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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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Penentuan Menu Makanan Untuk Penderita Diabetes Menggunakan Metode Iterative Dichotomizer Tree (ID3) Naufal Sakagraha Kuspinta; Agus Wahyu Widodo; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 4 (2018): April 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Diabates Mellitus (DM) is a metabolic disorder caused by several factors such as insulin deficiency or the inability of the body to utilize insulin. Most patients suffer from this disease due to heredity and unhealthy lifestyle. Diabetes Mellitus is also a chronic disease that became a public health problem in Indonesia. In the body of patients with DM, the inability to automatically adjust the sugar levels in the blood like a healthy person makes them suffering from diabetes. Significant increases in hyperglycemia or sugar levels are believed to increase along with digested consumption. Causes of food sources consumed. Iterative Dichotomizer Tree (ID3) is one of the methods. Subjects in this research is the application of data grouping by using Iterative Dichotomizer Tree (ID3) to classify diabetic food menu data. The dataset used in this study is sourced from Puskesmas Kendalsari Malang. The results of this study is a system capable of grouping food menu datasets for diabetics using the ID3 method. From the test conducted by the results of the testing of 80 data trainning dan 20 data testing is 75%.
Penerapan Algoritme Genetika Pada Kasus Optimasi Penentuan Bibit dan Pemerataan Subsidi pupuk (Studi Kasus: Desa Pandansari, Kabupaten Kediri) Erlyan Eka Pratiwi; Agus Wahyu Widodo; Wayan Firdaus Mahmudy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Equity in the distribution of subsidized fertilizer has several constraints. Based on a survey of equal distribution of seed and fertilizer subsidy at farmer group of Pandansari Village of Kediri Regency, several equality obstacles are that most farmers have no basis and proper calculation in buying fertilizer subsidy based on nutrition requirement of planted seeds. So that resulted in farmers only buy the type of fertilizer with the same composition when different plant varieties that cause less than maximum yield. Besides also if the composition of fertilizer not in accordance with the varieties then the amount of fertilizer in the warehouse will be shortages and excess. To solve the problem used Genetic Algorithm method. The algorithm parameters used in rice plants are population as much as 220, generation as much as 1100, crossover rate 0,8 and mutation rate 0,2 whereas in corn plant population as much as 320, generation 1250, crossover rate 0,8 and crossover rate 0 , 2. The average percentage difference in value generated by genetic algorithm and fertilizer in warehouses on rice plant is 9,873% while in corn plants yield difference of mean percentage between fertilizer in warehouse and genetic algorithm equal to 24,882%. Solution The composition of fertilizers produced by genetic algorithms can be ascertained that the nutrients needed by plants are met so that the yield can increase.
Klasifikasi Keminatan Menggunakan Algoritme Extreme Learning Machine dan Particle Swarm Optimization untuk Seleksi Fitur (Studi Kasus: Program Studi Teknik Informatika FILKOM UB) Nur Afifah Sugianto; Imam Cholissodin; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Majoring program in Informatics Engineering Program Faculty of Computer Science (FILKOM) Brawijaya University is a stabilization program for the profile of graduates of Informatics Engineering students so that each student has a special ability in accordance with the profile of graduates to be achieved. To be able to help the student in selecting the major program then a smart system is needed to determine the major program of each student that accordance with the interests and abilities of students. One methods of classification that can be used is Extreme Learning Machine (ELM) algorithm. However, the method does not have the ability to select features so it needs to be combined with Particle Swarm Optimization algorithm that can be used to perform feature selection automatically and optimally. This research uses 90 data of student study result with 25 features and 3 classes. Based on the research that has been done, the optimal parameters are the number of nodes in the hidden node is 20, the comparison of training data and testing data is 80%:20% (72 training data and 18 testing data), the number of particles is 120, the maximum iteration is 600 and the weight of inertia is 1. From these parameters, the system accuracy using ELM&PSO algorithm is 94.44% with 11 selected features. While the accuracy obtained from the ordinary ELM algorithm is only 66.67%. from the results of accuracy obtained, shows that the addition of PSO algorithm on ELM can improve the accuracy of common ELM algorithm.
Penerapan Ciri Geometric pada Deteksi dan Verifikasi Tanda Tangan Offline Wenny Ramadha Putri; Agus Wahyu Widodo; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Various attempts at securing personal information have been done in both traditional and biometric ways. And among the various ways to protect information, signatures are the most widely used in identifying and verifying personal information. Therefore, efforts should be made to be able to recognize whether the signature is genuine or false by performing detection and verification. In performing the detection process used steps consisting of preprocessing, geometric extraction features, and classification with the modified-K approach method of Nearest Neighbors as a way of verifying signatures. The preprocessing process consists of filtering, binarization, thinning, cropping, and resizing. Then extraction process geometric cirri. Before performing the extraction, zoning on the image with 3 different techniques are vertical, horizontal, and zoning 4 parts. After that is done classification for signature verification process. The result is by testing the zoning technique to determine the value of FRR and FAR of each technique. The smallest FRR value obtained is 54% and the smallest FAR value is 7%. The value is obtained by applying the vertical zoning technique. This shows that the system has a good ability in performing the verification process against fake signatures. While in the process of verification of the original signature the ability of the system is still low. So in accordance with the results obtained, to improve the ability of the system can be improved on the process of preprocessing the image.
Sistem Pakar Diagnosa Penyakit Ibu Hamil Menggunakan Metode Certainty Factor (CF) Aryu Hanifah Aji; Muhammad Tanzil Furqon; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In Indonesia, the death rate of pregnant women was still very high. Lack of knowledge about the perceived symptoms during pregnancy make pregnant women regardless of the specific symptoms that can be harmful and disease records indicate the causes of indirect maternal death in pregnant. Moreover, the risk of pregnant mother mortality is also higher due to the delay in taking the decision factors for referenced. Based on the fact, the proposed solution in the form of expert system diagnosis of diseases of pregnant women using the method of Certainty Factor (CF) that can help recognize diseases during pregnancy to take place based on the perceived symptoms of pregnant women as well as references that should be targeted by the patient. The methods of the CF have a performance system that is capable of running the functional needs and high accuracy percentage results. Moreover the method of CF can describe a level of confidence to the problem at hand. Based on the test results, obtained results 100% functionality of disease diagnosis expert system of pregnant women worked in accordance with a list of system requirements and the system has a level of accuracy of 100%.
Voting Based Extreme Learning Machine dalam Klasifikasi Computer Network Intrusion Detection Sindy Erika Br Ginting; Agus Wahyu Widodo; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Intrusion Detection System (IDS) is useful software or system to detect intrusion on computer networks. It works by utilizing artificial intelligence to identify anomalies or signatures from the activity on computer networks. To refine more the IDS, it requires the development of intrusion classification algorithms with high accuracy. Voting based Extreme Learning Machine (ELM) is a new scheme algorithm which updates the Extreme Learning Machine (ELM) in improving ELM classification performance and is known more reliable for many data. In this study, the performance of the V-ELM has been evaluated on the Knowledge Discovery and Data Mining (KDD) Cup 99 dataset to support IDS development. This study showed that V-ELM was produced bad performance when using some data from KDD Cup 99. It was using 1000 training data and 250 testing data from KDD Cup 99 datasets. The data was divided into 3 variants are 40 classes, 5 classes, and 2 classes attack. The parameters which tested are the values of hidden neurons (L), independent training (K), and sensitivity of each intrusion class. This study found that the best accuracy result on independent training (K) was 3 and 100 hidden neurons in 2 attack class data with an accuracy of 72%. The lowest accuracy was obtained on hidden neurons was 100 and independent training (K) was 11 in 40 attack classes with an accuracy of 12%. This result showed that good classification capability in 2 classes and bad classification capability in 40 classes.
Pengembangan Sistem Rental Kamera Online Ridho Saputra; Agus Wahyu Widodo; Adam Hendra Brata
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Nowadays technological developments are progressing very rapidly. Gadgets as a facility and means of communication and entertainment are also experiencing tremendous growth. Indonesian society increasingly wants to know closer to internet technology, many who use the internet as a field of business, one of which is a site that sells or leases goods online. Not just smartphones or Tablet PCs, the camera now has a growing technology. In the development of all these technologies are also accompanied by technological developments in the field of photography, such as single lens reflect digital camera or more we are familiar with the name of DSLR cameras. The process of analysis of the validation test results is done by looking at the conformity between the results of system performance with a list of needs. Based on the results of validation testing can be concluded that the implementation and functionality of Online Camera System has met the needs that have been described in the needs analysis phase. The process of analysis of the performance test results is done by analyzing the results of testing of Online Camera Rental System.
Segmentasi Pembuluh Darah Pada Citra Retina Menggunakan Algoritme Multi-Scale Line Operator dan Preprocessing Data dengan K-Means Winda Cahyaningrum; Randy Cahya Wihandika; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The vascular changes that occur in retinal are precursors of a diseases, such as heart disease, diabetic retinopathy, stroke and hypertension. Changes can be seen by analyzing retinal image, but it takes a long time. In this study we propose the automation of vascular segmentation processes in retinal image so that can assist in analysis process, which is an important step in retinal image analysis. The segmentation process is done by detecting the line using the Multi-Scale Line Operator algorithm and preprocessing image using K-Means algorithm. Line detection is performed on several different scales, then combines the results of each scale. Image preprocessing using the K-Means algorithm aims to ignore the optic disc area, which in that area will probably be detected as false positive. The performance of proposed algorithm was evaluated using the DRIVE and STARE dataset, the result showed that average accuracy of the DRIVE dataset reaches 0,940980219 with AUC 0,7462, and for STARE dataset reaches 0,949293361 with AUC 0,778. The results are obtained by using the number of K as much as 3 on the K-Means algorithm, which consists of background, foreground, and vessel.
Penerapan Evolution Strategies untuk Optimasi Travelling Salesman Problem With Time Windows pada Sistem Rekomendasi Wisata Malang Raya Cahya Chaqiqi; Agus Wahyu Widodo; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Tourism has became one of influential sectors that plays significant role in shaping the economy of a nation. Malang Raya is one of the place in Indonesia that have an abundance of tourism potential. Malang Raya is a region consisting of three different area of administration which are Kabupaten Malang, Kota Malang, and Kota Batu. Malang Raya has a large collection of destinations and attractions for tourists. On the other hand, the diverse tourism spots to visit can rise another issue as tourists left confused in choosing the best sites and destination alternatives that suit their expectations. The selection of routes faced with limited travel time is a common optimization problem known as Travelling Salesman Problem With Time Windows (TSP-TW). Optimization problem such of TSP-TW can be solved by utilizing Evolution Strategies (ES). According to the result acquired in (pre-research) assessment, the highest fitness value of 0,0041 is reached when the sum of population is 100 and the sum of generation is 15. The results of the optimization test obtained that the application can optimize the recommendation of respondents by 5.57%.
Implementasi Gabungan Metode Multi-Factors High Order Fuzzy Time Series dengan Fuzzy C-Means untuk Peramalan Tingkat Inflasi di Indonesia Jefri Hendra Prasetyo; Agus Wahyu Widodo; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Inflation is a monetary phenomenon in a country where ups and downs result in economic turmoil. Bank Central Indonesia sets the inflation target for the next time with the Inflation Targeting Framework (ITF) as a reference for monetary policy. If the actual inflation does not match the inflation target, then the policy is needed to return inflation to such an inflation target. Based on the inflation rate problem, this research is expected to provide inflation target for the future through inflation rate forecasting using combined Multi-Factors High Order Fuzzy Time Series method with Fuzzy C-Means. Fuzzy C-Means is used to determine the cluster center to be used as a basis for the development of intervals, the use of Fuzzy C-Means is expected to reflect the real data so that the results of forecasting is better. In forecasting used 4-factor data that includes time series data rate inflation and 3 factors that affect. The results of the combined implementation of Multi-Factors High Order Fuzzy Time Series method with Fuzzy C-Means tested the error of forecasting using Mean Absolute Percentage Error (MAPE). Based on the test the error value is 11.33676%, which indicates that the combined method of Multi-Factor High Order Fuzzy Time Series with Fuzzy C-Means is included in the good category used in forecasting the inflation rate in Indonesia because it has an accuracy value below 20%.
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