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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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Peramalan Tingkat Produksi Gula Menggunakan Multi Factor Fuzzy Time Series yang Dioptimasi dengan Algoritme Genetika Kholifa'ul Khoirin; Budi Darma Setiawan; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 11 (2018): November 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sugar is one of the strategic commodities that affect the Indonesia's economy. This is because sugar is one of a essencial staple for Indonesian society. But on the other hand, the large demand of sugar consumption in Indonesian cannot meet with the low production of sugar. One of sugar factories is PG Candi Baru Sidoarjo. Besides production processing's factors, the factory is experiencing difficulties in its planning. Which in the production planning, the sugar factory will set targets that must to be achieved in future production. In an effort to overcome these problems, this study is expected to provide forecasting to see the possibility of achieving sugar production targets. Multi Factor Fuzzy Time Series method optimized with Genetic Algorithm by considering several factors influencing sugar production process such as number of milling days in one month, percentage of rendeman, and number of milled sugarcane. The genetic algorithm is used to perform subinterval optimization. Forecasting results of sugar production using a combination of these two methods get RMSE of 424,70. These results are smaller than the Multi Factor Fuzzy Time Series method without optimizing the subintervals that yield RMSE 6168,7437. Thus, it can be concluded that the proposed method is capable of forecasting better results than the unoptimized Multi Factor Fuzzy Time Series method.
Pemanfaatan Ciri Gray Level Co-Occurrence Matrix (GLCM) Citra Buah Jeruk Keprok (Citrus reticulata Blanco) untuk Klasifikasi Mutu Restu Widodo; Agus Wahyu Widodo; Arry Supriyanto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 11 (2018): November 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The most important thing of production result of fruit is quality. Especially in citrus, it is related to selling value. 92% production of citrus is “Keprok”. But now the quality classification in the fruits industry is still done manually, so it becomes subjective. Information technology is needed to speed up the process of quality classification and make it an objective. This research utilizes the extraction feature of gray level co-occurrence matrix (GLCM) citrus image for quality classification. Begins with collecting data of citrus. There are 100 image data, 60 as training data and 40 as test data. Of each training data, obtained one 64x64 pixels good and bad data image. Do pre-processing on the image and GLCM matrix is formed in direction 0°, 45°, 90° and 135°, feature extraction are contrast, homogeneity, energy and entropy. Support vector machine (SVM) is used for good and bad image identification, to get the percentage of fruit defects. The quality classification is Super Grade, Grade A and Grade B. The result shows that the best classification accuracy is 82.5%, with the amount of training data is 20, distance=2 at 45° GLCM.
Identifikasi Individu Berdasarkan Sketsa Wajah menggunakan Pendekatan Diskriminatif Harits Abdurrohman; Agus Wahyu Widodo; Anto Satriyo Nugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 11 (2018): November 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Identifying a person based on his or her characteristics is the work done on the scope of biometrics. For example each individual has a unique characteristic such as a face or fingerprint. Face is the most recognizable feature which used in the field of forensics only by knowing the physical features on its face by witnesess. Discriminative approach used in this experiment is a well-known method, SIFT (Scale Invariant Feature Transform) and MCWLD (Multiscale Circular Weber Local Descriptor)/ Starting from extracting local features from a set of photos and sketches then performed matching using euclidean distance. The result of this experiment proves that SIFT method with configuration of small window size 8 and 32-overlapping sliding window achieves 79.79% identification rate in top-match rank, while for MCWLD with 16-overlapping sliding window configuration and the parameters used are T = 6, M = 4 and S = 3 achieved 82.45% identification rate on top-match rank. Although MCWLD's identification rate are better than SIFT on top-match, but on the overall result or top-rank, SIFT's identification over-perform MCWLD.
Klasifikasi Aduan Masyarakat pada SAMBAT Online Kota Malang Menggunakan NW-KNN dan Seleksi Fitur Information Gain - Genetic Algorithm Rosi Afiqo; Agus Wahyu Widodo; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

SAMBAT Online is an application system used to accommodate complaints from the public against to the government of Malang. The incomplete features of SKPD selection related to the system made it difficult for Diskominfo of Malang City to report the complaint to the related SKPD. This is because the complaint grouping based on related SKPD is still done manually. Therefore, a system that can group complaints based on the relevant SKPD is required for time efficiency. NW-KNN is classification method which can be used to handle balanced issues that work by involving all training data in the process. The feature selection techniques that will be used are information gain and genetic algorithm to get a small number of features and high f-measure. Stages performed in the system get the best features of the first is pre-processing data, second is feature selection by using information gain, and the third is selection features by using genetic algorithm. The results of the tests performed resulted 0.22 in average of f-measure for unbalanced data and 0.39 for balanced data. These results have increased up to 0.04 for unbalanced data and 0.22 for balanced data from classification results without using feature selection process. Based on these results, it can be concluded that the classification using NW-KNN and information gain-genetic algorithm feature selection can be used to improve the classification results.
Optimasi Penjadwalan Ujian Akhir Semester Menggunakan Algoritme Genetika (Studi Kasus: SMAN 5 Malang) Ni'mah Firsta Cahya Susilo; Budi Darma Setiawan; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Scheduling is an activity with detailed division of time for various purposes in various fields. Scheduling of the semester final exam at SMAN 5 Malang in practice there are still some obstacles such as limited examination supervisors and the distribution of the subjects tested is less suitable. SMAN 5 Malang has applied the exam schedule by dividing subjects based on national examination subjects and other subjects. This study aims to determine the effect of parameter changes on genetic algorithms and find a scheduling solution for the semester final exam at SMAN 5 Malang with a genetic algorithm. Scheduling the final semester exam in this study is divided into subject scheduling and scheduling of exam supervisors. The testing of individual subjects and supervisors is carried out 5 times with population size of 100, number of generations 500 and combination of crossover rate 0.5 and mutation rate 0.5. Testing results in an optimal population for 180 subjects while for supervisors a total of 150. In testing the combination of Cr and Mr values ​​found a combination of optimal values ​​for individual subjects is Cr = 0.7 and Mr = 0.3 and a combination of Cr = 0.6 and Mr = 0.4 for individual supervisors with an optimal number of generations in individual subjects is 200 generations while in individual supervisors is 400 generations.
Klasifikasi Sinyal Otak Motor Imagery Menggunakan Extreme Learning Machine Dan Discrete Fourier Transform Fransiskus Cahyadi Putra Pranoto; Agus Wahyu Widodo; Muhammad Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The brain is the most important body organ that humans have to act as a process for all movements and thoughts in the human body. The brain emits a signal when doing an activity and can be captured by an interface device called brain computer interfaces. To stimulate brain signal activity a stimulus is used, namely an imagery motor. Imagery motors are representations of motor movements imagined by the brain. In this study using 3 datasets namely datasets that have been collected by researchers with muse devices with subjects numbering 20 and having an age range of 19-23 years, the second and third datasets are BCI Competition IIIA and IIIB which are publicly available at bbci.de. The BCI Competition IIIA and IIIB datasets will be used to compare the quality of the datasets collected by the researchers. Signal processing uses the Butterworth Filter Infinite Impulse Response method with a frequency range of 8 to 30 Hz. In this study a study was conducted on the implementation of feature extraction methods with the help of the Discrete Fourier Transform method and the classification of brain signals using the Extreme Learning Machine method that uses imagery motor stimuli. The results obtained were 44% accuracy for 5 classes, 85% and 90% for 2 classes using Muse datasets, 66.67% and 75% 4 classes using BCI Competition IIIA datasets and 93.33% 2 classes using BCI Competition IIIB datasets.
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

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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

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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%.
Ekstraksi Ciri Pada Klasifikasi Tipe Kulit Wajah Menggunakan Metode Haar Wavelet Muhammad Rafi Farhan; Agus Wahyu Widodo; Muhammad Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Facial skin is one of the important parts of a human body. Lots of people trying to make their skin flawless. And also, most of them are willing to spend their money to achieve a perfect skin starts from treatment with distinguished doctors, applying expensive skin products or going abroad to get the product that matches with their skin type. The problem is, people are having difficulties on choosing the right product due to the nonconformity between the purchased product with the skin type. Moreover, this problem leads to acne, wrinkles, and black spot on the skin. The need for a system to ease non-expert to determine their skin type. So, they can purchase the product that fits their skin type. Therefore, the author propose to build a classification system which can classify skin types. In building that, the author uses haar wavelet method which is has been proven to get good result. Based on the result of this research, the highest accuracy is 90% in detection type of skin.
Rekomendasi Prioritas Perbaikan Jalan Dengan Metode AHP-SAW-TOPSIS (Studi Kasus: Dinas Pekerjaan Umum dan Penataan Ruang Kota Malang) Ayudiya Pramisti Regitha; Nurul Hidayat; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the most important public facilities is roadway as it helps in distributing and delivering various human needs. There are 3776 roadways in Malang, and the total accumulation of its length is 1.221.193 kilometers. Based on the data in 2017, 15% of are damaged. However, the allocation of APBN is very limited, about 3-4%, causing limitation in repairing those damaged roads in the time span of one year. Moreover, that allocation is not enough and so it creates difficulties for the staff of PU Bina Marga to decide the priorities in repairing the damaged roadways as all of them need to be fixed. The solution offered for this problem by creating a program/system that can analyze and make a quick decision about the list of priority in repairing damaged roads which called Sistem Rekomendasi Prioritas Perbaikan Jalan. Criterias used in the decision making of this program are the length of the road, the width of the road, the condition, the acces to certain road, the classification of the road based on its function and the route of public transportation. This system uses MADM Method which consists of AHP, SAW and TOPSIS Method. This research testing has resulted 57,14% .
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