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IJITEE (International Journal of Information Technology and Electrical Engineering)

ijitee
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Published by Universitas Gadjah Mada

ISSN : - EISSN : 25500554 DOI : https://doi.org/10.22146/ijitee.48545

Core Subject : Engineering,

Electrical & Electronics Engineering

IJITEE (International Journal of Information Technology and Electrical Engineering), with registered number ISSN 2550-0554 (Online), is a peer-reviewed journal published four times a year (March, June, September, December) by Department of Electrical engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada. IJITEE (International Journal of Information Technology and Electrical Engineering) invites manuscripts in the various topics include, but not limited to, Information Technology, Power Systems, Digital Signal Processing, Communication Systems

Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro

Articles 93 Documents

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Product Recommendation System Design Using Cosine Similarity and Content-based Filtering Methods Cut Fiarni; Herastia Maharani
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 2 (2019): June 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

The wide variety of products offered by a company, combined with the consistent demands of specific products from customers, create a certain problem for the organization when they want to market a new product. Organization need information that could help them promote the most suitable product based on their customer’s characteristics. The organization also need to suggest alternative products for customer if the requested product is unavailable. In this research, we design a Recommender System that could suggest either new or alternatif products to customer based on their characteristic and transaction history. This proposed system adopts Cosine Similarity method to calculate product similarity score and Content-based Filtering to calculate customer recommendation score and used as a model for the proposed system. Subsequently, these models are used to classify customers as well as products according to their transaction behavior and consequently recommends new products more likely to be purchased by them. Based on the testing results of the proposed system, it can be concluded that the chosen methods can be utilized to recommend products and costumer of products. It is shown that Precision and Recall of product similarity scores and customer recommendation for product scores are 100% and 93.47%.

Relational into Non-Relational Database Migration with Multiple-Nested Schema Methods on Academic Data Teguh Bharata Adji; Dwi Retno Puspita Sari; Noor Akhmad Setiawan
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 1 (2019): March 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

The rapid development of internet technology has increased the need of data storage and processing technology application. One application is to manage academic data records at educational institutions. Along with massive growth of information, decrement in the traditional database performance is inevitable. Hence, there are many companies choose to migrate to NoSQL, a technology that is able to overcome the traditional database shortcomings. However, the existing SQL to NoSQL migration tools have not been able to represent SQL data relations in NoSQL without limiting query performance. In this paper, a relational database transformation system transforming MySQL into non-relational database MongoDB was developed, using the Multiple Nested Schema method for academic databases. The development began with a transformation scheme design. The transformation scheme was then implemented in the migration process, using PDI/Kettle. The testing was carried out on three aspects, namely query response time, data integrity, and storage requirements. The test results showed that the developed system successfully represented the relationship of SQL data in NoSQL, provided complex query performance 13.32 times faster in the migration database, basic query performance involving SQL transaction tables 28.6 times faster on migration results, and basic performance Queries without involving SQL transaction tables were 3.91 times faster in the migration source. This shows that the theory of the Multiple Nested Schema method, aiming to overcome the poor performance of queries involving many JOIN operations, is proved. In addition, the system is also proven to be able to maintain data integrity in all tested queries. The space performance test results indicated that the migrated database transformed using the Multiple Nested Schema method showed a storage requirement of 10.53 times larger than the migration source database. This is due to the large amount of data redundancy resulting from the transformation process. However, at present, storage performance is not a top priority in data processing technology, so large storage requirements are a consequence of obtaining efficient query performance, which is still considered as the first priority in data processing technology.

Ontology-Based Social Media Talks Topic Classification (Twitter Case) Fransisca Julia Kusuma Deviyanti; Sri Suning Kusumawardani; Paulus Insap Santosa
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 1 (2019): March 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

In the era of digital communication, the use of Twitter as a customer service has been widely encountered. Companies have started to develop strategies around effective use of Twitter, one of which was to identify problems that customers frequently complain about. Twitter, with its straightforward tweet characteristics, will certainly contain sentences with very specific and easily recognizable keywords. These characteristics can be used as a basis for classifying tweets into certain topics. With a help of ontology, classification with keywords can be done automatically. The purpose of this paper is to design an ontology used as a basis for classifying tweets into certain topics related to the 4G telecommunications network in Indonesia and to evaluate performance of proposed classifier model.

DC Motor Speed Control Using Hybrid PID-Fuzzy with ITAE Polynomial Initiation Hari Wibawa; Oyas Wahyunggoro; Adha Imam Cahyadi
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 1 (2019): March 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

DC motors are widely applied in industrial sector, especiallyprocesses of automation and robotics. Given its role in the sector, DC motor operation needs to be optimized. One of optimization steps is controlling speed using several control methods, for example conventional PID methods, PID Ziegler Nichols, PID based on ITAE polynomials, and Hybrid PID-Fuzzy. From these methods, Hybrid PID-Fuzzy was chosen as a method to be proposed in this paper because it can anticipate shortcomings of PID controllers and fuzzy controllers so as to produce system responses that are fast and adaptive to errors. This paper aimed to design a Hybrid PID-Fuzzy system based on ITAE polynomials (Hybrid-ITAE), to analyze its performance parameters values, and tp compare Hybrid-ITAE performance with conventional PID method. Working parameters being reviewed include overshoot, rise time, settling time, and ITAE. First of all, JGA25-370 DC motor was modeled in a form of a third order transfer function equation. Based on the transfer function, PID parameters were calculated using PID Output Feedback and ITAE polynomial methods. The best ITAE polynomial PID controllers were then be combined with a Fuzzy Logic Controller to form a Hybrid-ITAE system. Simulation and experimental stages were carried out in two conditions, namely no load and loaded. Simulation and experimental results showed that Hybrid-ITAE (l = 0.85) was the best controller for no-load simulation conditions. For loaded simulation Hybrid-ITAE (l=1) was a better controller. In no-loads experiment, the best controller was Hybrid PID-Ziegler Nichols, while for loaded condition the best controller was Hybrid PID-Ziegler Nichols.

Page Load Time Speed Increase on Disease Outbreak Investigation Information System Website Rahmat Oktrifianto; Dani Adhipta; Warsun Najib
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 2, No 4 (2018): December 2018
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Outbreaks or extraordinary events often become an issue that occurs in Indonesia. Therefore, an outbreak investigation information system is required to collect, manage and analyze data quickly and accurately. On the other hand, challenges in data accessing processes in certain locations are still constrained by a slow internet connection. This paper conducted speed increase of a page load or site speed time from disease outbreaks investigation information system website.Page load time speed testing was carried out using Google Chrome Developer Tools and using simulation speeds of 2.5 Mbps. Testing time was carried out by dividing the time into three sections, morning hours, working hours and night hours. Implementation of page load time increase includes reducing HTTP requests, utilizing GZIP compression, performing code minification, setting browser chache, using CDN, and using other enhancement techniques.The results showed that after implementing an increase in page load time by turning off cache and using cache, there was an increase in site speed. When the browser cache was turned off, an average page load time increased of 54.79% from the previous time. Whereas when using the browser cache, page load time speed increased by 55.28% from the previous time.

Prototype of Student Attendance Application Based on Face Recognition Using Eigenface Algorithm Tio Eko Prabowo; Rudy Hartanto; Sunu Wibirama
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 1 (2019): March 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Prototype of face recognition based attendance application that has been developed to overcome weaknesses in DTETI UGM student manual attendance system has several weaknesses. These weaknesses are a decrease in facial recognition accuracy when operating under conditions of varying environmental light intensity and in condition of face rotating towards z axis rotation centre. In addition, application prototype also does not yet have a database to store attendance results. In this paper, a new application prototype has been developed using Eigenface face detection and recognition algorithm and Haar-based Cascade Classifier. Meanwhile, to overcome prototype performance weaknesses of the previously developed application, a pre-processing method was proposed in another study was added. Processes in the method were geometry transformation, histogram levelling separately, image smoothing using bilateral filtering, and elliptical masking. The test results showed that in the category of various environmental light intensity conditions, face recognition accuracy from developed application prototypes was 16.71% better than previous application prototypes. Meanwhile, in category of face slope conditions at z axis rotation centre, face recognition accuracy from developed application prototype was 38.47% better. Attendance database system was also successfully implemented and running without error.

Remote Sensing Technology for Land Farm Mapping Based on NDMI, NDVI, and LST Feature Ahmad Fauzi Mabrur; Noor Akhmad Setiawan; Igi Ardiyanto
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 3 (2019): September 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Remote Sensing is a reliable and efficient data acquisition techniques. This technique is widely used for land image processing. This technique has many advantages, especially in terms of cost and time. In this study, the classification between dry and irrigated land from irrigation canals is presented. Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), and Land Surface Temperature (LST) values obtained from satellite imagery data are used in this process. It is expected that through this method, the distribution and control of irrigation water can optimize existing agricultural potential. Ground Check (GC) is used for validation process. The results showed that the error rate based on the moon was not so large, i.e., 18%. The highest errors occur in February and March. This happens because those months are the rainy season, so the measured temperature is mostly the temperature above the cloud layer. On the other hand, the lowest error occurs in November. Also, it can be seen that this method can function optimally when detecting residential areas or highways.

Deep Learning Methods for EEG Signals Classification of Motor Imagery in BCI Muhammad Fawaz Saputra; Noor Akhmad Setiawan; Igi Ardiyanto
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 3 (2019): September 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

EEG signals are obtained from an EEG device after recording the user's brain signals. EEG signals can be generated by the user after performing motor movements or imagery tasks. Motor Imagery (MI) is the task of imagining motor movements that resemble the original motor movements. Brain Computer Interface (BCI) bridges interactions between users and applications in performing tasks. Brain Computer Interface (BCI) Competition IV 2a was used in this study. A fully automated correction method of EOG artifacts in EEG recordings was applied in order to remove artifacts and Common Spatial Pattern (CSP) to get features that can distinguish motor imagery tasks. In this study, a comparative studies between two deep learning methods was explored, namely Deep Belief Network (DBN) and Long Short Term Memory (LSTM). Usability of both deep learning methods was evaluated using the BCI Competition IV-2a dataset. The experimental results of these two deep learning methods show average accuracy of 50.35% for DBN and 49.65% for LSTM.

Autocorrelation Method for Cyclic Prefix OFDM Estimation Desti Madya Saputri
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 3 (2019): September 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

A radio system design providing various data service needs becomes one of the Software Defined Radio (SDR) system advantages. SDR technology applies software functions further to be run in hardware platforms. The need for services with greater data rates can be resolved by using multi-carrier transmission techniques, one of which is the Orthogonal Frequency Division Multiplexing (OFDM) technique. This paper discusses the detection of OFDM signals and their parameters. Multi-carrier transmission can prevent Inter-Symbol Interference (ISI) occurrence due to multi-path fading effect. The recognition can classify the correctly received signals, including the signal conditions mixed with AWGN noise. The autocorrelation method was used to estimate the OFDM parameters, namely the one symbol duration and the cyclic prefix duration. The detected cyclic prefix durations were 1/2, 1/4, 1/8, and 1/16. This method is very simple, because with the cyclic prefix presence, a different signal peak will be detected to further estimate the cyclic prefix duration. The results show the correlation method performance can detect one symbol duration with 100%, accuracy, starting at SNR 0 dB, whereas the cyclic prefix duration accuracy rate is getting more accurate by using a less cyclic prefix duration, which is 1/16 of the total symbol duration.

Designing a Smart Mirror as a Laboratory Information Media Using Raspberry Pi Denny Hardiyanto; Galang Wicaksono; Anggoro S Pramudyo; Rian Fahrizal; Romi Wiryadinata
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 3 (2019): September 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Development of microprocessor technology provides new ideas for creating smart devices, one of which is in the field of smart home. Smart home is a concept of a home integrated with a smart system and supported by technology that enables all work to be more effective and efficient. Mirror is a household device that is beneficial to humans. In this paper, a research on smart mirrors is explained. A smart mirror is a mirror integrated with an intelligent system so that it can display multimedia data originating from the internet using Raspberry as a computing tool, PIR sensor as a tool to control monitors, and DC fans as a tool to control temperature system. In this paper, the mirror was able to display information about time, weather, academic calendar, lab work schedules, prayer schedules, and academic news. A PIR sensor has a good accuracy when the device is placed at 180 cm above the ground and the distance between mirror and humans when mirroring is 70 cm. A DC fan was utilized to stabilize the system temperature in a range of 40 to 50 oC.

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Risanuri Hidayat

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ijitee.ft@ugm.ac.id

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+62274 552305

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https://jurnal.ugm.ac.id/ijitee/about/contact

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Kab. sleman,

Daerah istimewa yogyakarta

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Risanuri Hidayat

Contact Email ijitee.ft@ugm.ac.id

Phone +62274 552305

Journal Mail Official ijitee.ft@ugm.ac.id

Editorial Address https://jurnal.ugm.ac.id/ijitee/about/contact

Location Kab. sleman, Daerah istimewa yogyakarta INDONESIA

Abstract

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Abstract

Contact Name
Risanuri Hidayat

Contact Email
ijitee.ft@ugm.ac.id

Phone
+62274 552305

Journal Mail Official
ijitee.ft@ugm.ac.id

Editorial Address
https://jurnal.ugm.ac.id/ijitee/about/contact

Location
Kab. sleman,

Daerah istimewa yogyakarta

INDONESIA