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All Journal Journal of Enviromental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Indonesian Journal of Electrical Engineering and Computer Science Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI)
Indriati Indriati
Fakultas Ilmu Komputer, Universitas Brawijaya
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Social Sciences

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Implementasi Metode Dempster-Shafer untuk Diagnosis Penyakit pada Tanaman Kedelai Rahmat Arbi Wicaksono; Nurul Hidayat; Indriati Indriati
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

Soybean is one of the main sources of food commodities in Indonesia that not only serves as raw materials for the food industry but also non-food industries. But the lack of knowledge of farmers of soybeans crops about the various symptoms and types of diseases that attack soybean plants are problems that have a negative impact on soybean cultivation. Therefore needed a system that can solve problem of soybean disease diagnosis quickly and precisely. In this research, the writer will implement Dempster-shafer method to diagnose soybean plant disease. This soybean plant diagnosis system can detect 5 types of diseases with 16 symptoms. The results of accuracy tested on 25 data cases obtained an accuracy of 92%, so it can be said that the system works well enough and can be applied.
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%.
Implementasi Algoritme Fuzzy K-Nearest Neighbor untuk Penentuan Lulus Tepat Waktu (Studi Kasus : Fakultas Ilmu Komputer Universitas Brawijaya) Andhika Satria Pria Anugerah; Indriati Indriati; Candra Dewi
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

Along with the increasing interest of studying in the collage, therefore the data of student graduation which is filed will keep increasing. However, those data could be in a very large amount if it is processed manually, therefore it is needed to apply the student graduation classification which able to classify the graduation data based on the determined parameters. There are some ways to classify the object that have been developed, one of them is Fuzzy K-Nearest Neighbor. Fuzzy K-Nearest Neighbor is one of the methods which is used to classify the object by calculating the membership degree in each class. The experiment of Fuzzy K-Nearest Neighbor is done toward the problem of time of student graduation which is categorized into graduate on time and graduate out of time. In this experiment, Fuzzy K-Nearest Neighbor is used to identify the students based on the achievement index that they have got. Based on the experiment results, Fuzzy K-Nearest Neighbor is able to get an accuracy score around 98%. This accuracy is from the given weight of the membership in each output class. This is able to minimize the doubtful in determining the output class
Sistem Pakar Diagnosis Penyakit Hepatitis Menggunakan Metode Dempster Shafer Ayu Tifany Novarina; Edy Santoso; Indriati Indriati
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

Hepatitis is an inflammation of the liver. Inflammation is characterized by elevated liver enzyme levels, due to liver membrane damage or damage. There are two factors that cause the factors of infection and non-infectious factors. There are 5 main hepatitis viruses, referred to as types A, B, C, D and E. These 5 types are of greatest concern because of the burden of illness and death they cause and the potential for outbreaks and epidemic spread.There are many other viruses that potentially cause hepatitis such as adenoviruses, herpes simplex, HIV, rubella, and others. The problems that often occur today is still a lot of ordinary people who lack understanding of health. In fact, not infrequently people do not realize when they get the disease because they do not know the symptoms that cause patients late to handle early. In this study the problems are solved by creating a system by implementing the Dempster-Shafer method to diagnose the types of hepatitis disease suffered by humans, so the system is expected to assist users in diagnosing hepatitis disease in misery since early. Based on the results of system accuracy testing with 20 data samples obtained an accuracy of 90%. Inaccuracy of 10% is caused by several things, among others, the subjectivity of the expert in determining the disease and in the calculations performed using the Dempster-shafer method that uses the highest value without any optimization of the density value on any symptoms.
Aplikasi Berbasis M-KNN untuk Mendukung Keputusan Perekrutan Pemain yang Sesuai dengan Kebutuhan Tim Sepakbola Deny Stevefanus Chandra; Mardji Mardji; Indriati Indriati
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

Football is each team or squad trying to control the ball, inserting the ball into the opposing goal as much as possible, and try to break the opponent's attack to protect or keep his goal so as not to concede the ball. From the explanation it can be seen that the purpose of playing football is to score numbers or goals. Each player has a different function that is the attacker or the front player serves as an attacker, therefore a 3 front player is required to be able to score against the opponent's goal. Then the midfielder or midfielder serves as a ball feeder or it could be a midfielder in charge of assisting the attacker to insert the ball into the goal. In addition, there is also a defender or defender who serves to keep the goal defense from attack the opponents. However, in addition to serving as defensive, defender or more often called a defender can also be tasked to assist the attack. Because each player has a function or task of each different, of course it affects the kicks of each player depending on the position they have. MkNN is a development of the k-Nearest Neighbor (kNN) method. MkNN class labels on test data based on the validated training data and weight of each training data, not just based on the nearest distance as done on kNN. MkNN provides a greater opportunity for training data that has high validity, so the classification is not too affected on data that is less stable or have low validity. The result of MkNN calculation done by decision support system is same with result of calculation manually. The accuracy of this decision support system application in determining the player's position gets 90% results.
Penerapan Algoritma C4.5 Untuk Memprediksi Nilai Kelulusan Siswa Sekolah Menengah Berdasarkan Faktor Eksternal Rizky Haqmanullah Pambudi; Budi Darma Setiawan; Indriati Indriati
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

Education in the life of a country plays a very important role to ensure the survival of the state and nation. Statistics show that Portugal's education level is at the bottom of the list due to many students dropping out of school. External factors affect the failure of students in completing the field of study, especially the field of study of mathematics. Algorithm C4.5 is one method of data mining to predict students' ability in completing the field of study seen from the external factors of students. The C4.5 algorithm is used to find out the accuracy of the prediction ability of high school students. The feature selection parameters are the factors that affect the ability of high school students in the field of mathematics studies. Testing and analysis results show that the Decision Tree C4.5 algorithm is accurately applied to predict the final grade of high school students with a 60% accuracy rate.
Optimasi Fungsi Keanggotaan Fuzzy Inference System Tsukamoto dengan Particle Swarm Optimization pada Penentuan Jumlah Produksi Gula (Studi Kasus : Pabrik Gula Kebonagung Malang) Nur Intan Savitri Bromastuty; Budi Darma Setiawan; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Production is an activity that resulted in goods and services with the usage of resources called production factor. The usual factors for sugar productions is farming area, sugar cane rendement, sugar cane amount, amount of labors, mechine operations, supporting materials and grinding time. Based on previous studies, the major factors that applies to PG. Kebonagung Malang are sugar cane amount, rendement, labor, and machine operations. Studies that estimate sugar production amount already exist, but it's still not optimal. This research was meant to optimize the estimation of sugar production of PG. Kebonagung Malang with particle swarm optimization method to optimize tsukamoto fuzzy inference system. Testing was done with varying particle counts and varying iteration. Computation speed decreases when the number of iterations and particles count increases. Every test with different particle count and iterations results in different fitness value.
Optimasi Bobot Multi-Layer Perceptron Menggunakan Algoritma Genetika Untuk Klasifikasi Tingkat Resiko Penyakit Stroke Nadya Oktavia Rahardiani; Wayan Firdaus Mahmudy; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Stroke is one of a high mortality disease in Indonesia. A various ways can be done to detect stroke, such as blood test. The result is known just after a few hour. Unfortunately, in some case it took a long time to find out whether a patient at risk of stroke or not. The level of risk can be easily done with a system. Multi-layer perceptron (MLP) network is one of artificial neural network (ANN) model which has a random weight from backpropagation (BP) learning. This study is doing optimization to obtain proper weights, using genetic algorithm (GA) as a training method, so that the classification results are more accurate. Implementation, testing, and analysis are done in BP learning algorithm and GA to compare its accuracy on classifying the risk level of stroke. MSE value obtained in testing phase is 0.0122 with number of iteration = 190, number of neuron in hidden layer = 10, and learning rate = 0.9. While in testing phase of GA obtained 0.0549 with population size = 100, generation size = 400, Cr = 0.8, and Mr = 0.2. In final result, average data accuracy of BP is 88.40% with average MSE value is 0.0122 and GA is 60.60% with average MSE value 0.0549 by 10 times trial.
Implementasi Metode Naive Bayes Dengan Perbaikan Missing Value Menggunakan Metode Nearest Neighbor Imputation Studi Kasus: Penyakit Malaria Di Kabupaten Malang Riyant Fajar; Rizal Setya Perdana; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Malaria is an infectious disease that is transmitted among humans by the bites of female Anopheles mosquit. There are four types of Plasmodium that are frequently found in the case of malarial infection in Indonesia: Plasmodium vivax (Tertiana), Plasmodium malariae (Quartana), Plasmodium falcifarum (Tropica), and Plasmodium ovale (Pernisiosia). Thus far, people are having difficulty in differentiating the symptoms found in malaria and in another common cold or influenza as the laymen rely only on general knowledge without any medical facts and reviews. As a result, the patient of malaria is often mistreated. The symptoms of malaria depend on the types of malaria itself. Classic symptoms of malaria suffered by non-immune patients (patients who live in non-endemic area) are paroxysmal (sudden acute fever) preceded by chills and oversweating. On the other hand, classic symptoms of malaria suffered by immune patients are headache, nausea and vomitting, diarrhea , as well as muscle pain. Malaria is a life-threatening disease that can lead into death if not treated in an immediate manner. On that account, a computer system that can accelerate the detection is needed to help in diagnosing whether or not the patient is infected. The said system was designed using Naive Bayes method and the improvement of missing value with the usage of nearest neighbor imputation method. The verdict of the system's accurateness from two testing scenarios has been acquired with the best accuracy point of 77.14% in the first testing scenario and 64.70% in the second testing scenario.
Implementasi Fuzzy Time Series Pada Prediksi Harga Daging Di Pasar Kabupaten Malang Frans Agum Gumelar; Rekyan Regasari Mardi Putri; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Beef is one of the staples that are always consumed by the people of Indonesia. The scarcity of local beef is one of the causes of rising prices. Stabilize the price of beef is the duty of DISPERINDAG. DISPERINDAG spreads almost in every region of Indonesia, one of them is in Malang. Its population is increasing annually so that the demand of food especially beef also increasing. Rising demand of beef also affects the rise in beef prices. So DISPERINDAG should control the increase of beef prices as action to anticipate the increasing price. Therefore, one of the efforts that can be done is to forecast increasing price of beef. So that DISPERINDAG can consider the next month price based on forecast result.The forecasting process is based on historical data. This forecasting that is used is called time series data forecasting. The relations between data are emphasized in time series forecasting. The method used for forecasting is the Fuzzy Time Series (FTS). Based on the results of the test using 21 data of meat prices in Malang Regency in 2016 and 2017, the accuracy obtained from forecasting of 57%. With the smallest error value lies in june 2017 of 16,129 and the biggest error value lies in march 2016 of 65,610,000.
Co-Authors Abdul Azis Adjie Sumanjaya Abel Filemon Haganta Kaban Achmad Arwan Achmad Burhannudin Achmad Ridok Achmad Ridok Ade Wahyu Muntizar Adella Ayu Paramitha Adinugroho, Sigit Afif Musyayyidin Aghata Agung Dwi Kusuma Wibowo Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Fauzan Rahman Ahmad Nur Royyan Aisyah Awalina Aisyah Awalina Alaikal Fajri Nur Alfian Alfita Nuriza Alvin Naufal Wahid Anak Agung Bagus Arisetiawan Andhika Satria Pria Anugerah Andre Rino Prasetyo Andri Santoso Anggara Priambodo Jhohansyah Anjelika Hutapea Annisa Selma Zakia Ardhimas Ilham Bagus Pranata Arief Andy Soebroto Arifin Kurniawan Arinda Ayu Puspitasari Arthur Julio Risa Ashshiddiqi Arya Perdana Avisena Abdillah Alwi Ayu Tifany Novarina Bagus Abdan Aziz Fahriansyah Bayu Rahayudi Benita Salsabila Berlian Bidari Ratna Sari B Beta Deniarrahman Hakim Billy Sabilal Binti Najibah Agus Ratri Binti Robiyatul Musanah Brian Andrianto Budi Darma Setiawan Candra Ardiansyah Candra Dewi Candra Dewi Chandra Ayu Anindya Putri Choirul Anam Daneswara Jauhari Dea Zakia Nathania Deny Stevefanus Chandra Deri Hendra Binawan Desy Andriani Desy Wulandari Dewi Syafira Dhaifa Farah Zhafira Dhony Lastiko Widyastomo Diajeng Ninda Armianti Dian Eka Ratnawati Dina Dahniawati Dinda Adilfi Wirahmi Durrotul Fakhiroh Dwi Suci Ariska Yanti Dyah Ayu Wulandari Edo Ergi Prayogo Edy Santoso Eka Putri Nirwandani Enggar Septrinas Erma Rafliza Fajar Pradana Faradila Puspa Wardani Fardan Ainul Yaqiin Febriana Ranta Lidya Febrina Sarito Sinaga Fera Fanesya Ferdi Alvianda Feri Angga Saputra Firda Oktaviani Putri Firda Priatmayanti Firhad Rinaldi Saputra Fitra Abdurrachman Bachtiar Frans Agum Gumelar Galuh Fadillah Grandis Ghiffary Rizal Hamdhani Guedho Augnifico Mahardika Hilmy Khairi Idris I Made Budi Surya Darma Imam Cholissodin Indah Mutia Ayudita Indriya Dewi Onantya Inosensius Karelo Hesay Jeffrey Junior Tedjasulaksana Jeowandha Ria Wiyani Joda Pahlawan Romadhona Tanjung Junda Alfiah Zulqornain Katherine Ivana Ruslim Khaira Istiqara Khalisma Frinta Kornelius Putra Aditama Ksatria Bhuana Lailil Muflikhah Liana Shanty Wato Wele Keaan Liana Shinta Dewi Liana Shinta Dewi Linda Pratiwi Ludgerus Darell Perwara Lusiyana Adetia Isadi Luthfi Mahendra M. Aasya Aldin Islamy M. Ali Fauzi Mahdarani Dwi Laxmi Mahendra Okza Pradhana Mardji Mardji Marinda Ika Dewi Sakariana Marji Marji Mentari Adiza Putri Nasution Merry Gricelya Nababan Moch Bima Prakoso Mochamad Havid Albar Purnomo Mohamad Alfi Fauzan Mohammad Birky Auliya Akbar Mohammad Fahmi Ilmi Mohammad Imron Maulana Muhammad Abdurasyid Muhammad Fauzan Ziqroh Muhammad Hakiem Muhammad Mauludin Rohman Muhammad Reza Ravi Muhammad Tanzil Furqon Muhammad Yudho Ardianto Nadia Artha Dewi Nadya Oktavia Rahardiani Nana Nofiana Nanda Ajeng Kartini Nanda Cahyo Wirawan Natasya Eldha Oktaviana Ni Made Gita Dwi Purnamasari Ni Made Gita Dwi Purnamasari Nihru Nafi' Dzikrulloh Nirmala Fa'izah Saraswati Novanto Yudistira Novia Agusvina Nur Intan Savitri Bromastuty Nurdifa Febrianti Nurina Savanti Widya Gotami Nurudin Santoso Nurul Hidayat Nurul Muslimah Pengkuh Aditya Prana Prais Sarah Kayaningtias Pratitha Vidya Sakta Puteri Aulia Indrasti Putra Pandu Adikara Putri Nur Fadila Putri Rahma Iriani Putu Amelia Vennanda Widyaswari Putu Rama Bena Putra Rachmad Ridlo Baihaqi Rahma Chairunnisa Rahmat Arbi Wicaksono Rakhman Halim Satrio Randy Cahya Wihandika Rangga Adi Satria Ratih Karika Dewi Ratna Tri Utami Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rien Difitria Rifki Akbar Siregar Rifki Akbar Siregar Rilinka Rilinka Riska Dewi Nurfarida Riski Nova Saputra Riyant Fajar Riza Cahyani Rizal Aditya Nugroho Rizal Setya Perdana Rizaldy Aditya Nugraha Rizky Haqmanullah Pambudi Rizky Nur Ariyanti Sabrina Hanifah Salsabila Rahma Yustihan Sandra Elanda Aza Permataningrum Sinta Kusuma Wardani Siti Robbana Sutrisno Sutrisno Sutrisno Sutrisno Swandy Raja Manaek Pakpahan Tania Malik Iryana Tania Oka Sianturi Tasya Agiyola Thio Marta Elisa Yuridis Butar Butar Titus Christian Vera Rusmalawati Wayan Firdaus Mahmudy Yane Marita Febrianti Yobel Leonardo Tampubolon Yoke Kusuma Arbawa Yudha Ananda Kresna Yudha Irwan Syahputra Yudha Prasetya Anza Yuita Arum Sari Yuita Arum Sari Yulia Kurniawati Zahra Swastika Putri