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All Journal Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer JOURNAL OF APPLIED BUSINESS ADMINISTRATION Indonesian Journal of Electrical Engineering and Computer Science
Muhammad Tanzil Furqon
Fakultas Ilmu Komputer , Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Mechanical Engineering Social Sciences

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Klasifikasi Standar Produk Baja PT. Krakatau Steel (Persero) Tbk. Berdasarkan Komposisi Kimia dan Sifat Mekanis Baja Menggunakan Fuzzy K-Nearest Neighbor (Fuzzy K-NN) Ardisa Tamara Putri; Muhammad Tanzil Furqon; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The occurrence of chemical composition deviations or mechanical properties in steel production causes the clasification of steels based on standards can't be defined. The deviation that occurs is the deviation from the maximum limit of the chemical composition and the minimum limit of the mechanical properties of steel. This is the background of researchers to create a system using the Fuzzy k-Nearest Neighbor method. The Fuzzy k-Nearest Neighbor (Fuzzy K-NN) method used for classifying steel standards based on the chemical composition of the steel produced. The data used for this study is data steel products with the specifications of the steel composition, the mechanical properties of the steel and the classification of standard of steel produced. The steps performed are data normalization, Fuzzy k-Nearest Neighbor, calculate Euclidean distance, take the shortest distance k, calculate the membership value of each class and determine the target class. The highest accuracy resulted by testing k values using k-fold cross validation is 74,44% with k value equal to 74,44 and total of training data is 267 data.
Optimasi Komposisi Menu Makanan bagi Penderita Tekanan Darah Tinggi Menggunakan Algoritme Genetika Adaptif Raden Rafika Anugrahning Putri; Muhammad Tanzil Furqon; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

High blood pressure or commonly called hypertension is a disease that can affect anyone. High blood pressure is one disease that can cause other diseases, such as heart attack and stroke. Blood pressure is high if systolic blood pressure is more than 140 mmHg and diastolic blood pressure is more than 90 mmHg. One thing that most affect the high blood pressure is an unhealthy diet. To set a healthy diet for people with high blood pressure then need to set the composition of foods with the needs of the body. A technique to get solution of foods for people with high blood pressure is by applying Adaptive Genetic Algorithm. Adaptive parameters are applied to the reproduction process mutation. The data used in the test is 146 Data of food ingredients classified into staple food, vegetable sources, sources of animal, vegetable and complementary. On this process of Adaptive Genetic Algorithm is used the permutation represented with integer with a length of chromosome 15 genes represented each digit of the number of food, methods of crossover with single-point crossover and mutation methods with reciprocal exchange mutation and elitism selection. As the results, the test performed obtained optimal parameters is the measure population of 200 individuals with an average fitness of 0,0774665, 90 generations with the average fitness of 0,0774665 and combinations cr = 0,8 and mr = 0,2 with the average fitness of 0,0780737.
Klasifikasi Teks Pengaduan Pada Sambat Online Menggunakan Metode N-Gram dan Neighbor Weighted K-Nearest Neighbor (NW-KNN) Annisya Aprilia Prasanti; Mochammad Ali Fauzi; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

SAMBAT Online is a concrete application of E-Government in a web-based platform for complaints provided by Dinas Komunikasi dan Informatika Kota Malang (Diskominfo Malang). An incoming complaint text will be categorized into various areas of the SKPD. With that being said, in order to make the job of the super admin easier in organizing and determining an SKPD category, as well to organize a complaint text and improve the time efficacy, a method of text classification is paramount. NW-KNN is an upgraded algorithm of the traditional KNN algorithm. Generally, the closest neighboring distance calculations will use Cosine Similarity with bag of words for feature extraction. Bag of words is a feature extraction that ignores the order of words of a sentence altogether. To improve the algorithm despite the deficiency, this research will use supporting method for feature extraction, which is called as N-Gram. The result in this research indicated that NW-KNN with neighboring value k = 3 and N-Gram with Unigram have the highest f-measure's value with 75.25%.
Klasifikasi Penyakit Typhoid Fever (TF) dan Dengue Haemorhagic Fever (DHF) dengan Menerapkan Algoritma Decision Tree C4.5 (Studi Kasus : Rumah Sakit Wilujeng Kediri) Ulva Febriana; Muhammad Tanzil Furqon; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Fever is a rise in body temperature is higher than usual. Fever is not a disease, but the initial symptoms of a person affected by the disease. There are many diseases caused by fever, such as Typhoid Fever and Dengue Haemorragic Fever. Both diseases when observed clinically will be difficult to distinguish them. Because the two diseases almost have the same symptoms and if there is an error in diagnosing it will cause a fatal thing in the patient. Typhoid Fever disease is a fever caused by Salmonella Typhi bacteria that spread throughout the body and Haemorragic Fever Dengue fever caused by Aedes Aegypti mosquito bites. To overcome this, then made a classification system of disease diagnosis Typhoid Fever and Dengue Haemorragic Fever based on symptoms possessed by patients by applying desicion tree algorithm C4.5. Accuracy obtained by Typhoid Fever (TF) and Dengue Haemorhagic Fever (DHF) classification system by k-folds cross validation test showed the highest accuracy value on 5-fold cross validation with accuracy of 91,875% using 32 data test and Training data of 128 data. The results of the 4th test on 5-fold cross validation test resulted in the highest accuracy of 97%. While the analysis by conducting 16-fold cross validation test of the test data of 10 data and training data of 150 data, obtained the result of the test value of 100% on the 2nd, 3rd, 4th, 6th, The 9th, the 11th, the 12th and the 16th. Although the 100% accuracy value obtained in this test is numerous, the average accuracy of the 16-fold cross validation test is still below the average score of accuracy obtained by testing 5-fold cross validation.
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 Metode Fuzzy Analytical Hierarchy Process (F-AHP) Untuk Menentukan Besar Pinjaman Pada Koperasi Fernando Parulian Saputra; Nurul Hidayat; 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

One of the functions of cooperative is to offer loans. Loan offer has own risks, some cases of bad loans cause disadvantage for the cooperative. The same problems also happen at KUD Tuwuh Sari. The causes occur when KUD Tuwuh Sari can not analyze the value can be loaned correctly. This research offers a solution to solve the problems, by creating a system that can help KUD Tuwuh Sari to analyze and determine the value of the loan. Fuzzy Analytical Hierarchy Process (F-AHP) method applied to the system because this method has proven can solve the multi-criteria decision making (MCDM) problems, who have subjective side. The calculation process of F-AHP required consistent pairwise comparison matrix between criteria, with CR value < 0,1. Testing is done by comparing the suitability of the system's decisions to cooperative's, using k-fold cross validation method. And from this test known that, system's decision has an average 86% of compatibility levels.
Identifikasi Penyimpangan Tumbuh Kembang Anak Dengan Algoritme Backpropagation Fadhilla Puji Cahyani; Muhammad Tanzil Furqon; 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

Growth and development are two processes that are interdependent and inseparable. Growth and development of children greatly affect the quality of growth and development of children in the future. In the development phase, often encountered irregularities that cause delay in child development when compared to children of the same age. Developmental disorders that often occurred in children are such as autism, Attention Deficit Disorder (ADHD), and Down Syndrome. This study aims to identify the type of development disorder of children based on symptoms that appear using Backpropagation algorithm. Backpropagation algorithm is one of Artificial Neural Network algorithm that has ability to solve complex problems that can not be solved by conventional learning technique. The network architectures used in this study are 38 input neurons, 5 hidden neurons, and 3 output neurons. The results of this study indicate that Backpropagation algorithm can identify the development disorder of children well with the average accuracy of 91,11% in the test of training data of 81, 9 testing data, learning rate 0,1, and 0,0009 minimun error.
Sistem Informasi Geografis Berbasis Mobile Rekomendasi Pencarian Iklan Dan Petunjuk Arah Lokasi Transaksi Pada Aplikasi Jual Beli Online Menggunakan Location Based Services Wildan Afif Abidullah; Issa Arwani; Muhammad Tanzil Furqon
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

E-commerce is a method of selling, purchasing and marketing goods and services through electronic media such as radio, television and computer or internet network. Otomotifstore.com is one of the e-commerce or online shop sites in the automotive field with the concept of bringing together between sellers and buyers. Buyers who want to buy something will search for ads based on their location, which then the buyer will contact the seller to make the transaction. The solution that can ease the transaction process based on the nearest location is to create an application that can provide advertising recommendations in the form of geographic maps based on the location of the buyer followed by route to reach the location of transaction. The application is built based on android mobile using Location Based Services with a Global Positioning System (GPS) which can take the target of prospective buyers and sellers location. The geographic map displayed in the apps is by utilizing the android API maps from google. The application can ease the sellers and buyers to make transactions directly by the presence of ad distribution in the form of geographic maps and followed by route to transaction location. Based on the validation testing, the application have fulfilled all the functional requirements and usability testing proves that the built application has been successful with a percentage of 97%, so the application is ready to used for user. From the results of compatibility testing of three types of devices with different specifications obtained valid results.
Klasifikasi Penyakit Kulit Pada Manusia Menggunakan Metode Binary Decision Tree Support Vector Machine (BDTSVM) (Studi Kasus: Puskesmas Dinoyo Kota Malang) Dyan Dyanmita Putri; Muhammad Tanzil Furqon; Rizal Setya Perdana
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

The skin is an organ in the human body is very important because it lies on the outside of the body that serves to receive stimuli such as touch, pain and other influences from the outside. Skin disease is one of the most common diseases in tropical countries such as Indonesia. The lack of knowledge about the type of skin disease and do not know how to prevent it cause a person can get acute skin disease. So with the help of computer technology is expected to attack the skin of the human body can be detected early and it can minimize the occurrence of more dangerous diseases. This research aims to determine the classification of skin diseases in humans using the method of Binary Decision Tree Support Vector Machine (BDTSVM) Based on the test results obtained the best accuracy of 97.14% with SVM parameter test that is the value of λ (lambda) = 0,5, C (complexity) = 1, constant γ (gamma) = 0,01, and itermax = 10.
Peramalan Harga Saham Menggunakan Metode Support Vector Regression (SVR) dengan Particle Swarm Optimization (PSO) Vera Rusmalawati; Muhammad Tanzil Furqon; Indriati Indriati
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

One of the advantages of investing in stocks is capital gains, which is the benefits from stock trading. The use of stock price forecasting will increase profits from stock sale and purchase transactions because shareholders can know when the right time to sell or buy a particular stock. Support Vector Regression (SVR) is one of the methods used for forecasting, it can recognize patterns of time series data and can provide good forecasting results when the parameters of importance can be determined well as well. So we need an optimization method to determine SVR parameters so that SVR can be optimally applied in stock price forecasting. One of the optimization algorithms that can be used is Particle Swarm Optimization (PSO). Stock price forecasting using SVR with PSO optimization uses MAPE method to evaluate forecasting results. Based on the test that has been done, the value of MAPE obtained is 0.8195% with fitness of 0.5496 with the optimal parameters obtained is the number of particles 40, iteration PSO 40, iteration SVR 1000, parameter range of C 100 - 500, the parameter range of ɛ 0, 0001 - 0,001, parameter range of σ 0,001 - 2, parameter range of γ 0,00001 - 0,001, parameter range of λ 0,001 - 0,1, and comparison of training data and test data from 2016 BCA Bank share data is 90%: 10%.
Co-Authors Abas Saritua Gultom Abu Wildan Mucholladin Achmad Arwan Achmad Ridok Adinda Chilliya Basuki Adinugroho, Sigit Agus Wahyu Widodo Ahmad Afif Supianto Akhmad Eriq Ghozali Al-Mar&#039;atush Shoolihah Aldion Cahya Imanda Amalia Luhung Andini Agustina Anindya Celena Khansa Kirana Anjelika Hutapea Annisya Aprilia Prasanti Annisya Aprilia Prasanti Ardisa Tamara Putri Arief Andy Soebroto Arif Indra Kurnia Arina Rufaida Arinda Rachman Arjun Nurdiansyah Arya Perdana Arynda Kusuma Dewi Aryo Pinandito Aryu Hanifah Aji Asfie Nurjanah Audi Nuermey Hanafi Ayu Anggrestianingsih Barik Kresna Amijaya Bayu Rahayudi Bayu Rahayudi Bossarito Putro Brillian Ghulam Ash Shidiq Budi Darma Setiawan Candra Dewi Cusen Mosabeth Daniel Alex Saroha Simamora David Bernhard Defanto Hanif Yoranda Dendry Zeta Maliha Destin Eva Dila Purnama Sari Desy Andriani Diajeng Sekar Seruni Dian Eka Ratnawati Dwi Yana Wijaya Dyan Dyanmita Putri Dyang Falila Pramesti Dzar Romaita Edy Santoso Eko Ari Setijono Marhendraputro Eky Cahya Pratama Elan Putra Madani Erwin Bagus Nugroho Evilia Nur Harsanti Fadhilla Puji Cahyani Fahmi Achmad Fauzi Fajar Pradana Fatwa Ramdani, Fatwa Fernando Parulian Saputra Fikar Cevi Anggian Firdaus Rahman Fitra Abdurrachman Bachtiar Gabriel Mulyawan Ghulam Mahmudi Al Azis Guntur Syafiqi Adidarmawan Hangga Eka Febrianto Hanifa Maulani Ramadhan Hanifah Khoirunnisak Hugo Ghally Imanaka Humam Aziz Romdhoni I Gusti Ngurah Ersania Susena Imam Cholissodin Iman Harie Nawanto Imaning Dyah Larasati Inas Hakimah Kurniasih Indra Eka Mandriana Indri Monika Parapat Indriana Candra Dewi Indriati Indriati Inggang Perwangsa Nuralam Issa Arwani Jojor Jennifer BR Sianipar Julita Gandasari Ariana Jumerlyanti Mase Kevin Nadio Dwi Putra Khaira Istiqara Laila Diana Khulyati Lailil Muflikhah Listiya Surtiningsih Luthfi Faisal Rafiq M. Ali Fauzi Mahardhika Hendra Bagaskara Mahendra Data Maria Sartika Tambun Marji Marji Masayu Vidya Rosyidah Mochamad Ali Fahmi Muh. Arif Rahman Muhamad Fahrur Rozi Muhammad Aghni Nur Lazuardy Muhammad Iqbal Mustofa Muhammad Rafif Al Aziz Muhammad Riduan Indra Hariwijaya Muhammad Wafiq Naufal Sakagraha Kuspinta Nindy Deka Nivani Novanto Yudistira Nur Kholida Afkarina Nurdifa Febrianti Nurudin Santoso Nurul Hidayat Nurul Hidayat Nurul Ihsani Fadilah Ofi Eka Novyanti Oky Krisdiantoro Pangestuti, Edriana Pricielya Alviyonita Priyambadha, Bayu Putra Pandu Adikara Putri Indhira Utami Paudi R Moh Andriawan Adikara Raden Rafika Anugrahning Putri Raditya Rinandyaswara Raditya Rinandyaswara Rahman Syarif Randy Cahya Wihandika Ratna Ayu Wijayanti Restia Dwi Oktavianing Tyas Ridho Ghiffary Muhammad Rifaldi Raya Rifwan Hamidi Rimba Anditya Kurniawan Riski Nova Saputra Riza Rizqiana Perdana Putri Rizal Setya Perdana Robbiyatul Munawarah Romlah Tantiati Satrio Hadi Wijoyo Setyoko Yudho Baskoro Silvia Aprilla Sutrisno Sutrisno Tania Oka Sianturi Taufan Nugraha Teri Kincowati Tryse Rezza Biantong Ulva Febriana Vandi Cahya Rachmandika Vania Nuraini Latifah Vera Rusmalawati Vianti Mala Anggraeni Kusuma Weni Agustina Wildan Afif Abidullah Wildan Ziaulhaq Wildan Ziaulhaq Wilis Biro Syamhuri Yuita Arum Sari Yuita Arum Sari