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Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control

kinetik
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Published by Universitas Muhammadiyah Malang

ISSN : 25032259 EISSN : 25032267 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control was published by Universitas Muhammadiyah Malang. journal is open access journal in the field of Informatics and Electrical Engineering. This journal is available for researchers who want to improve their knowledge in those particular areas and intended to spread the knowledge as the result of studies. KINETIK journal is a scientific research journal for Informatics and Electrical Engineering. It is open for anyone who desire to develop knowledge based on qualified research in any field. Submitted papers are evaluated by anonymous referees by double-blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully within 4 - 8 weeks. The research article submitted to this online journal will be peer-reviewed at least 2 (two) reviewers. The accepted research articles will be available online following the journal peer-reviewing process.

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Articles 526 Documents

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Design and Implementation of COTS-Based Aircraft Data Network Using Embedded Linux Wijiutomo, Catur Wirawan; Ariyanto, Endro
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 2, No 4, November-2017
Publisher : Universitas Muhammadiyah Malang

Aircraft Data Network (ADN) is a data communication developed specifically for the aircraft environment. In such environments required data communication system that can work in real time and has a high level of reliability. One of the standards in ADN is Avionics Full-Duplex Switched Ethernet (AFDX) based on the ARINC 664 specification that is data communication standard for ADN that uses IEEE 802.3 standard on physical layer 1 and 2. It becomes the gap and challenge to implement the standard on the component of COTS By utilizing Linux-based embedded systems. The features designed and implemented in this paper are the switching and fault tolerant data components of ARINC 664. From the tests obtained, several results show that ADN functional features can be implemented and can simulate ADN mechanisms including fault tolerance capabilities. But there are performance limitations that the average jitter value of 3380 microseconds obtained has not met the requirements for use on aircraft that should be in the range of 500 microseconds.

Perancangan Chatbot Pusat Informasi Mahasiswa Menggunakan AIML Sebagai Virtual Assistant Berbasis Web Maskur, Maskur
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 1, No 3, November-2016
Publisher : Universitas Muhammadiyah Malang

Seiring perkembangan teknologi dan keinginan program studi teknik informatika untuk mengembangkan layanan terhadap mahasiswa, informasi yang diperoleh melalui sistem informasi dan chatting yang dilakukan antara pengguna dengan pihak Virtual Assistant. Penelitian ini bertujuan untuk membangun chatbot yang mempunyai tujuan sebagai Virtual Assistant yang memberikan informasi kepada mahasiswa melalui data yang tersimpan pada sistem yang berisi informasi mengenai program studi teknik informatika dan penambahan pengetahuan baru apabila data yang tersimpan tidak ditemukan. Pada perancangan dan implementasi perangkat lunak ini menghasilkan sebuah prototipe Chatbot yang dibangun dengan menggunakan mesin ALICE sebagai penerjemah AIML. AIML ini menyebabkan Chatbot dapat mengintegrasikan input yang diterima berupa input text. Sehingga akan dihasilkan percakapan antara pengguna dan program. Dengan pemanfaatan chatbot yang telah dilengkapi dengan informasi berupa audio, membuat pengguna dapat lebih mudah mendapatkan informasi yang berasal dari database yang diinformasikan kepada pengguna. Dari hasil pengujian verifikasi, pengujian validitas dan pengujian prototipe yang dilakukan sistem berjalan dengan baik sesuai dengan perencanaan.

Comparative Analysis of Tracking Objects Using Optical Flow and Background Estimation on Silent Camera Supriyatin, Wahyu; Ariestya, Winda Widya; Astuti, Ida
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 2, May-2018
Publisher : Universitas Muhammadiyah Malang

Tracking and object is one of the utilizations on the field of the computer vision application. Object tracking utilization as a computer vision in this study is used to identify objects which exist within a frame and calculate the number of objects passing within a frame. The utilization of computer vision in various fields of application can be used to solve the existing problems. The method used in object tracking is by comparison between optical flow estimation method with background method. The test is conducted by using a still camera for both methods by making changes to the parameter values used as a reference. The results of the tests, conducted on the three video objects by comparing the two methods show a Total Recorded Time better than those of the background estimation method, being smaller than 100 seconds. Testing both methods successfully identifies the object tracking and calculates the number of passing cars.

Front and Back Matter Volume 3 Number 2 Waskito, Adhitya Dio
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 2, May-2018
Publisher : Universitas Muhammadiyah Malang

Case Based Reasioning (CBR) for Medical Question Answering System Basuki, Setio; Rizky, Alfira; Wicaksono, Galih Wasis
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 2, May-2018
Publisher : Universitas Muhammadiyah Malang

In this research, the researchers implement a medical Question Answering System (QAS), a complaint system in the form of sentences or paragraphs of questions about the complaint (illness) suffered by a person. Afterwards, the system will give answer to the questions with answers in the form of diagnosis based on the system knowledge. The system in this study has knowledge of the system obtained based on Case Based Reasoning (CBR) method from the previous cases stored in the database. When there is a new case, the system will perform a matching process using CBR and Sorenson Coefficient calculations to find out which the previous cases have the highest percentage of matches with the new case. Then the selected previous cases will be taken and given to the new case. Testing is processed by using 2 types of testing, expert validation testing with result of 28 data of appropriate test from 30 test data and accuracy testing resulting of 93,33% from the appropriate test data.

Generating Indonesian Question Automatically Based on Bloomâs Taxonomy Using Template Based Method Kusuma, Selvia Ferdiana; Alhamri, Rinanza Zulmy
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 2, May-2018
Publisher : Universitas Muhammadiyah Malang

In education field, evaluation is needed to know the extent to which the learning process has been done. The evaluation process can be done through the provision of questions with varying degrees of difficulty. However, making questions with varying degrees of difficulty is not easy. Someone must understand the whole new materials to make the question. If there are a lot of materials, it takes a little time to change them to be a question. Therefore, it is necessary to automate the question generation process, in order to facilitate and accelerate the question generation process. This research introduces a template-based method to generate questions based on New Blooms Taxonomy. There were 4 stages in this research, dataset collection, pattern identification process, question generating process & classification, and final evaluation process result. The dataset consists of 60 samples of paragraphs that derived from 9 courses of study courses Informatics Engineering. The 60 paragraphs produced 278 sentences and 654 questions. The proposed method is capable of producing an accuracy of 81.65% to generate questions using New Blooms Taxonomy classification. So it can be concluded that the proposed method can be used to generate questions with varying difficulty levels in accordance with New Blooms Taxonomy.

Acquisition of Email Service Based Android Using NIST Umar, Rusydi; Riadi, Imam; Muthohirin, Bashor Fauzan
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 3, August 2018
Publisher : Universitas Muhammadiyah Malang

Email is one of the results of the development of information and communication technology. Email is widely used to exchange information by sending and receiving data, such as document files, images, correspondence and others. WithÂ the development of technology and information causing crimes in communicating also growing, the perpetrators of cyber crime commonly referred to as cybercrime. Any crime committed by cybercrime will surely leave the evidence, in this study will make the acquisition of android-based email using the method of national institute of standards and technology (NIST). The results obtainedÂ IPÂ address of the senders email header as digital evidence.

Purchase Recommendation and Product Inventory Management using Content Based Filtering with Sequential Pattern Mining Approach Raharja, Aditya Cipta; Sitanggang, Imas Sukaesih; Buono, Agus
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 4, November 2018
Publisher : Universitas Muhammadiyah Malang

Today, the product sales at XYZ Bookstore are increase in accordance to the trend in society. In that case, high sales must be supported by good supply and on target. Product sold based on needs of consumers will make possibility to achieve high sales. Using the Sequential Pattern Mining approach, we can specify sales patterns of products in relation to another products. SPADE (Sequential Pattern Discovery using Equivalence classes) is an algorithm that can be used to find sequential patterns in a large database. This algorithm finds frequent sequences of the sales transaction data using database vertical and join process of the sequence. The results of SPADE algorithm is frequent sequences which are used to form the rules. Those can be used as predictors of other items that will be purchased by consumers in the future. The result of this study is a lot of unique sequence appears that can provide the best advice for Merchandiser Officer, for example, there are 1.468 sequences that prove the customer who bought the product in Childrenâs Book category will always bought the same thing in the others day. This research produce some recommendation, one of the recommendation is Childrens Book category has a very high chance of being a Best Seller for a long time so that the purchasing officer on XYZ bookstore should ensure that the products supply of the category is always safe throughout the year. It means SPADE is successfully used to provide the advice and Merchandiser Officer must ensure the stock of that product is always available to avoid Lost Sales.

Increasing Smoke Classifier Accuracy using NaÃƒÂ¯ve Bayes Method on Internet of Things Putrada, Alieja Muhammad; Abdurohman, Maman; Putrada, Aji Gautama
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 4, No 1, February 2019
Publisher : Universitas Muhammadiyah Malang

This paper proposes fire alarm system by implementing NaÃƒÂ¯ve Bayes Method for increasing smoke classifier accuracy on Internet of Things (IoT) environment. Fire disasters in the building of houses are a serious threat to the occupants of the house that have a hazard to the safety factor as well as causing material and non-material damages. In an effort to prevent the occurrence of fire disaster, fire alarm system that can serve as an early warning system are required. In this paper, fire alarm system that implementing NaÃƒÂ¯ve Bayes classification has been impelemented. NaÃƒÂ¯ve Bayes classification method is chosen because it has the modeling and good accuracy results in data training set. The system works by using sensor data that is processed and analyzed by applying NaÃƒÂ¯ve Bayes classification to generate prediction value of fire threat level along with smoke source. The smoke source was divided into five types of smoke intended for the classification process. Some experiments have been done for concept proving. The results show the use of NaÃƒÂ¯ve Bayes classification method on classification process has an accuracy rate range of 88% to 91%. This result could be acceptable for classification accuracy.

Feature Selection on Pregnancy Risk Classification Using C5.0 Method Azhar, Yufis; Afdian, Riz
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 4, November 2018
Publisher : Universitas Muhammadiyah Malang

The maternal mortality rate in Indonesia is still relatively high. This is caused by several factors, including the ignorance of pregnant women about the risk status of pregnancy. Several methods are proposed for early detection of the risk of a mothers pregnancy. However, no one has highlighted what features are most influential in the process of classifying the risk of pregnancy. In this research, we use data of pregnant women in one of the health centers in Malang, Indonesia, as a dataset. The dataset has 107 features, therefore, feature selection is needed for the classification process. We propose to use the C5.0 method to select important features while classifying dataset into low, high, and very high risk of pregnancy. C5.0 was chosen because this method has a better pruning algorithm and requires relatively smaller memory compared to C4.5. Another classification method (SVM, Naive Bayes, and Nearest Neighbor) is then used to compare the accuracy values between datasets that use all features with datasets that only use the selected features. The test results show that feature selection can increase accuracy by up to 5%.

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