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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Knowledge Engineering and Data Science
Agus Wahyu Widodo
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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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.
Ekstraksi Ciri Untuk Klasifikasi Gender Berbasis Citra Wajah Menggunakan Metode Histogram of Oriented Gradients Dani Devito; Randy Cahya Wihandika; Agus Wahyu Widodo
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

Human gender could be recognized from his or her face. Males and females have many different features, such as face shape, eyebrows, mouth, chin, nose, eyes, including facial hairs. Many fields aided by such system which could be developed to automatically recognize human gender, especially for demographic analysis by Indonesian Government. Such gender classification system will rapidly help decision maker that need gender recognition ability. A classifier model could be built to distinguish males from females from its facial features by learning a collections of male and female images data. One method for shape feature extraction is Histogram of Oriented Gradients (HOG). Results shows that classifier ability could be improved by tuning HOG parameter like size for dividing to local image regions, orientation histogram bin size and how each histogram relate to another. This research discussing case of subjects wearing glasses and not. This research explains how to build classification model from Histogram of Oriented Gradients based on face images. Built model able to classify men and women up to 97,83% and 95,92% each. Best parameter for Histogram of Oriented Gradients to classify gender is using (8,8) pixels per cell, 9 bin histogram each cell, (2,2) cell per blocks from (128,128) face image. It could be concluded too that glasses shape affects classification model ability.
Sistem Informasi Rekam Medis Paru berbasis Web (Studi Kasus : Rumah Sakit Karsa Husada Batu) Rizki Aziz Amanullah; Achmad Arwan; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Lung Medical Record Information System is a system intended to assist doctors and nurses in managing lung patient data along with storing medical record data of patients who have visited. In examining patients, doctors and nurses conduct initial assessments which include initial nursing assessments, and patient medical assessments. The patient's medical assessment includes anamnese, physical examination, supporting investigation, diagnosis, follow-up, and progress notes. The follow-up section, the patient will be outpatient or inpatient and will be treated. Inpatient medical records consists of inpatient identity, anamnese, physical examination, list of problems, and chest radiographs. The development of the pulmonary medical record system took a case study at the Karsa Husada Batu Hospital. The system development process starts from the requirements analysis to the testing section with an object oriented approach. At requirement analysis stage there are 111 functional requirements. The system implementation phase is carried out using the Laravel framework. Unit testing produce 100% valid data from 3 functionality tested, while validation testing produce 100% valid data from 111 tested functionalities. In compatibility testing it is proven that this system can run on two browsers, namely Mozilla Firefox and Internet Explorer.
Penerapan Metode Fuzzy K-Nearest Neighbour (FK-NN) Untuk Diagnosis Penyakit Pada Kucing Hardyan Zalfi; Agus Wahyu Widodo; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cats are the animals most loved by humans with a very nice shape and fur many people make cats as their pets especially in Indonesia or the world. The population of cats is 220 million in the world. With the big populatian of cats, of course there are also many cats that have poor health with disease. The limited ability of a person to detect cat disease and the limited of veterinary experts requires a system that can diagnose disease in cats easily. The making of this cat disease diagnosis system uses the k-nearest neighbor fuzzy method which is a development of the k-nearest neighbor method where the membership value of the k-nearest neighbor results will be calculated. Based on the functional tests that have been carried out, each "test class produces conformity to system requirements. The first accuracy testing is testing accuracy based on variations in the amount of training data with a different amount of training data for each test. For this test the highest accuracy value obtained by 85% while the lowest accuracy value is 80%. The second accuracy testing is accuracy testing based on the influence of K values ​​with the same test data totaling 15 test data. The results of this test the greatest accuracy is 86% while the lowest is equal to 73%. This shows that the k-nearest neighbor fuzzy method has a pretty good accuracy to diagnose diseases in cats.
Implementasi Metode Linear Discriminant Analysis (LDA) Untuk Klasifikasi Pengambilan Mata Kuliah Pilihan Ayu Anggrestianingsih; Agus Wahyu Widodo; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The Faculty of Computer Science is one of the best faculties at Brawijaya University. The Faculty of Computer Science (FILKOM) has several majors, one of which is the Informatics major which is most in demand by FILKOM students. When students enter semester 5, they are required to choose interests that are in accordance with their abilities. There are a variety of fields of study offered, one of which is artificial intelligence, which in this study, will focus on taking electives of interest in the field of Artificial Intelligence, to help students choose interests in accordance with their abilities. In this study, using the Linear Discriminant Analysis (LDA) method in order to get good accuracy for taking courses. The training data used as many as 30 data, where each class consists of 15 data for yes classes and 15 data for classes not with 5 elective courses. Then obtained accuracy values ​​for each elective course such as 40% Fuzzy Logic, 40% Decision Support System, 80% Digital Image Processing, 20% Evolution Algorithm and 40% Expert System
Prakiraan Penggunaan Volume Air PDAM Kota Malang Menggunakan Metode Support Vector Regression dengan Ant Colony Optimization Akmilatul Maghfiroh; Agus Wahyu Widodo; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Water is a very important element in the life of all living things. Humans need water to survive and carry out daily activities. Regional Drinking Water Company (PDAM) is a Regional-Owned Company (BUMD) that provides clean water for every region in Indonesia, one of them is PDAM in Malang. The population continues to grow every year causing an increase in the need for clean water. Considering the increasing need for clean water and limited water sources, PDAM Malang must distribute the water optimally and efficiently so that consumers can fulfill their needs for clean water. Therefore, by forecasting the water volume that can be used, it is hoped that it can help PDAM Malang to estimate the volume of water that needs to be distributed efficiently and on target. Some water forecasting methods such as "An Enhanced Differential Evolution Based Gray Model For Forecasting Urban Water Consumption" has a pretty good MAPE value of 2,285%. Then for the SVR-ACO method used in the research "Support Vector Regression and Ant Colony Optimization for HVAC Cooling Load Prediction" has an NMSE of 0.241.
Pemanfaatan Ciri Gray Level Co-occurrence Matrix (GLCM) Untuk Deteksi Melasma Pada Citra Wajah Winda Ika Praseptiyana; Agus Wahyu Widodo; Muh Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Skin is the outermost human organ with the highest sensitivity from external environment, it can cause skin diseases. Skin disease in tropical countries like Indonesia is melasma. Melasma is caused by excessive use of cosmetics and contact with ultraviolet light. If allowed to damage skin cells, damage DNA and risk of skin cancer. Examination on site by a dermatologist relies on visual examination and history taking, which does not rule out the possibility on inaccurate analysis and diagnosis. Therefore, patients choose to do selfcare. However, selfcare can cause melasma to get worse if it is misidentified. Therefore, a detection system is needed to help identify melasma automatically. Using 20 face images data divided into 16 training images and 4 testing images. Face image come in processed cropping images in non-overlapping sliding window to get the window images, then converted to grayscale images. Using the Gray Level Co-occurrence Matrix (GLCM) method as texture extraction with combination angle is 0 °, 45 °, 90 °, 135 ° and neighboring distance value d = 1,2,3. Use of GLCM features are contrast, homogeneity, energy and entropy. For classification method using K-Nearest Neighbor (KNN) with value k=5. This research success in testing of window images, the best percentage was 98% with window size of 200x200 pixels, angular direction with 3 combination is 0°+45°+90° and distance of neighborhood is d = 2.
Implementasi Regresi Linier Berganda Untuk Prediksi Jumlah Peminat Mata Kuliah Pilihan Nur Kholida Afkarina; Agus Wahyu Widodo; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Higher education is a continuation of education at a higher level after completing secondary education. With so many elective courses with each interest, it makes students have difficulty in knowing the number of interested ones. To overcome the problems that exist, this study predicts the number of interested subjects with multiple linear regression methods. Therefore we need a system to predict the number of interested subjects. There are two features used, namely the average student score in the previous year, the number of interested ones in the previous year. The method used is multiple linear regression. The training data used to determine the number of interested parties in taking courses is the 2013-2017 student data. As for the test data using student data for 2018-2019. From this research, the predicted MAPE score of Fuzzy Logic (2017) is 61.52% and in 2016 is 49.64%
Pengelompokan Musik berdasarkan Emosi menggunakan Metode Transformasi Haar Wavelet Natassa Anastasya; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Music consists of various genres and emotions, therefore it is important to group the music according to what the listener wants both based on the genre and the emotions they feel. As an example of an online music application that can automatically group music that makes it easy for listeners to play the desired music, music grouping is seen based on the similarity of certain characteristics. Another example is the Radio music player, where a common problem with radio broadcasters is to play and choose what songs to play. With the grouping of music automatically this will certainly be very helpful and more efficient for playing these songs automatically. Then this research will cluster songs based on the emotions of Broken Heart and Happy with feature extraction using the Haar Wavelet transformation method, then clustering using K-Means. The results of clustering will be evaluated using purity. The test is based on the song structure, a combination of statistical features, and the Haar Wavelet coefficient. Based on the results of all tests carried out obtained clustering with the highest purity value of 0.62.
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 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