoring is carried out so that the handling of management runs properly, for this purpose coral identification activities are needed in a certain area. Identification of corals is not as easy as identifying plants, animals or other creatures that have common terminology and have been established. Corals that have similar types like the example in Genus are difficult to do. Therefore it is necessary to classify the Hard Coral Genus (Scleractinia) with the Gray Level Counseling Matrix (GLCM) method. The class used is the genus Acropora, Echinopora, Porites and Fungia. Processing is carried out using the image of the coral with this type of genus by GLCM preprocessing. The features used in the GLCM process are Contrast, Entropy, Energy, Homogenity and Correlation values. The classification used is Support Vector Machine (SVM) with the results obtained by the four Genus still difficult to identify with the results of accuracy of 25%.
Sistem Informasi Manajemen Ternak Sapi Perah di AKA Milk Jakarta Muhammad Heryan Chaniago; Faizatul Amalia; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

AKA Milk is a public dairy cattle company that handling from the process of production to selling the cow's milk to customers. In order to maintain the quality of milk production, the cattle care and handling have been done routinely. However, in practice of the cattle care and handling, it has never been well-documented. Therefore, it's difficult to track the handling record or the current condition of the dairy cattle. In addition to cattle care, matters relating to milk selling are also not well-documented. While, a fact stated by Purwatiningsih and Kia (2018) that the identification and recording of dairy cattle can help farmers in managing the farm and ease the process of managing cattle raising. To overcome the above problems, a management information system of dairy cattle was built using the SDLC Prototyping method. At the stage of analysis and design, a model that can facilitate communication between developers and stakeholder is built in order to find the best solution in a form of a web-based information system. Models used for analysis and design stage includes use cases, use case scenarios, sequence diagrams, class diagrams, and entity relationship diagrams. The implementation will be carried out after stakeholders approve the design by creating a system using codeigniter framework. After the implementation phase done, the system will be tested using white box testing with cyclomatic complexity method and basis path testing. Black box testing will be used to continue the test using decision table method and compatibility testing using the single factor coverage method. The test results close to 100% valid indicates that the system can work optimally in supporting farm activities of AKA Milk which includes dairy cattle data management, care and milking activities, milk selling activities to financial management.
Klasifikasi Jenis Citra Makanan menggunakan Color Histogram dan Gray Level Co-occurrence Matrix dengan K-Nearest Neighbour Hafid Satrio Priambodo; Yuita Arum Sari; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The habit of consuming food irregularly is one factor increasing health risks. One solution to make it easier for the public to know, record and monitor the types of food consumed is to create an intelligent system. To support this solution, research is conducted to identify the type of food that will be consumed. The initial stage in making an introduction is to classify these foods. The classification process is done from the value of the feature extraction used. The introduction process begins with the image preproccessing process which is then performed a feature extraction. Feature extraction used is Color Histogram and Gray Level Co-occurrence Matrix. In feature extraction using the Color Histogram using 3 colors namely red, green, blue with each color having the mean, standard deviation, and skewness features. In addition, feature extraction with the Gray Level Co-occurrence Matrix has 6 types of features such as contrast, dissimilarity, homogeneity, angular second moment, energy, and entropy with the angle of taking pixel values ​​0o, 45 o, 90 o, and 135 o. The method applied to classify the value of the feature extraction results can use is the K-Nearest Neighbor method. The results of the average accuracy produced by these methods amounted to 93.33%. This proves that the methods used in this study are able to classify the types of food images.
Ekstraksi Ciri pada Klasifikasi Tipe Kulit Wajah Menggunakan Metode Local Binary Pattern Diantarakita Diantarakita; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 8 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Various objects in the form of digital images can be extracted the features. One of the features that can be used in feature extraction is statistical texture features. In this case, the feature extraction is used to identify the characteristics of each type of facial skin because many cases of mistakenly recognize the type of facial skin that has resulted in occurrence of diseases and unwanted things on the face. In this study, the author uses facial skin especially the cheek part as the object of research because the cheek is one part of the T-zone. Local Binary Pattern (LBP) is one of the feature extraction method that uses adjacency/neighboring distance and the number of neighbors that can be used and utilized in the identification process, which can be combined with statistical texture features. The benefit of this study itself is to assist in the initial diagnosis in determining the type of facial skin that is owned. This study uses data as many as 112 female face images obtained by taking data directly in the field (primary data). This study got the highest accuracy result that was equal to 84.62% with adjacency/neighboring distance (R) = 1 and a combination of 3 statistical texture features, that is a combination of mean, skewness and energy.
Co-Authors Achmad Arwan Achmad Dewanto Aji Wibisono Adam Hendra Brata Adinugroho, Sigit Afrida Djulya Ika Pratiwi Aida Fitri Nur Amrina Ainun Najib Eka Christianto Aisha Laras Akmilatul Maghfiroh Al-Mar'atush Shoolihah Allifira Andara Hasna Ana Mariyam Puspitasari Andika Indra Kusuma Andreas Pardede Angelika Trivena Lodong Anggita Nurfadilla Mahardika Annisa Amalia Nur'aini Anto Satriyo Nugroho Ardiansyah Setiajati Arry Supriyanto Arya Agung Andika Aryu Hanifah Aji Asfie Nurjanah Ayu Anggrestianingsih Ayudiya Pramisti Regitha Ayustina Giusti Azizah Nurul Asri Bagas Laksono Bayu Rahayudi Beryl Labique Ahmadie Budi Darma Setiawan Budi Kurniawan Cahya Chaqiqi Candra Dewi Dani Devito Delischa Novia Sabilla Deo Hernando Dian Eka Ratnawati Diantarakita Diantarakita Diva Kurnianingtyas Dwi Retnoningrum Dyan Putri Mahardika Eko Wahyu Hidayat Erlyan Eka Pratiwi Faizatul Amalia Fajar Pangestu Fajar Pradana Fajri Eka Saputra Farizky Novanda Pramuditya Femilia Nopianti Feris Adi Kurnia Sadiva Fitri Dwi Astuti Fransiskus Cahyadi Putra Pranoto Grace Theresia Situmorang Gusti Ngurah Wisnu Paramartha Hafid Satrio Priambodo Hardyan Zalfi Haris Bahtiar Asidik Harits Abdurrohman Herman Tolle Imam Cholissodin Indriati Indriati Irwan Shofwan Javier Ardra Figo Jefri Hendra Prasetyo Kholifa'ul Khoirin Lailil Muflikhah Latifa Nabila Harfiya Laviana Agata M. Ali Fauzi Maharani Tri Hastuti Maria Sartika Tambun Miftahul Arifin Muh Arif Rahman Muh. Arif Rahman Muh. Arif Rahman Muh. Ihsan As Sauri Muhamad Rendra Husein Roisdiansyah Muhammad Dimas Setiawan Sanapiah Muhammad Fahmi Hidayatullah Muhammad Fahmi Wibawa Muhammad Faiz Abdul Hamif Muhammad Fajriansyah Muhammad Heryan Chaniago Muhammad Ikhsan Nur Muhammad Rafi Farhan Muhammad Tanzil Furqon Muhja Mufidah Afaf Amirah Nabilla Putri Sakinah Nanda Dwi Putra Miskarana Ade Natassa Anastasya Naufal Sakagraha Kuspinta Nelli Nur Rahma Ni'mah Firsta Cahya Susilo Ningsih Puji Rahayu Nizar Riftadhi Prabandaru Novanto Yudistira Nur Afifah Sugianto Nur Faiqoh Laely Ambarwati Nur Firra Hasjidla Nur Kholida Afkarina Nurudin Santoso Nurul Hidayat oktiyas muzaky Luthfi, oktiyas muzaky Olive Khoirul L.M.A. Puteri Aulia Indrasti Putra Pandu Adikara Putri Bunga Rahmalita Putu Satya Cahyani Rahma Juwita Sany Randy Cahya Wihandika Rekyan Regasari Mardhi Putri Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Restu Widodo Resya Futri Hadi Febryana Retno Dewi Anissa Revan Yosua Cornelius Sianturi Ridho Saputra Rinindya Nurtiara Puteri Rizka Husnun Zakiyyah Rizki Aziz Amanullah Rosi Afiqo Rr Dea Annisayanti Putri Ryan Iriany Satria Habiburrahman Fathul Hakim Sayyidah Karimah Sindy Erika Br Ginting Sri Rahadian Ramadhan Sakti Susiawan Hastomo Ajie Talitha Raissa Tusiarti Handayani Tusty Nadia Maghfira Umar Zaki Izzuddin Utaminingrum, Fitri Vriza Wahyu Saputra Wayan Firdaus Mahmudy Wayan Firdaus Mahmudy Wenny Ramadha Putri Willy Karunia Sandy Winda Cahyaningrum Winda Ika Praseptiyana Witriana Sumarni Yane Marita Febrianti Yosafat Vincent Saragih Yuita Arum Sari Yunita Kristanti Emilia