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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Multimedia JAST : Jurnal Aplikasi Sains dan Teknologi TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) DEDIKASI PKM Jurnal Informatika dan Multimedia Enrichment: Journal of Multidisciplinary Research and Development Majority Science Journal
Dian Eka Ratnawati
Brawijaya University, Malang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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Momentum Backpropagation Untuk Klasifikasi Fungsi Senyawa Aktif Berdasarkan Notasi SMILES (Simplified Molecular Input Line Entry System) Nyimas Ayu Widi Indriana; Dian Eka Ratnawati; Syaiful Anam
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Active compounds can be used to make certain drugs and very important in the medical sector. Classification of active compounds is the most important thing in making medicines. After classifying the active compound, it is continued with the process of making and testing drugs that require a variety of tools. The cost of making and testing these drugs requires a high cost and time. This is a major obstacle for medical experts to make certain medicines. By utilizing current technology, a system can be made to classification process of active compounds, so the performance of medical experts for making certain drugs can be faster. The classification process can be done by using a computer and utilizing the SMILES notation. SMILES notation allows a compound to be processed by a computer. The momentum Backpropagation method can be used to perform the classification process properly. Based on the program that has been made, there are 4 types of testing using 522 training data and 131 test data producing, the best accuracy of 70,99% with a learning rate of 0,00001, max epoch of 100, momentum of 0,25 and hidden layer neurons of 4.
Prediksi Kebangkrutan Menggunakan Metode Backpropagation (Studi Kasus: Perseroan Terbatas Terdaftar Pada Bursa Efek Indonesia) Nanda Alifiya Santoso Putri; Dian Eka Ratnawati; Bayu Rahayudi
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

Bankruptcy is a condition while a company fails either economic failure or even financial failure. Bankruptcy causes a general seizure of all the assets of a bankrupt Debitor (company) that settled and managed by the Curator (supervisor of Debitor's asset). Because it can causes a severe consequences, several attemps were done as an alternative for bankruptcy prevention. One of those attemps is by predicting the bankruptcy itself. Backpropagation is a method of artificial neural network that widely used in the context of classification or regression datasets, one of the regression problem is prediction, because backpropagation is one of the supervised learning algorithm which the output or input values already known. In this study, backpropagation works for predicting the bankruptcy with Altman's five variabels as inputs and the results of Z-Score calculation as output target. The entire test that has been done produces the best MAPE value with average at 0,062% using learning rate parameter value at 0,2, 1000 iterations and 6 neurons in the hidden layer. This MAPE value is under 10% and close to 0% which included in the criteria of prediction with very good accuracy.
Klasifikasi Fungsi Senyawa Aktif Data Berdasarkan Kode Simplified Molecular Input Line Entry System (SMILES) menggunakan Metode Modified K-Nearest Neighbor Yunita Dwi Alfiyanti; Dian Eka Ratnawati; Syaiful Anam
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Compounds are single chemical substances from two or more chemical elements that form bonds and can be described. The compound is divided into active compounds and inactive compounds. Active compounds are chemical compounds that have pharmacology or usability. Compounds have an arrangement that is difficult to process on a computer, for which code is created that is easy to process using a computer. The code is a SMILES (Simplified Molecular Input Line Entry System) which is a code of modern chemical bonds that will be converted into a line to facilitate the classification process in the system. The special character of SMILES is obtained by doing preprocessing with the results of 11 features consisting of B, Br, C, Cl, F, I, N, O, P, S and OH atoms. These features are then used for the classification process using the Modified K-Nearest Neighbor method, where this algorithm is the development of the KNN method which consists of two processing, training data validation and weighting. The classification of the function of active compounds aims to facilitate the grouping of active compounds based on their pharmacology through the help of information technology and computer science degeneration, which so far in the medical field requires a long time in its determination because it uses laboratory tests. Tests that have been conducted using 260 data are divided into 2 categories of classes, namely the Neural class and the Heart class which consists of 90% (234 data) training data and 10% (26 data) test data. The test gets results in the form of an accuracy value of 73% with a k value of 3, whereas in the k-fold cross validation test the value of accuracy is obtained an average of 62.69%.
Klasifikasi Jenis Kanker Berdasarkan Struktur Protein Menggunakan Metode Neighbor Weighted K-Nearest Neighbor (NWKNN) Aldy Satria; Marji Marji; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cancer is non-infectious disease with large population in the world. Cancer is ranked on 7th deadliest disease in Indonesia. Mostly cancer happened because of gene mutation that cause changes in protein form,one of them happens in protein 53 (p53). Mutation of gene p53 most commonly found in human cancers. From this case required a system that can classify the types of cancer. One of methods used is Neighbor Weighted K-Nearest Neighbor (NWKNN). Data used in this paper consists of 752 protein sequences data with 393 sequence length. Classification class includes non-cancer, breast cancer, collorectal cancer and lung cancer. NWKNN is improvement of K-Nearest Neighbor (KNN) method with addition of weight class in its classification class scoring calculation. The test is conducted by dividing dataset into training data and testing data with training data and testing data ratio 80%:20%, 70%:30%, 60%:40, 50%:50, 40%:60%, 30%:70%, 20%:80%, 10%:90% from dataset. The result shows that 80%:20% ratio with K=8 and E=3 provided the highest accuracy eate of 80.666%.
Klasifikasi Senyawa Kimia dengan Notasi Simplified Molecular Input Line Entry System (SMILES) menggunakan Metode Extreme Learning Machine (ELM) Isti Marlisa Fitriani; Dian Eka Ratnawati; Syaiful Anam
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesia has a huge natural's potential by the existence of various plants and animals discovery. This issue brings a good for Indonesian people through taking advantage of nature, especially in pharmacology. In pharmacology, active compounds can be used to prevent and cure disease. Therefore, a research is conducted in informatics's field by making an active compounds' classification system to determine its pharmacological benefits. SMILES is a chemical compound notation used in this research. SMILES's features which are used as many as 15, namely B, C, N, O, P, S, F, Cl, Br, I, OH, @, =, #, and (). ELM is an ANN method that can do a generalization better than conventional methods in a limited time. A number of hidden neurons test which were conducted using k-fold cross validation method in 2 classes produced the best accuracy, 85,03%, in Metabolism and Inflammation class scenario with a total of 5, 10, and 15 hidden neurons. A number of hidden neurons' test use k-fold cross validation method which were conducted in 3 classes produced the best accuracy, 55,06%, in Metabolism, Inflammation, and Cancer class scenario with a total of 300 hidden neurons. The best accuracy was obtained as many as 55,06% by testing 15 features with 300 hidden neurons, while in 11 features's test with 400 hidden neurons was found a number of 49,18% as the best accuracy.
Sistem Rekomendasi Dosen Pembimbing Berdasarkan Dokumen Judul Skripsi di Bidang Komputasi Cerdas Menggunakan Metode BM25 Anak Agung Bagus Arisetiawan; Indriati Indriati; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In the text mining there is a process for information retrieval. Problems related to information retrieval are found in universities, especially in the Faculty of Computer Science, University of Brawijaya (FILKOM UB). The problem is the selection of the thesis supervisor for the FILKOM UB Informatics Engineering S1 study program in the interest of Smart Computing is still done manually. Determination of supervisors only relies on personal knowledge related to the specialization of lecturers needed to guide during the execution of the thesis. These problems can be solved through a recommendation system based on information retrieval using the BM25 method. The process carried out is document preprocessing, calculation of BM25 score in each document, and taking the highest BM25 scoring result as much as k. In this study three tests were carried out. Each test uses the same testing data of 20 documents. The average results of each test obtained the best recommendation results, namely at the value k=3, with a value of precision @k of 0.87. The higher the value of k used can affect the recommendation results to be less optimal because more and more irrelevant documents are counted.
Klasifikasi Fungsi Senyawa Aktif Berdasarkan Notasi Simplified Molecular Input Line Entry System (SMILES) Dengan Metode K-Means Naive Bayes (KMNB) Revi Anistia Masykuroh; Dian Eka Ratnawati; Syaiful Anam
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

Indonesia is a tropical country that has the most biodiversity in the world. Almost all of the plants part like leaf, root, stem, fruit, flowers, seeds, and rhizome can be used for human health. In Indonesia the utilization of plants as medicine is so limited. Therefore, further research and continuous plant drugs or herbal remedies is really needed as well as the technologies are able to maximize the utilization. In 1980, David Weininger found a chemical notation for processing informations that related to a modern chemistry named Simplified Molecular Input Line System (SMILES) and that notation is specifically for computer used. On this research, K-Means Naive Bayes methods are used for the classification of the functions of the active compounds because this methods are able to grouping data according to their similarity and the classification process is much easier to understand. Based on the test results, the K-Means Naive Bayes are abled to give an accuracy system 85.45% with a 80% training data ratio and 20% testing data. The system also being tested using K-Fold Cross Validation with K-Fold as many as 10, the highest accuracy that can be given is 86.66% on 9th fold and the lowest is 70.37% on 1st fold. While the average of accuracy using the K-Fold Cross Validation is 82.6%.
Klasifikasi Fungsi Senyawa Aktif berdasarkan Data Simplified Molecular Input Line Entry System (SMILES) menggunakan Metode Support Vector Machine (SVM) Dwi Febry Indarwati; Dian Eka Ratnawati; Syaiful Anam
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

Chemical compounds can be distinguished into active compounds or commonly called bioactive compounds and inactive compounds or commonly called passive compounds. At this time there are still many active compunds that the pharmacological role does not known yet, so the system being made for classify the functions of active compounds that expected to support chemists research in the laboratory. To simplify the process of making the system, the representation of molecular structure must be easily processed by a computer so that the SMILES notation will be used, the SMILES notation describes chemical formula in a row notation. This system is using the SVM (Support Vector Machine) method because the SVM method has high generalization capabilities without requiring additional datasets. In this research uses as many as 15 features and objects as many as 3 classes of active compound functions, including metabolism, infection, and anti-inflammation. The best test result is 83.33% when using the Gaussian kernel RBF, using a lambda value (λ) of 5, the complexity value is 0.1, the sigma value (σ) is 0.5, and with the number of iterations is 5.
Analisis Sentimen pada Sosial Media Twitter Terhadap Layanan Sistem Informasi Akademik Mahasiswa Universitas Brawijaya dengan Metode K-Nearest Neighbor Luqman Rizky Dharmawan; Issa Arwani; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 3 (2020): Maret 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sistem Informasi Akademik Mahasiswa Universitas Brawijaya (SIAM UB) is an academic service belongs to University of Brawijaya that is used for college academic needs service. The topic about SIAM UB sometimes become trending topic at Twitter before the new semester starts. Twitter is a social media service that quite famous among citizen for giving opinion or thought through certain topic including SIAM UB. This research try to analyze some tweets about SIAM UB by classifying a tweet into the positive sentiment class or negative sentiment class. The classification process implemented on RapidMiner. The method used on this classification process is K-Nearest Neighbor and Chi Square method for feature selection. There are four main processes for the classification, which are preprocessing, term weighting, feature selection, and classification. The highest accuration score from the classification process is 86%. That accuration score was obtained when using K = 3 and using 100% feature. The percentage of the number of features which is used affects the accuracy value where the lower feature ratio is used, the accuration score became lower too.
Analisis Pengelompokkan Penjualan Rattan Furniture Pada PT. Hymsa Indotraco Berbasis Algoritma K-Means Clustering Krishna Febianda; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 6 (2020): Juni 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Hymsa Indotraco is a rattan furniture manufacturing and exporter company in Indonesia, which has more than 5000 furniture collections. Production is based on orders from buyers. This raises a problem, namely management has difficulty determining the amount and type of raw materials available in accordance with customer orders. So, we need a method that can help the processing of sales data. This study aims to determine the pattern of grouping sales data using K-Means Clustering to get the results of grouping sales of rattan furniture that are most ordered, frequently ordered, and rarely ordered. In its implementation, RapidMiner tools are used. This clustering produces clusters that are rarely ordered as many as 678 products, clusters that are often ordered as many as 14 products, and the most ordered are as many as 15 products. Data evaluation was performed using the Davies-Bouldin Index with 3 clusters yielding 0.106. The results of this study are used as recommendations for companies to determine the supply of raw materials and products offered to customers.
Co-Authors Abdurrahman Airlangga, Aria Abhiram, Muhammad Tegar Achmad Arwan Achmad Ridok Achmad, Riza Putra Adhitya, I Made Yoga Adrian Firmansah, Dani Afif Ridhwan Afrida Djulya Ika Pratiwi Agus Wahyu Widodo Agustin Kartikasari Ahmad Afif Supianto Akbar, Rozaq Aldy Satria Alfa Fadlilah Alifah, Syafira Almira Syawli, Almira Alvian Akmal Nabhan Amonito, Kurnia Ana Mariyam Puspitasari Anak Agung Bagus Arisetiawan Anam, Syaiful Ardhiansyah, Muhammad Hanif Arief Andy Soebroto Arif Pratama Asmoro, Priandhita Sukowidyanti Asroru Maula Romadlon Audia Refanda Permatasari Ayu Dwi Lestari, Cynthia Ayulianita A. Boestari Azizul Hanifah Hadi Bayu Rahayudi Bayu Satriawan, Eka Bayu Septyo Adi Bella Krisanda Easterita Bening Herwijayanti Berton, Freddy Toranggi Buce Trias Hanggara Buce Trias Hanggara Buchori Anantya Firdaus Budi Darma Setiawan Cahyo Gusti Indrayanto Candra Dewi Dany Primanita Kartikasari Darma Setiawan, Budi Darmawan, Riski Davia Werdiastu Denny Manuel Yeremia Sinurat Deny Tisna Amijaya, Fidia Devi Nazhifa Nur Husnina Dewi Yanti Liliana Dhiva Mustikananda Dimas Diandra Audiansyah Dimas Fachrurrozi Azam diniyah, zubaidah Diva, Zahra Djoko Pramono Dwi Ari Suryaningrum Dwi Febry Indarwati Dwi Purwono, Prayoga Dwija Wisnu Brata Dyva Pandhu Adwandha Dzulkarnain, Tsania Dzulkarnain, Tsania - Easterita, Bella Krisanda Edgar Maulana Thoriq Edy Santoso Elfa Fatimah Ema Agasta Entra Betlin Ladauw Eva Agustina Ompusunggu Fadhil, Muhammad Farrasseka Fadila, Putri Nur Faiz Anggiananta Winantoro Fanka Angelina Larasati Fathin Al Ghifari Fatthul Iman Fauzan Dwi Kurniawan, Fauzan Dwi Fauzidan Iqbal Ghiffari Figgy Rosaliana Firdaus, Muhammad Fariz Fitra Abdurrachman Bachtiar Fitri Dwi Astuti Fitria Yesisca Fitria, Tharessa Ghani Fikri Baihaqi glenando Gusti Ngurah Wisnu Paramartha Hadi Wijoyo, Satrio Hamas, radityo Hana Chyntia Morama Hanggara, Buce Trias Hanifa Maulani Ramadhan Haris Haris, Haris Harris Imam Fathoni Hasibuan, Herida Hafni Hasibuan, Raka Ardiansyah Heru Nurwasito Hilal, Khaliffman Rahmat Hilmy Ramadhan, Achmad Zhafran Huda Minhajur Rosyidin I Dewa Gede Ngurah Bramasta Darmawan Ibnu Aqli Ibnu Aqli, Ibnu Ibrahim Kusuma Ilyas, Muhaimin Imam Cholissodin Imam Cholissodin Imam Cholissodin Immanuel Tri Putra Sihaloho Indriati ., Indriati Indriati Indriati Ismiarta Aknuranda Issa Arwani Issa Arwani Isti Marlisa Fitriani Izza, Aisyah Nurul Jesika Silviana Situmorang Jibril Averroes, Muhammad Juan Michel Hesekiel Kartika, Annisa Wuri Kelvin Anggatanata Kevin Renjiro Khairi Ubaidah Khoba, Ahmad Faiz Khofifatunnabilah, Khofifatunnabilah Kirana, Urdha Egha Krishna Febianda Kusuma, Salsabila Azzahra' Zulfa Lailil Muflikhah Leonardo, Ryan Luqman Rizky Dharmawan M. Ali Fauzi Madjid, Marchenda Fayza Maghfiroh, Sofita Hidayatul Mahendra Data Mahendra Data Mala Nurhidayati Maliha Athiya Rahmani Marji . Marji Marji Marji Marji Marji Marji Maulana Syahril Ramadhan Hardiono Michael Eggi Bastian Mochammad Iskandar Ardiyansyah Rochman Moh Fadel Asikin Muh. Arif Rahman MUHAJIR Muhammad Iqbal Mustofa Muhammad Kevin Sandryan Muhammad Reza Utama Pulungan Muhammad Tanzil Furqon Muhyidin Ubaiddillah Muslimah, Fakhriyyatum Muthia Maharani Nabilah Iftah Nella Naily Zakiyatil Ilahiyah Nanang Yudi Setiawan Nanang Yudi Setiawan Nanda Alifiya Santoso Putri Nanda Petty Wahyuningtyas Nilna Fadhila Ganies Norma Desitasari Novirra Dwi Asri Nugraha Perdana, Aditya Nugraheni, Miftakhul Fitria Nur Adli Ari Darmawand Nur Khilmiyatul Ilmiyah Nuraini Anitasari Nuralam, Inggang Perwangsa Nurul Hidayat Nyimas Ayu Widi Indriana Oceandra Audrey Pandu Adikara, Putra Pangestu Ari Wijaya Panjaitan, RE. Miracle Prahesti, Suherni Prakoso, Ricky Pratomo Adinegoro Priyono, Mochammad Fajri Rahmatullah Rendra Puji Indah Lestari Purnomo, Welly Putra Pandu Adikara Putra, Alland Rifqy Putri, Nindy Alya Rachmad, Zikfikri Yulfiandi Raden Rizky Widdie Tigusti Rahma, Dzakiyyah Afifah Rahmah, Yusriyah Raisha, Serefika Raja Farhan Ramadha Pohan Rama Humam Syarokha Randy Cahya Wihandika Rani Metivianis Ratih Diah Puspitasari RE. Miracle Panjaitan Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Retno Indah Rokhmawati, Retno Indah Revi Anistia Masykuroh Rifqi Irfansyah, Nandana Rizal Setya Perdana Rizal Setya Perdana Robiata Tsania Salsabila Aditya Putri Rodiah Rodiah Ryan Leonardo Salsabillah, Dinar Fairus Saparila Worokinasih Saputro, Dimas Sarie, Riza Athaya Rania Satriawan, Eka Bayu Satrio Agung Wicaksono Satrio Hadi Wijoyo Sema Yuni Fraticasari Setiawan, Alexander Christo Setya Perdana, Rizal Setyowati, Andri Shafira Margaretta Sherly Witanto Sherryl Sugiono Sindarto Sigit Pangestu Silvia Ikmalia Fernanda Siregar, Fauziah Syifa R. Siti Fatimah Al Uswah Sobakhul Munir Siroj Sormin, Hartati Penta Angelina Sri Indrayani, Sri Suhhy Ramzini Sukmawati, A'inun Sutrisno Sutrisno Sutrisno, Sutrisno Syaiful Anam Syifa Namira Neztigaty Thifal Fadiyah Basar Titis Sari Kusuma Ulfa Lina Wulandari Utomo, Yoga Cahyo Vina Adelina Welly Purnomo Wibowo, Shinta Dewi Putri Widhy Hayuhardhika Nugraha Putra Wijanarko, Rizqi Winda Fitri Astiti Winurputra, Raihan Wiratama Paramasatya Yahya, Faiz Yolanda Nailil Ula Yudi Setiawan, Nanang Yuita Arum Sari Yunita Dwi Alfiyanti Yure Firdaus Arifin Zahra, Wardah