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All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Ilmu Komputer dan Informasi MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Register: Jurnal Ilmiah Teknologi Sistem Informasi Fountain of Informatics Journal Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Proceedings Series on Physical & Formal Sciences Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Anestesi: Jurnal Ilmu Kesehatan dan Kedokteran Journal of Information Technology and Cyber Security
Ratih Kartika Dewi
Fakultas Ilmu Komputer, Universitas Brawijaya
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Health Professions Library & Information Science Mechanical Engineering Nursing Physics Public Health

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Pengembangan Aplikasi Mobile Penyusunan Ransum Pakan Ternak Sapi dan Kambing Menggunakan Framework Ionic Andriano Eucharistia Wibowo; Herman Tolle; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

An application to compile rations for cattles' meals was developed by a student of Brawijaya University ini 2015. This application is a web-based application that formulate cattles' meal from two kinds of ingredients, that is forage ingredients and concentrate ingredients, to fulfill the daily nutrition or to increase the weight of a cow. The application that is called SunRan (Susun Ransum) used Yii framework in its development. The developer of the application felt that a development for the mobile version in needed. The need encourages the writer to develop the SunRan on a mobile platform. This mobile version of SunRan uses Ionic framework which has a function for developing applications in hybrid system, which is a ixture of system based on website and native. The operating system used to run SunRan Mobile is Android OS. It's done because this operating system is the most opoular operating system, especiallly in Asia, where there are still a lot of people working on a ranch for cows and goats. Besides being used to compile rations for cow's meal, the writer is also adding a new object that hasn't included in the web-based SunRan before, the object is goat. The tests for this mobile application is done twice to prove if the web-based SunRan can be developed into a mobile-based application with an addition of a new object and an utilization of a different framework.
Diagnosis Penyakit Hati Menggunakan Metode Naive Bayes Dan Certainty Factor Rhyzoma Grannata Rafsanjani; Nurul Hidayat; Ratih Kartika Dewi
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

Liver disease or liver disease is a disease caused by various factors that damage the liver, such as viruses and alcohol use. Obesity is also associated with liver damage. Over time, liver damage can cause serious effects, the presence of experts will be very helpful in dealing with liver disease problems by identifying the symptoms experienced and infer what type of liver disease is attacking and provide information to deal with the problem. The Naive Bayes method is a method used to predict probabilities. While Certainty Factor is a method that can help experts who diagnose something uncertain. Variables needed in this study are symptoms of liver disease and liver disease type. Based on the results of testing and analysis of the results of this study, it can be taken some conclusions that Method Naive Bayes and certainty factor can be used for the diagnosis of liver disease. The Naive Bayes method and certainty factor resulted in an accuracy of 88%.
Sistem Diagnosis Penyakit Penglihatan Kabur Pada Mata Menggunakan Metode AHP-SAW Mochammad Faizal Satria Rahman; Nurul Hidayat; Ratih Kartika Dewi
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

Blurred vision sickness is an eye-attacking disease which has a high rate of cases in Indonesia. The disease is also difficult to detect visually. In many cases, this disease is detected when the symptom is already severe. Patients with this disease are usually not aware of blurred vision symptom. Therefore it needs expert diagnosis to understand this disease. On the other hand, limited number of eye experts in Indonesia is also problem which has to be addressed. Those problems can be solved by establishing an expert system of blurred vision diagnosis. Expert systems are part of artificial intelligence which contains expert knowledge and experience incorporated into a particular area of knowledge to solve specific problems. Method of Analytic Hierarchy Process-Simple Additive Weighting (AHP-SAW) is kind of method which applied to overcome the problem of identifying criterion with measuring data qualitatively and quantitatively. Based on the test data which used in this study, system succeed to diagnosis of blurred vision sickness with 87% of accuracy.
Klasifikasi dan Rekomendasi Jurusan Kuliah Bagi Pelajar SMA Menggunakan Algoritme Naive Bayes-WP Restu Fitriawanti; Imam Cholissodin; Ratih Kartika Dewi
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

Each year high school students will be faced with a final choice to determine what direction will be selected for future education. Each choice will determine the future of the voter, and this is something that is difficult enough to be determined by most high school students, because they do not have information and images related to education in college. In addition, the child is still not aware of the interests and abilities on him. Based on the problems above the selection of majors as early as possible should start to be considered because choosing faculty and majors with precisely very difficult, if one chose the department will result in learner in the learning process in lectures, because less comfortable with the materials in the lecture and probably a lot of less-liked material. This will affect the child's achievement index (IP) that can be below the standard and worse the discharge of the student (DODrop Out) because it is declared not able to follow the education that followed. So the classification and recommendation of college majors for high school students who based on academic grades wrote can help high school students to determine the proper choice. The calculation of the study is calculated separately for the Naive Bayes algorithm used to classify student learner data into the faculty class and Weighted Product (WP) is used to help determine the exact majors based on the majors in the faculty predetermined by the Naive Bayes algorithm. By using the Naive Bayes-WP algorithm, the system's average accuracy reaches 82%.
Implementasi Metode Extreme Learning Machine (ELM) untuk Memprediksikan Penjualan Roti (Studi Kasus : Harum Bakery) Luqman Hakim Harum; Nurul Hidayat; Ratih Kartika Dewi
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

Harum Bakery is a bread store located in Malang Regency area. The number of bread sales in this company is uncertain everyday. It makes the company difficult to predict the sale of breads per day. To avoid loss, this company need a system to predict sales prediction easily. With the prediction of the sale, the writer hope that the company can suppress the losses that may occur and optimizing company's profit. This research use Extreme Learning Machine (ELM) method which is method of Artificial Neural Network(ANN) to predict bread sales at Harum Bakery. The Process of prediction using ELM method is started from data normalization, then training process, testing process, find the error value using Mean Square Error (MSE) method to find the smallest error value with some testing, and data denormalization the ELM method is feedforward method with a single hidden layer which is called Single Hidden Layer Feedforward Neural Network (SLFNs). The main purpose of this method is to improve the weakness of other feedforward artificial neural networks, especially in the learning speed. Based on some tests that have been done, the smallest error rate is 0,01616 for white bread using 7 neurons, 4 features, and 5 months of sales data, the best MSE is 0,02839 for sweet bread using 2 neurons, 5 features, and 4 months of sales data, and 0,00812 for cake bread using 7 neurons, 4 features, and 3 months of sales data.
Pembangunan Aplikasi Android Rekomendasi Tempat Rental Motor Di Kota Malang Dengan Metode AHP TOPSIS Berbasis Location Based Services Jeriko Hosea Julanto; Komang Candra Brata; Ratih Kartika Dewi
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

There are very few native townspeople of Malang City, who know the motorcycle rental in Malang City. In fact, as already know, the city of Malang is a tourist city which is always crowded by visitors. Plus each person has different criteria in choosing a motorcycle rental. Scratch facilities make users have difficulty in choosing a motorcycle rental in Malang City. To solve these problems required decision support system (DSS) to support and facilitate the user in choosing a motorcycle rental. The DSS method must have a low time complexity. Application android recommendation of motorcycle rental in malang city by AHP TOPSIS method based on location based services is an application that gives recommendation of motorcycle rental in malang city according to weight of interest criteria entered by user. These criteria include the price of 125cc motorcycle rental per day, the location of the motorcycle rental, the popularity and rating of the motorcycle rental. Tests of this research resulted that the percentage of usability reached the value of 82.82%, where this value is included in good category, then the functional test result is 100%, then the conformity test also stated that this application has 90% test result value.
Pengembangan Sistem Informasi Pelayanan Ibu Hamil Pada Platform Android Berbasis Lokasi (Studi Kasus: Puskesmas Karangploso Kabupaten Malang) Muhammad Hafidz Rahman; Herman Tolle; Ratih Kartika Dewi
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

During the period of 2013 to 2015, the mortality rate of pregnant women and infants in Malang Regency is still high. Based on data obtained from the Health Office of Malang Regency, 2013 until 2015 on average as many as 125 babies and 15 pregnant women die every year. PUSKESMAS as one of the health worker has done its best to help reduce AKI(Maternal Mortality Rate) in Malang Regency. But in the process of implementation, PUSKESMAS often encounter obstacles in the data collection of pregnant women. In fact, data collection is still using manual method so that it can cause difficulties in data collection and checking. In addition, if there is an emergency condition which requires the PUSKESMAS to take action, it is often encountered an obstacle in finding the patient's address because of poorly recorded rural road conditions. Whereas at that time it takes time and action as effectively as possible to avoid events that can be fatal to the safety of mother and child. Solutions that can be used by PUSKESMAS by utilizing technology in doing data collection to pregnant mother that is by making information system that can record pregnant woman who do control. PUSKESMAS midwife can also do data collection of pregnant women using location based service technology, making it easier for PUSKESMAS to find the location of the patient's house.
Implementasi Metode Naive Bayes-Certainty Factor Untuk Identifikasi Cedera Pada Pemain Futsal Rhiezky Arniansya; Nurul Hidayat; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

There are still many futsal players who think that injury can recover quickly without having to go through the right handling. There are injuries that injury can get worse if the initial handling is wrong. That's because the lack of understanding of players about injury. Injury treatment can be done by the physiotherapist but it was hit because of the lack of physiotherapist available for handling. In the research will be made an identification system to reduce these limitations by implementing the method of Naive Bayes-Certainty Factor-based android to diagnose the injury that affects futsal players. The results show that the use of Naive Bayes-Certainty Factor method has accurate results and a good and accurate diagnosis, since the output produced by the system has an accuracy of 88.57%. Hopefully with this application will be able to help the players futsal to know injury or handle injury and add insight about any injuries that can befall him.
Prediksi Harga Batu Bara Menggunakan Support Vector Regression (SVR) Olivia Bonita; Lailil Muflikhah; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Coal price prediction is needed as support for coal user industrial to buy coal. Prediction result can be used to make next budgeting. This research uses Support Vector Regression (SVR) method to predict coal price. SVR is applied through data normalization, hessian matrix calculation, α searching through sequential learning, and regression function calculation. Kernel for hessian matrix stage can determine accuracy of prediction, so in this research Gaussian RBF kernel and ANOVA kernel are used and analyzed the effects. To obtain predictive results with good accuracy, testing of each parameter is performed and evaluated by mean absolute percentage error (MAPE). The average of MAPE for testing are 9,64% with Gaussian RBF kernel and 8,38% with ANOVA kernel, which are categorized good, on 48 training data for 12 testing data and optimal parameters are ε 0,00001; cLR 0.01; C 0.5; λ 0.5 with Gaussian RBF kernel and 1 with ANOVA kernel. SVR gives the most optimal result when predicting the next month price. The predicted results of the two kernels are not too different, but the ANOVA kernel works better on this coal price data.
Perbaikan Usability Aplikasi Pemesanan Tiket Bioskop Menggunakan Metode Usability Testing dan USE Questionnaire Moch Dian Fahmi; Hanifah Muslimah Az - Zahra; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Usability is one of the important aspects to be a benchmark for the quality of an application can be said to be good. Usability is used to measure how an application can be used according to the user's desire to achieve the desired goal, supported by the ease of the user to use the application interface. This cinema ticket booking application is an application that is used to book tickets in theaters throughout Indonesia can be accessed through applications on the Android platform. Based on the problems found in the results of user reviews on the platform there are still problems experienced by users, then usability measurement is used to measure the usability level of the application. Testing using usability testing method is done directly to the user, done by giving a task scenario. This test is carried out twice, the initial test to find out the initial usability value and the existing problems, then based on the existing problems given recommendations for improvements in the form of prototypes which are then re-tested to get the final usability value, after that the test results will be compared to get the usability value of the application this cinema ticket booking after repairs and before repairs. When testing there were three stages, namely, usability testing, filling out questionnaires and conducting interviews. Filling in the questionnaire is supported by USE Questionnare which has four parameters, namely Usefulness, Ease of Use, Ease of Learning, Satisfaction, the results of which will be processed and produce usability values ​​in this cinema ticket booking application. Improvements made refer to Material Design and Color Comparison Websites to get good recommendations. The initial test results obtained usability value of 57.4% categorized as sufficient predicate and the final test results obtained 83.1% were categorized as very good
Co-Authors Adam Hendra Brata Ade Armawi Paypas Aditya Purwa Pangestu Afrizal Fath Rahman Agi Putra Kharisma Agi Putra Kharisma, Agi Putra Ahmad Aulia Fahmi Ahmad Wildan Rizaldy Akhmad Syururi Alexandrio Kharisma Putra Marasin Alfi Musyaffa Ghossa Almira Kalyana Alsiendo Dewantara Amalia, Annisah Andriano Eucharistia Wibowo Andrianto Setiawan Angel Anggina Nasution Annisah Amalia Aryo Pinandito Asep Ardi Herdiyanto Askia Sani Asrina Fitri Asti Dhiya Anzaria Atikah Nabila Bella Dwi Rahmatulia Bella Rhobiatul Adhawiyah Brilliant Richky Setya Putra Candra , Ersya Nadia Candra Dewi Carly Vyoletta Siagian Chastine Fatichah Chindy Aulia Sari Chrysler Imanuel Dani Kurnianto David Hosea Sipahutar Dea Annisa Larasati Deni Kusuma Fajri Desy Diandra Bestari Devita Natalia Krisdayanti Dewantoro, Mury Fajar Dheanisa Putri Rahayu Diah Priharsari Dieni Anindyasarathi Dimas Angga Nazaruddin Djohansyah Putra Dwi Astuti Dwi Juni Kartika Dwi Yovan Harjananto Dwi Yovan Harjananto Edy Santoso Elvine Ivana Kabuhung Erastus Mauliate Eriq Muhammad Adams Jonemaro Erlangga Rizki Pratama Fais Al Huda Faishal Pradipta Astungkoro Farah, Najla Alia Faris Abdi El Hakim Fasya Yahya Febrian Diaz Maulana Felinda Gracia Lubis Fendra Gunawan Ferdinan Oky Fahrerri Fiqih Yanfirdaus Afandi Fitra Abdurrachman Bachtiar Frondy Fernanda Ferdianto Ganda Adi Khotarto Gede Satria Harinamanata Gerald Marihot Hasiholan Ginardi, R.V. Hari Hadi Dwi Abdullah Hamid Hanifah Muslimah Az - Zahra Hanifah Muslimah Az-Zahra Healtho Brilian Argario Hema Prasetya Antar Nusa Herman Tolle Heru Budiyanto Heru Putra Hutomo Ardianto I Made Wira Satya Dharma Ibnu Rakha Icha Gusti Vidiastanta Ignasius Try Sevandri Ikhsanul Isra Yunelfi Imam Cholisoddin Imam Cholissodin Imam Cholissodin Imron Hari Budisetyo Iqbal Santoso Putra Irsyad Rifqi Arrazaq Ismail Risky Rahmansyah Issa Arwani Jeriko Hosea Julanto Jermias Kristian Jiwandani Andromeda Jodie Rizky Hidayat Jonemaro, Eriq Muhammad Adams Julian Fuad Fauzi Kadek Dwi Aryasa Komang Candra Brata Komang Yoga Arimbawa Kurnia S., Primananda Labib Alfaruqi Ibrahim Lailil Muflikhah Luqman Hakim Harum Lutfi Fanani Lutfi Fanani M. Salman Ramadhan Mahardeka Tri Ananta Mahendro Agni Giri Pawoko Marji Marji Moch Dian Fahmi Moch Irfan Prayudha Adhianto Mochammad Faizal Satria Rahman Mochammad Taufiqi Effendi Mohammad Arda Dwi Ardianto Mona Adelina Muh Wildan Shalahuddin Muhamad Arifin Ramadhan Muhamad Danis Firmansyah Muhamad Hilmi Hibatullah Muhammad Abdul 'Alim Muhammad Aminul Akbar Muhammad Aminul Akbar Muhammad Aufa Athallah Muhammad Dimyathi Muhammad Hafidz Rahman Muhammad Kurniawan Khamdani Muhammad Rasyid Ridho Muhammad Regian Siregar Muhammad Rifqi Ramdhani Muhammad Robby Dharmawan Muhammad Salman Ramadhan Mujahid Bariz Hilmi Mustika Mentari Nabila Fairuz Zahra Nabila Nabila Nabila Nabila Nadia Putri Nur Ramadhani Naufal Afif Bunyamin Navisa Putri Maulidia Nisrina Dhia Ufaira Novianto Donna Prayoga Nugroho Dwi Saksono Nurizal Dwi Priandani NURUL HIDAYAH Nurul Hidayat Nurul Huda Abdullah Olivia Bonita Pungky Aryati Putut Abrianto Randy Cahya Wihandika Raras Kirana Amaranggana Rebecca Octaviani Renno Andika Syawaludin Restu Fitriawanti Retno Indah Rokhmawati Reynald Hermanto Simanjuntak Reza Rahardian Rhiezky Arniansya Rhyzoma Grannata Rafsanjani Ricky Irfandi Riswan Septriayadi Sianturi Rizal Rudiantoro Rizki Wulyono Propana Sodiq Rizky Adytia Ivan Rahman Sandy Ikhsan Armita sarwo sri, sarwo Steven Willy Sanjaya Sukmo Wardhono, Wibisono Sutrisno Sutrisno Swastika Akbar Umardani Syndu Pramanda Galuh Widestra Tifanny Rizka Faressi Tri Afirianto Tri Afirianto Tri Afirianto, Tri Usman Adi Nugroho Valen Novandi Kanasya Vicky Robi Wirayudha Wanda Septia Dewi Lestari Wardhani, Shinta Kusuma Wiandono Saputro Wibisono Sukmo Wardhono Wibisono Sukmo Wardhono, Wibisono Sukmo Widhi Yahya Yehezkiel Windriono Yori Tri Cuswantoro Yuita Arum Sari Yuita Arum Sari Yusuf Ramadhani Ziya El Arief Zulfikar Faras Fadila Zumrotul Islamiah