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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 6,972 Documents
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Analisis Struktur dan Pola Berjalan Robot Humanoid Menggunakan Metode Inverse Kinematic pada MATLAB Muhammad Prabu Mutawakkil; Rizal Maulana; Agung Setia Budi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Today, the development of robot was growing so quick, one of them is Humanoid Robot. As like the name, Humanoid Robot have feet that have walks and shaped like human does. This robot has two feet that consisted of three DoF (Degree of Freedom) for one of each foot. Humanoid Robot use Inverse Kinematic method to walk which using end of effector as the coordinate. The result that suggested from Inverse Kinematic method were the coordinate destination. The implementation of Humanoid Robot we do it on MATLAB and Simulink to test about the mechanism from the robot if it were applied on software. The difference was shown for the avability of the hardware and its tools and the result sometimes would be different if applied in real world. There are some differences when robot got implemented compared with physical ones. From this research, there are 11 trials to measure about success rate for robot to able to walk successfully from the robot if their variables from physical appereances were modified. As the result, there are 54,54% success rate compared with the original variables that got from trial and error.
Sistem Klasifikasi Kesegaran Daging Sapi berdasarkan Citra menggunakan Metode Naive Bayes berbasis Raspberry Pi Habib Muhammad Al-Jabbar; Hurriyatul Fitriyah; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 4 (2021): April 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Beef is one of the commodities that has contributed to the improvement of public nutrition, particularly the need for animal protein. Fresh beef is meat that is fresh red in color, starting from being cut up to 10 hours. So far, evaluation of freshness and identification of meat composition has been done manually by means of human visual observations. Due to human limitations, there are often different perceptions of each observer. On this basis, as an effort to obtain beef freshness accurately, this research has made a tool that can detect the freshness of beef with the help of digital image computing. By using the Raspberry Pi as a mini computer, a camera as a sensor and image processing which is then classified by Naive Bayes, this system can work properly, it can be proven by the output of the accurate classification of beef freshness. The choice of the naive Bayes method is based on the fact that this method is a very good classification method in which the class of freshness types is known from the start. This method can also work even though it only uses a little training data. When there is a slight change in training data, the naive Bayes method also adapts quite well. The results of the beef color conversion process are then classified at the color level based on SNI standards. From 40 training data and 20 tested data, an accuracy of 95% and an average computation rate of 0.009094 seconds.
Pengembangan Sistem Penjualan Koperasi POM AU Lanud Iswahjudi Magetan Kasfia Jihan Dzahabiyyah Hasna'; Denny Sagita Rusdianto; Lutfi Fanani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 10 (2020): Oktober 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PRIMKOPAU "WIRA WASKITA" SATPOM or the POM AU cooperative Iswahjudi Air Force is a primary cooperative that has a waserda shop or unit. In sales activities, members can make payments in two ways, namely cash and debt. Every time there is a sales transaction, the seller will make records. In recording this, sellers often forget or enter incorrect notes because it is still done manually. In addition, the cooperative also provides credit for goods in collaboration with other stores. Each month, the shop department sends an invoice to the payer, which will be deducted from the member's salary. In searching and calculating these bills, it took the store department a long time to produce a list of these bills. With a system in the form of a website that can record sales, be able to calculate installments automatically, generate a list of bills, good stock management of goods, can help and prevent cooperatives from losing. In carrying out its development, it resulted in 17 functional requirements and 1 non-functional requirement. System testing is carried out using white-box testing for unit testing, black-box testing for functional testing and compatibility testing to find out whether the system can run on various hardware and various software.
Pengembangan Antarmuka Website Awniraya dengan Menggunakan Metode Design Thinking Amirul Adila Nyata; Yusi Tyroni Mursityo; Kariyoto Kariyoto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Untuk dipublikasikan di Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)
Prediksi Omzet Restoran Haltoy Corner menggunakan Metode Recurrent Extreme Learning Machine (RELM) Ridho Ghiffary Muhammad; Muhammad Tanzil Furqon; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Haltoy Corner Restaurant is a new restaurant in wonosobo city that is famous for its beautiful scenery. Currently, Haltoy Corner is still not able to do the management of the number of employees and the allocation of turnover well. This led to the need for a turnover prediction system for Haltoy Corner to help optimize the number of employees to be employed. Extreme Learning Machine (ELM) is one of the prediction methods that have good accuracy and relatively fast training time, but in ELM the sequence of data has no effect so it can affect the accuracy for dataset timeseries such as Haltoy Corner turnover data. ELM developed a method to overcome this with Recurrent Extreme Learning Machine (RELM), this method adds recurrent to ELM so that it is better for dataset timeseries. The flow to conduct this research starts from data normalization, data training, data testing, data denormalization and finally the calculation of evaluation value. Based on the results of tests conducted using Haltoy Corner turnover data, an error value with Mean Absolute Precentage Error (MAPE) was obtained at the most optimal of 31.677%, with the number of eight features, the number of hidden neurons three, the number of context neurons five, and the comparison of the number of training data with data testing of 90%:10%.
Analisis Usability Aplikasi Mobile Layanan Paspor Online Menggunakan Metode Usability Testing (Studi Kasus : Kantor Imigrasi Kelas I Malang) Apriani Ingin Marito Tampubolon; Retno Indah Rokhmawati; Lutfi Fanani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 1 (2021): Januari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Layanan Paspor Online is a mobile application for online passport queue registration developed by Directorate General of Immigration Indonesia which has been implemented at Malang Class I Immigration Office. But in its application there are some problems such as the colors that are too flashy, the registration process is complicated, less attractive design, and less user friendly where people who lack of knowledge about technology find it difficult to use this application. Based on these problems, it is necessary to analyze and improve the user interface using usability testing method. The usability aspect used in this method are learnability, efficiency, error, and satisfaction. Respondents who participated in this study were 5 people for usability testing and 20 people for system usability scale questionnaire. The result of the learnability aspect measured using success rate metric increased from before the improvement by 90% to 98,6% after the improvement. The efficiency aspect measured using time based efficiency metric increased from before the improvement by 0,2 goals/sec to 0,3 goals/sec after the improvement. The error aspect measured using defective rate metric decreased from 8,90% to 1.1%. The satisfaction aspect measured using System Usability Scale (SUS) questionnaire increased from before the improvement by 66 to 77 after the improvement. From these result, the improvement given to Layanan Paspor Online application can fix the problem found.
Pengembangan Aplikasi Rekomendasi Makanan Bagi Pasien Hiperkolesterolemia Berbasis Web Ayuri Alfarianti; Agi Putra Kharisma; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Penyakit Hiperkolesterolemia merupakan penyakit yang dapat memicu terjadinya penyakit lain seperti penyakit kardiokasvular, jantung koroner dan stroke. Salah satu solusi yang dapat dilakukan bagi pasien hiperkolesterolemia adalah dengan mengonsumsi makanan diet yang berpedoman pada aneka ragam makanan gizi seimbang. Konsultasi dengan ahli gizi dapat membantu pasien dalam mengatur kebutuhan gizi seimbang yang harus dipenuhi oleh pasien. Namun terdapat masalah utama yaitu sulit menentukan makanan yang harus dikonsumsi perharinya. Pasien tidak diberi detail variasi makanan yang harus dikonsumsi, melainkan diserahkan kepada masing-masing pasien. Berdasarkan permasalahan tersebut diperlukan sebuah aplikasi rekomendasi makanan bagi pasien hiperkolesterolemia. Pada penelitian yang dilakukan, diperoleh 21 kebutuhan fungsional dan 1 kebutuhan non-fungsional berdasarkan hasil analisis kebutuhan. Masing-masing kebutuhan fungsional dan non-fungsional dimodelkan dengan menggunakan usecase diagram dan usecase scenario. Selanjutnya dilakukan perancangan aplikasi yang dijadikan acuan untuk tahapan implementasi. Aplikasi yang dikembangkan merupakan aplikasi berbasis web. Aplikasi diimplementasikan menggunakan beberapa bahasa pemrograman dengan bantaun framework Codeigniter. Selain itu juga diterapkan algoritme genetika sebagai metode untuk menentukan rekomendasi makanan yang sesuai. Pada tahapan pengujian dilakukan pengujian unit, pengujian integrasi, pengujian validasi dan pengujian compatibility. Pengujian ini menghasilkan 100% valid pada 37 kasus uji dan tidak ditemukan issue pada saat pengujian compatibility dengan menggunakan Sortsite.
Kendali Posisi Robot Beroda Dengan Sistem Global Positioning System (GPS) Menggunakan Proportional, Integral dan Derivative (PID) Berbasis Arduino Mega 2560 Duwi Hariyanto; Eko Setiawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 1 (2021): Januari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

A wheeled robot is a technological innovation that makes it easier to mobilize exploration. In carrying out the exploration, the wheeled robot has several obstacles, namely the unstable reading of the robot's position. From this problem, the researcher designed a wheeled robot position control system by adjusting the accuracy of the robot's position. The process of monitoring the position of the robot uses the Ublox Neo-6m GPS module which is controlled by the Arduino Mega2560. Latitude and longitude data obtained from the GPS sensor will be converted into a distance and processed into control. The control used to adjust the position of the robot is PID (Proportional Integral Derivative). For the calculation of PID, this research uses the Zigler-Nichols tuning method in getting to a point. In this study, several tests were carried out for the four controls. The results showed that they had a good response to P and PD controls. Because the two controls achieved set points and had a slight error, where the P control has reached the setpoint in 56.378 seconds with an error = 0.1026 meters with a Kp value of 9.4. Meanwhile, PD control in achieving the target takes 57.384 seconds with an error = 0.1481 meters with a value of Kp = 11.38 and Kd = 11.47.
Penentuan Kelayakan Debitur Menggunakan Metode Decision Tree C4.5 Dan Oversampling Adaptive Synthetic (ADASYN) Farhan Setya Dhitama; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 10 (2020): Oktober 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Credit is an activity or service that cannot be separated from life in the current era. Credit can also be interpreted as a loan of money, goods or services that have a limited time agreement and may include guarantees or not. Nowadays there are many companies in Indonesia that provide credit services. One of the challenges for companies engaged in credit provision is the credit that is delinquent. Less precisely judgment at the beginning debtors want to apply for credit being the cause of the credit that delinquent itself. This research aims to analyze and determine the feasibility decision of prospective debtor to receive credit from the credit provider bank in Lamongan. In the decision making system of credit eligibility, the method of decision Tree C 4.5 was used to classify into accepted classes or rejection potential debtors and also use Adaptive Synthetic (ADASYN) methods to perform oversampling processes on minority classes, as highly data that has been rejected is unbalanced in number with data that received credit decisions. The study uses the Decision Tree C 4.5 method as the debtor feasibility technique and the ADASYN method as an oversampling technique on the data that has the minority class. The features of the data used are Character, Capital, Capacity, Condition, Collateral, Age, and Dependents. The data to be used for classification calculations will be normalised using the Z-Score equation so that the data spread is not too wide. This research successfully develops a system that can classify debtor's eligibility using the Decision Tree C 4.5 and Adaptive Synthetic (ADASYN) methods for oversampling in the imbalance class. The test results show the best evaluation gained when the minor data sharing in training is 5 and in the testing amount of 2 and for the depth classification parameter of 1 and k is worth 3. Accuracy, Precision, Recall, and F-Measure obtained in this research is the Accuracy of getting 90%, Precision 100%, Recall worth 89%, and F-Measure is worth 94%.
Deteksi Kantuk pada Pengemudi melalui Jumlah Kedipan Mata Menggunakan Facial Landmark berbasis Intel NUC Dewi Amalia; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The level of traffic accidents is increasing every year, one of the causes is the driver who is tired and sleepy when driving. Therefore a system will be made to anticipate accidents by giving warnings in the form of writing and alarm. The system uses Intel NUC for processing, the webcam accepts inputs and monitors to see image captured by the camera and see information on the condition of the eyes and sleepy information. The method used is Facial Landmark for detection of eye areas on the face. For under-lighting or uneven lighting, use the feature of image thresholding, namely adaptive threshold gaussian. Detection of the eye area on the face and sleepiness is done with a camera within 30cm, 40cm and 50cm parallel to the shoulder or chest. This detection also uses the range of light intensity 0-49 lux and 50-400 lux. The average accuracy of Facial Landmark for detecting eye areas on the face with light intensity 0-49 lux is 93.33% and for light intensity 50-400 lux is 100%. While the average accuracy of drowsiness detection at 0-49 lux light intensity is 96.66% and for light intensity 50-400 lux is 98.88%. The average system accuracy is 97.77%. The fastest computing time of the system at 0-49 lux light intensity is 0.33 s and at light intensity 50-400 lux that is 0.34 s.

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