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INDONESIA
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Published by Universitas Brawijaya
ISSN : -     EISSN : -     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering
Jurnal Pengembangan Teknlogi Informasi dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya merupakan jurnal keilmuan dibidang komputer yang memuat tulisan ilmiah hasil dari penelitian mahasiswa-mahasiswa Fakultas Ilmu Komputer Universitas Brawijaya. Jurnal ini diharapkan dapat mengembangkan penelitian dan memberikan kontribusi yang berarti untuk meningkatkan sumber daya penelitian dalam Teknologi Informasi dan Ilmu Komputer.
Arjuna Subject : -
Articles 6,923 Documents
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Perbandingan Usability Pada Learning Management System Moodle dan Edmodo Dengan Menggunakan Metode Heuristic Walkthrough (Studi Pada SMKN 8 Malang) Hardy Padmayudha Nugraha; Admaja Dwi Herlambang; Hanifah Muslimah Az-Zahra
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

Edmodo and Moodle are systems which can be use in learning management. These two systems are popular in middle school and higher educational level. But, not all of the instructors know how to operate these systems caused by complicated design that have an impact in usability and learnabililty aspect. In order for usability reached properly, these two systems need to be evaluated with cognitive walkthrough and heuristic evaluation, six evaluators and comparative research. There are 15 problems in Moodle and seven problems in learning ability using the cognitive walkthrough method. For research with heuristic evaluation methods, there are 16 problems in Moodle with the highest frequency is H-8 (Aesthetic and minimalist design), as well as total severity rating is 2.50. As for the heuristic evaluation method in Edmodo, there were 15 problems with the highest frequencies are: (1) H-1 (System status visibility); (2) H-2 (Suitability between the system and the real world); (3) H-4 (Consistency and standards); (4) H-7 (Flexibility and efficiency of use); (5) H-8 (Aesthetic and minimalist design); and (6) H-10 (Help and documentation) as many as two for each principle, and the total average number of severity rating is 2.30. Edmodo is recommended because of it's user interface design that can be easily recognized by user. While, Moodle is recommended for an expert user that needs a LMS that has complex feature.
Klasifikasi Penurunan Fungsi Kognitif Pasien Stroke Menggunakan Metode Klasifikasi Random Forest Muhammad Shidqi Fadlilah; Randy Cahya Wihandika; 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

Stroke is a disease that attacks all human, regardless of race, gender, and age. One of the effects of stroke is a decreased cognitive function. A human brain has many nerves, one of them is regulating the work of the human's cognitive function. Based on research by Wardhani (2015), factors that decreasing cognitive function consist of thirteen factors. So, a system that can detect a decreased cognitive function on a stroke patient is needed. So in this research, we make a system that could be used to classify the decreasing cognitive function using a random forest method. the random forest was chosen because this method is good for categorical data. Based on the testing result, the best tree that builds in this system was 100 trees. The average result of the accuracy obtained from all experiments were 53.094%. That number means that the system is still far from perfect. One of the factors that caused this system's imperfection was the distribution of training classes were not evenly distributed.
Pengembangan Sistem Informasi Manajemen Keuangan Peternakan Kambing (Studi Kasus: Yoga's Farm Kabupaten Tulungagung) Rizki Indra Fanani; Ismiarta Aknuranda; Yusi Tyroni Mursityo
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

The need for information at this time is very important in various aspects of life. Yoga's Farm is a farm that runs the process of fattening goats, selling goats, selling cattle medicine, and selling various types of animal feed. This farm has enough benefits but all financial reporting is still not neatly arranged. Financial reporting is only done manually, this results in many finances that are not defined as useful. From the problems that arise, an information system is developed that will facilitate the processing of financial data. Financial reporting systems can also be printed and display the benefits of goat farming. The method used in development is waterfall. Whereas the framework used in developing this information system is Laravel. Testing for functional systems is a validation test, the results of validation testing state that the system is 100% valid, indicating that it is functioning properly and in accordance with user expectations. Testing for nonfunctional requirements is testing browser compatibility, the results suggest that the system can run on 9 different browsers. However, in IE (Internet Explorer) version 11 there are critical issues, 9 major issues from 16 browser versions and 5 minor issues from 10 browser versions.
Klasifikasi Penyakit Kelamin Pada Wanita Dengan Menggunakan Kombinasi Metode K-Nearest Neighbor Dan Naive Bayes Classifier Dimas Angga Nazaruddin; Fitra Abdurrachman Bachtiar; Ratih Kartika Dewi
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

Venereal or Sexually Transmitted Disease (STD) are still a public health problem in developed and developing countries. Expert stated that health problems caused by venereal disease are higher in women. symptoms experienced have similarities between one and other venereal disease. Lack of knowledge possessed by patients can cause more severe. Therefore, to reduce the level of problems in self-examination, research is needed to classifying female veneral disease to find out the types of infectious diseases. Various methods can be used in classification. including using K-Nearest Neighbor (KNN) and Naive Bayes Classifier. The combination of these two methods has advantages that include no need to discretize more on continuous variables. So that in this study the KNN and Naive Bayes Classifier method will be combined to classify venereal diseases, especially for women because both of these methods have a high degree of accuracy in studying a disease so it is expected to predict probabilities based on testing data. In this study the accuracy test of the combination of the K-Nearest Neighbor and Naive Bayes Classifier methods was 97.5% using an average accuracy and 99.17% using the confusion matrix for the nearest number of neighbors as K = 5.
Rekognisi Wajah Pada Sistem Smart Class Untuk Deteksi Kehadiran Mahasiswa Menggunakan Metode Viola Jones dan Local Binary Patterns Histograms (LBPH) Berbasis Raspberry Pi Fitrahadi Surya Dharma; Fitri Utaminingrum; Rizal Maulana
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

Facial recognition is one of the techniques in computer vision that is able to recognize a person's face from an image. The application of face recognition into the presence system is very important considering that there are still cases of attendance data manipulation by students in the presence system using manual - filling signatures on the attendance sheet. Lack of tight supervision in filling attendance sheets is an event that is vulnerable to cases of manipulating attendance data. Therefore in this study try to present a presence system that uses images to find out the presence of students. The trick is to take pictures using a camera that is placed in front of the class, just above the blackboard facing the student. From the images taken, the system will then detect the faces of students using the Viola Jones method of the OpenCV library combined with YCbCr skin color pixel detection to avoid false detection. And for face recognition students will be using the local binary patterns histograms method from the OpenCV library. Accuracy results obtained by the system showed the level of detection accuracy of 82.33% and recognition accuracy of 50.83% in the morning, 61.11% during the day, and 58.89% at night. The average total computing time for the detection of one student is 0.293 seconds, two students 0.297 seconds, three students 0.317 seconds, four students 0.313 seconds, five students 0.31 seconds and six students 0.307 seconds. While the average total face recognition computing time for one student is 2.17 seconds, two students 2.58 seconds, three students 3.01 seconds, four students 3.38 seconds, five students 3.78 seconds, and six students 4 .12 seconds.
Implementasi TOPSIS Pada Sistem Rekomendasi Tempat Latihan Bela Diri Di Kota Malang Berbasis Lokasi Ade Armawi Paypas; Ratih Kartika Dewi; Komang Candra Brata
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

There are various types of martial arts that exist in the world, including silat from Indonesia, kung fu from China, and karate from Japan. Because of the many types of martial arts, with the growing age, more and more martial arts training centers are scattered throughout the world. But with so many martial arts places, sometimes people don't know which is better. With this application, users can get recommendations for martial arts training sites based on GPS-based locations. The recommendation system for the place of self-defense training is designed using the TOPSIS method with data criteria in the form of distance between users and practice sites, training costs in 1 month, and the amount of training time in 1 week, and implemented on the android platform. The results of this blackbox test show that 100% of the functionality is valid. Other tests carried out are testing the validation of algorithms, where testing is done by comparing the results of the system with manual calculations. The results of system calculations and manual calculations are 100% the same, and rank consistency testing, where testing is carried out to determine the consistency of the recommendations when the number of criteria is added or reduced. The rank consistency test results show that the ranking results are consistent when the criteria are added, and will change when the number of criteria is reduced.
Klasifikasi Berat Badan Lahir Rendah (BBLR) Pada Bayi Dengan Metode Learning Vector Quantization (LVQ) Suryani Agustin; Budi Darma Setiawan; Mochammad Ali Fauzi
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

Low Birth Weight (LBW) is the condition as a birth weight of a baby less than 2500 grams or 2.5 kg.. LBW is a factor of infant mortality in Indonesia. The prevention and treatment of pregnant women when they know they will give birth to babies with LBW are very necessary, in order to minimize the death during the birth process. Therefore, it is expected that the existence of a low birth weight classification system in infant can help to identify the condition of the baby in pregnant women before the baby is born. This research use the Learning Vector Quantization (LVQ) method with 96 data and 6 features, there are age, education, parity, birth interval, hemoglobin and nutritional status. Those who will classify into two classes first is case class, which means the baby is born with LBW and the control class means that the baby is born without LBW. Based on the results of testing, the system produces an average accuracy is 60.5% using optimal parameters for learning rate 0.1, learning rate decrement 0.1 and maximum epoch is 5. In the k-fold cross validation testing the best accuracy value is 58.3% and the average accuracy is 46.85%.
Sistem Irigasi Pada Sawah Bertingkat Menggunakan Wireless Sensor Network Amrin Rosada; Mochammad Hannats Hanafi Ichsan; Gembong Edhi Setyawan
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

Agriculture is a livelihood for the people of Indonesia. Agriculture in Indonesia is carried out in a traditional system and carried out on makeshift land. The problem that is often experienced by farmers is the problem of irrigation such as being unable to check and control irrigation systems and one of the most important factors in increasing agricultural production. Irrigation is the activity of giving water to agricultural land with the aim of making the soil wetter so that the roots of plants grow well. To help farmers in conducting irrigation, WSN technology is needed to control and check irrigation systems. In this modern era the application of netwrok wireless sensors has greatly increased, given its ability to distribute and disseminate data wirelessly. In this study will make an irrigation system using a wireless sensor network to facilitate farmers in conducting irrigation. By using Arduino Uno as a microcontroller to process data, ultrasonic sensors for reading distance or high, servo as open doorstop, NRF24L01 as communication between nodes and bluetooth is used for communication with Android. The test results that have been carried out by this system can run as desired where each node can communicate with each other, servo works well can open and close water channels and ultrasonic sensors are able to detect water levels. From the results of the experiment processing time of 15 times land 1 to land 3 or land 3 and land 1 is 524.66 ms and from land 2 to land 3 or land 3 to land 2 is 405.33 ms.
Optimasi Fuzzy Time Series Menggunakan Algoritme Particle Swarm Optimization Untuk Peramalan Produk Domestik Bruto (PDB) Indonesia Dloifur Rohman Alghifari; Bayu Rahayudi; Candra Dewi
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

As one of the input indicators for development programs. This Gross Domestic Product (GDP) forecasting is expected to provide information about economic growth and performance in Indonesia. Data sources of GDP usually come from survey results or from administrative records from various institutions. Sometimes the source data is incomplete or not available when calculating GDP values, it must be determined how to calculate the GDP value so that it can be used to estimate GDP forecasting using fuzzy time series. To improve forecasting accuracy, we use fuzzy time series optimization intervals using particle swarm optimization (PSO). Based on the parameters obtained with a dimension length of 40, many particles of 40, 450 for maximum iteration, the value of c1 and c2 is equal to 1.5 and for inertial weight of 0.3, the forecasting error rate generated using MAPE is 2.48% of the 10 test data. These results indicate good forecasting ability with a low error rate. The comparison of forecasting results for the proposed method is slightly better than the fuzzy time series method with the determination of the average interval based on MAPE 2.66%. But it is no better than the linear regression method with MAPE 1.52%
Pengembangan Sistem Informasi Layanan Pemeriksaan Kesehatan Tenaga Kerja Dengan Metode Rational Unified Process (Studi Kasus Klinik Argaraya Medika Malang) Alfan Babtista Yordan; Yusi Tyroni Mursityo; Djoko Pramono
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

Malang, one of the regions in East Java that contributes the highest number of migrant workers in Indonesia can be an advantage for the Argaraya Medika Clinic in developing business and labor inspection services. However, the large number of patients who register for the health check-up of workers every hour of service makes it difficult for officers to handle the inspection files and queue of patients. The registration process of patients that takes a long time because it is done twice on the frontoffice and polyclinic causes the length of the queue. Another problem that is faced is the easy loss of the old data checking and data recording form files. Based on these problems the solution that can be applied is to develop an information system for labor inspection services that can help the patient registration process, check the inspection work, store inspection data, and help the recording of inspection data. The system was developed using the Rational Unified Process (RUP) method with the stages of inception, elaboration, construction, and transition phases. The labor health inspection service information system has been implemented with the results of validation testing to test the system's functionalities with 100% valid results and compability testing to test non-functional requirements resulting in 2 critical issues in 2 browser applications. User Acceptance testing is carried out with seven correspondents from each user indicating that the information system of labor inspection services is well received by the user.

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