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IJITEE (International Journal of Information Technology and Electrical Engineering)
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 5 Documents
 1 
Search results for , issue "Vol 2, No 2 (2018): June 2018" : 5 Documents clear
The Design of Application Architecture of the Institute of Business Based on Enterprise Architecture Planning Muhammad Yusuf Morais; Habibullah Akbar
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 2, No 2 (2018): June 2018
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2394.476 KB) | DOI: 10.22146/ijitee.42149

Abstract

Institute of Business (IOB) is committed to achieve its goals, i.e. becomes a place for economics and business as well as computer science developers, and prepare a ready-to-use Human Resources (HR), especially for Timor Leste. At present, IOB does not have an alignment between business processes and information systems owned. Therefore, this paper proposes an architectural design that bridges the alignment. The methods used to build the framework are include Enterprise Architecture Planning (EAP), SWOT, Value Chain, and Mc Farlan Grid. The built frameworks are focused on the needs of the application architecture. The resulted portfolio has 45 applications for various divisions of IOB. In addition, the SWOT analysis shows that IOB's internal and external factors are in the second quadrant. Thus, IOB's position is relatively strong, though it is facing a big challenge. The recommended strategy is the Strengths-Threats (ST) strategy that uses the company’s strength to overcome the threats. This strategy includes improving facilities, adding faculties and departments, developing academic information systems, improving the quality of learning, and improving the human resources quality.
Study of Undersampling Method: Instance Hardness Threshold with Various Estimators for Hate Speech Classification Naufal Azmi Verdikha; Teguh Bharata Adji; Adhistya Erna Permanasari
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 2, No 2 (2018): June 2018
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (969.833 KB) | DOI: 10.22146/ijitee.42152

Abstract

A text classification system is needed to address the problem of hate speech in social media. However, texts of hate speech are very hard to find in social media. This will make the distribution of training data to be unbalanced (imbalanced data). Classification with imbalanced data will make a poor performance. There are several methods to solve the problem of classification with imbalanced data. One of them is undersampling with Instance Hardness Threshold (IHT) method. IHT method balances the dataset by eliminating data that are frequently misclassified. To find those data, IHT requires an estimator, which is a classifier. This research aims to compare estimators of IHT method to solve imbalanced data problem in hate speech classification using TF-IDF weighting method. This research uses the class ratio of dataset after undersampling, time of the undersampling process, and Index of Balanced Accuracy (IBA) evaluation to determine the best IHT method. The results of this research show that IHT method using the Logistic Regression (IHT(LR)) has the fastest undersampling process (1.91 s), perfectly balance dataset with the class ratio is 1:1, and has the best of IBA evaluation in all estimation process. This result makes IHT(LR) be the best method to solve the imbalanced data problem in hate speech classification.
Gorontalo Medicinal Plants Image Identification System Using Artificial Neural Network with Back Propagation Mukhlisulfatih Latief; Rampi Yusuf
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 2, No 2 (2018): June 2018
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1234.879 KB) | DOI: 10.22146/ijitee.42154

Abstract

The purpose of this research is to design the application of digital image processing system to identify the image of medicinal plants of Gorontalo region using artificial neural network method using back propagation. This research used a digital image processing method with segmentation and extraction techniques. Segmentation process was carried out using thresholding method. Furthermore, a process of characteristic extraction from medicinal plants drawings was carried out using feature and color feature extractions to obtain the value of metric, eccentricity, hue, saturation and value. these five values were used as parameters for input neurons and one output neuron which denoted the class of the medicinal plants image. Data of this research consisted of 91 images which had been divided into two types, training data and test data. The training data consisted of 80 images and the test data consisted of eleven images. A network architecture was obtained from the training result and it provided the highest accuracy level (100%) and least number of iteration with a number of 50 neurons on hidden layer and 143 epochs. The testing result showed a lower accuracy of 54.54%.
Prediction of Peat Forest Fires Using Wavelet and Backpropagation Novera Kristianti; Albertus Joko Santoso; Pranowo Pranowo
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 2, No 2 (2018): June 2018
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1289.705 KB) | DOI: 10.22146/ijitee.42156

Abstract

One of the causes of smog as well as climate damage, particularly in Palangka Raya, Center Kalimantan, are peat forest fires. There are a lot of losses inflicted by the smog including the increasing number of people who suffer respiratory infection (ARI) due to polluted air and any other related aspects. Peat fires are problematic to overcome because the locations of fires are difficult to be accessed. This paper focuses on building the system to predict the distribution of peat forest fire hotspots by utilizing satellite imagery. In designing the system for predicting the fire hotspots distribution, wavelet orthogonal was used as the initial processing of mapping the distribution of peat forest fire hotspots. Meanwhile, backpropagation method was used to identify the fire hotspot distribution patterns of peat forest fire in this system. From the result of the data tested which had been done for predicting the peat forest fire hotspots, the decomposition image obtained using Haar wavelet had the highest percentage of accuracy to recognize the fire hotspots, which is 90%. The recency of this system was its ability to predict the peat forest fire hotspots distribution which can be used as peat forest fires prevention, especially in Palangka Raya, Central Kalimantan.
Role Analysis of Distributed Generation Towards Transmission Expansion Planning Using MILP Gessa Firman Febrian; Sasongko Pramono Hadi; Sarjiya Sarjiya
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 2, No 2 (2018): June 2018
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1110.861 KB) | DOI: 10.22146/ijitee.42551

Abstract

Electricity demand increase as function of population and economic activity growth. To meet the demand growth, one kind of approaches to expand electrical system is to calculate the need of generating unit and the result will be used to determine the needs of transmission line. In this research, a model was developed with focused on transmission line expansion based on Mix Integer Linear Programming method. The objective function was to minimize overall investment cost for transmission and operating cost of all generating units. The developed model was implemented in 6-bus Garver’s test system. Distributed generation implementation impact is also studied in this study in term of network configuration and overall expansion cost. The results show that distributed generation implementation will differ the network configuration and reduce the overall system cost, with overall system cost with and without distributed generation implementation was $106.4 million and $103.18 million respectively.

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