Journal of Information Technology and Computer Engineering
Journal of Information Technology and Computer Engineering (JITCE) is a scholarly periodical. JITCE will publish research papers, technical papers, conceptual papers, and case study reports. This journal is organized by Computer System Department at Universitas Andalas, Padang, West Sumatra, Indonesia.
Articles
186 Documents
<![CDATA[Otomatisasi Pengoperasian Alat Elektronik Berdasarkan Hasil Prediksi Algoritma Long Short Term Memory ]]>
<![CDATA[Afriansyah, Afriansyah]]>;
<![CDATA[Irawan, Ade]]>
<![CDATA[ JITCE (Journal of Information Technology and Computer Engineering) Vol. 4 No. 02 (2020) ]]>
Publisher : <![CDATA[Universitas Andalas ]]>
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DOI: 10.25077/jitce.4.02.83-89.2020
<![CDATA[Excessive use of household electricity is one of the causes of the largest amount of national electricity consumption coming from households. One way to reduce the amount of household electricity consumption is to automate the operation of electronic devices. This research proposes utilizing Long Short Term Memory (LSTM) algorithm to predict the habit of operating an electronic device. The prediction is then applied to automate the operation of that by exploiting the time series data from the usage. A series of experiments are conducted to capture the data of operating a manual lamp. Then, an LSTM model is built by training the data. The experiment results show the prediction accuracy of 99,28% and Root Mean Square Error of 0,091. Furthermore, the LSTM model is used to automatically operate a lamp in a month. The electricity cost from the automation is 36,38% lower than the manual.]]>
<![CDATA[Predicting Survival of Heart Failure Patients Using Classification Algorithms ]]>
<![CDATA[Oladimeji, Oladosu Oyebisi]]>;
<![CDATA[Oladimeji, Olayanju]]>
<![CDATA[ JITCE (Journal of Information Technology and Computer Engineering) Vol. 4 No. 02 (2020) ]]>
Publisher : <![CDATA[Universitas Andalas ]]>
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DOI: 10.25077/jitce.4.02.90-94.2020
<![CDATA[Heart failure is a situation that occurs when the heart is unable to pump enough blood to meet the needs of other organs in the body. It is responsible for the annual death of approximately 17 million people worldwide. Series of studies have been done to predict heart failure survival with promising results. Hence, the purpose of this study is to increase the accuracy of previous works on predicting heart failure survival by selecting significant predictive features in order of their ranking and dealing with class imbalance in the classification dataset. In this study, we propose an integrated method using machine learning. The proposed method shows promising results as it performs better than previous works and this study confirms that dealing with imbalanced dataset properly increases accuracy of a model. The model was evaluated based on metrics such as F-measure, Precision-Recall curve and Receiver Operating Characteristic Area Under Curve. This discovery has the potential to impact on clinical practice, when health workers aim at predicting if a patient will survive heart failure. Attention may be focused on mainly serum creatinine, ejection fraction, smoking status and age.]]>
<![CDATA[Rancang Bangun Sistem Reservasi Ruangan Menggunakan Near Field Communication (NFC) Berbasis Mikrokontroller ]]>
<![CDATA[Fadhil, Rahmad]]>;
<![CDATA[Hersyah, Mohammad Hafiz]]>
<![CDATA[ JITCE (Journal of Information Technology and Computer Engineering) Vol. 4 No. 02 (2020) ]]>
Publisher : <![CDATA[Universitas Andalas ]]>
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DOI: 10.25077/jitce.4.02.95-104.2020
<![CDATA[Current technological developments also help in the ordering system. Simplifying the reservation system with information technology is one of the innovations made to help users of the room more easily in booking a room. The system designed consists of hardware and software connected to book a room based on, UID, usage time and to open the door of the room. Hardware includes Arduino Mega, NFC tags, NFC readers, relays, solenoids, buzzers, and LEDs. The software includes a Mysql website and database. The system will store user data, date, shift, length of usage and type of room booked by the user. NFC tags will be used by the customer to open the door to the room by getting closer to the NFC reader. This system aims to facilitate the process of borrowing space without having to undergo a convoluted process.]]>
<![CDATA[Optic Cup Segmentation using U-Net Architecture on Retinal Fundus Image ]]>
<![CDATA[Prastyo, Pulung Hendro]]>;
<![CDATA[Sumi, Amin Siddiq]]>;
<![CDATA[Nuraini, Annis]]>
<![CDATA[ JITCE (Journal of Information Technology and Computer Engineering) Vol. 4 No. 02 (2020) ]]>
Publisher : <![CDATA[Universitas Andalas ]]>
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DOI: 10.25077/jitce.4.02.105-109.2020
<![CDATA[Retinal fundus images are used by ophthalmologists to diagnose eye disease, such as glaucoma disease. The diagnosis of glaucoma is done by measuring changes in the cup-to-disc ratio. Segmenting the optic cup helps petrify ophthalmologists calculate the CDR of the retinal fundus image. This study proposed a deep learning approach using U-Net architecture to carry out segmentation task. This proposed method was evaluated on 650 color retinal fundus image. Then, U-Net was configured using 160 epochs, image input size = 128x128, Batch size = 32, optimizer = Adam, and loss function = Binary Cross Entropy. We employed the Dice Coefficient as the evaluator. Besides, the segmentation results were compared to the ground truth images. According to the experimental results, the performance of optic cup segmentation achieved 98.42% for the Dice coefficient and loss of 1,58%. These results implied that our proposed method succeeded in segmenting the optic cup on color retinal fundus images.]]>
<![CDATA[Rekomendasi Strategi Sosialisasi Program Studi Melalui Jalur Undangan Menggunakan Algoritma ID3 dan K-Means ]]>
<![CDATA[Hairudin, Muhammad Azhar]]>;
<![CDATA[Zainuddin, Hazriani]]>;
<![CDATA[Wabula, Yuyun]]>
<![CDATA[ JITCE (Journal of Information Technology and Computer Engineering) Vol. 6 No. 01 (2022) ]]>
Publisher : <![CDATA[Universitas Andalas ]]>
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DOI: 10.25077/jitce.6.01.14-18.2022
<![CDATA[Based on data obtained from SPAN-PTKIN registrants in 2018 and 2019, the number of interested people through the invitation path who chose the study program at UIN Alauddin as the first choice was 30523 records. Analysis using the ID3 algorithm found that those who interested in the study of religions were more dominant from vocational students. While analysis using the K-Means shows the regions / regencies from which those interested in study programs of religions are spread in 35 regencies / cities. It can be concluded that the socialization of study programs of religions through the invitation path is recommended to be more focused on SMAs that are located in 33 districts / cities as identified in cluster 3. The study programs of religions are prioritized, because these study programs experienced the lowest number of registrants. It is expected that by implementing this recommended strategy, the number of interested prospective new students will draw a significant increase in the future.]]>
<![CDATA[Prediksi Energi Listrik Kincir Angin Berdasarkan Data Kecepatan Angin Menggunakan LSTM ]]>
<![CDATA[Andiyantama, Muhammad Qubaisy]]>;
<![CDATA[Zahira, Iffah]]>;
<![CDATA[Irawan, Ade]]>
<![CDATA[ JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 01 (2021) ]]>
Publisher : <![CDATA[Universitas Andalas ]]>
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DOI: 10.25077/jitce.5.01.1-7.2021
<![CDATA[Fossil energy is well known as the most energy resource consumed by humans. However, the exploitation leads to damage both in the process of taking raw materials and in the use of those. Furthermore, the amount has become decreasing nowadays. Renewable energy could solve the energy crisis. One kind of renewable energy that has been successfully used by a human is by utilizing wind turbines. However, there are still many problems in its implementation and usage. One of the problems is the unstable generated electricity that is caused by instability of the wind speed. Inappropriate plans for utilizing wind turbines in such areas with varying wind speed could harm renewable energy investment. Therefore, forecasting the wind speed is necessary to anticipate the stability and embrace optimal produced energy. This study proposes the Long Short Term Memory (LSTM) algorithm to predict the generated energy by using the wind speed dataset. Thus, wind turbines can be utilized effectively and efficiently in the right area with sufficient average wind speed.]]>
<![CDATA[Metode Kernel Distance Classifier Terhadap Klasifikasi Penyakit Jantung ]]>
<![CDATA[Aprianto, Kasiful]]>
<![CDATA[ JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021) ]]>
Publisher : <![CDATA[Universitas Andalas ]]>
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DOI: 10.25077/jitce.5.02.70-74.2021
<![CDATA[This study compares the Support Vector Machine (SVM) and Kernel Distance Classification (KDC) methods to classify heart disease. SVM works by transforming data into higher dimensions using the kernel and classifying data linearly using a hyperplane. Meanwhile, KDC works by finding points that represent each classification from the data that has been transformed into a higher dimension using the kernel, and the new data is predicted based on the closest distance from the point of each classification. The results show that the accuracy produced by SVM is 81.11%. The accuracy produced by the SVM model is better than that produced by the KDC model of 80.47% with a difference of 0.64%, even though both models use kernel transformation.]]>
<![CDATA[Implementasi Forward Chaining dan Certainty Factor pada Aplikasi Konsultasi Kecantikan ]]>
<![CDATA[Sari, Bunga Ratna]]>;
<![CDATA[Rudiarto, Sabar]]>
<![CDATA[ JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 01 (2021) ]]>
Publisher : <![CDATA[Universitas Andalas ]]>
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DOI: 10.25077/jitce.5.01.8-17.2021
<![CDATA[Having skin that is free from problems is a dream for most women, especially in Indonesia. However, the problem is not all women are aware that in carrying out treatment or using a product, it must match the needs of each skin type. The rise of beauty salons that operate but are not under the auspices of specialist doctors and also cheap beauty products that are claimed to solve skin problems in an instant makes women easily tempted. This of course can have a big negative impact when the maintenance procedures performed are not up to standard, and there are dangerous ingredients in the products used. For this reason, consulting with a specialist or the expert is indispensable. Researchers used the forward chaining method and certainty factors in building this system which is expected to be used in determining facial skin problems and their solutions based on case studies at the XYZ beauty clinic. The Forward Chaining method is used to draw conclusions based on the facts entered. While certainty factor is used to calculate the trust value from the existing conclusions. This method requires 2 main values in performing calculations, namely MB (measurement of belief) and MD (measurement of disbelief). Based on the research that has been done, the system was successfully built and gave an accuracy value of 97.35%.]]>
<![CDATA[Sistem Monitoring Perilaku Pengendara Mobil Berbasis Internet of Things ]]>
<![CDATA[Rahayu, Andri Ulus]]>
<![CDATA[ JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 01 (2021) ]]>
Publisher : <![CDATA[Universitas Andalas ]]>
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DOI: 10.25077/jitce.5.01.18-24.2021
<![CDATA[This research is created as a system for a car rental service. The system has monitoring features allowing the car rental owner to monitor the engine condition. The monitoring is performed by using a web interface that could read data from OBD-II that sent by raspberry pi 2. The owner can also monitor the position of the car by using coordinates sent from a smartphone by utilizing the GPS feature. In addition, it also has a reporting feature that allows the owner to track the data history from OBD II about the engine rpm, speed, engine load & temperature. Moreover, the owners can identify the route that has been passed by their car. Likewise, this system provides a program that analyzes the car driver's behavior based on the determined rules. The analysis was conducted based on all data from OBD-II in the database server and all data of driving rules violation performed by the driver. The result is an assessment of the driver as a driving error rate. This study generated 173 data of which 9 were driving rules violations with a 5.20% driving error rate. The report can be obtained by selecting the time interval. It also downloadable and can be sent by e-mail.]]>
<![CDATA[Utilization of AHP-MAUT Method to Determine the Country of Exhibition Abroad in Batik Hatta Boutique ]]>
<![CDATA[Cholil, Saifur Rohman]]>;
<![CDATA[Ardianita, Tria]]>
<![CDATA[ JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021) ]]>
Publisher : <![CDATA[Universitas Andalas ]]>
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DOI: 10.25077/jitce.5.02.52-56.2021
<![CDATA[This research was conducted with the aim of helping decide the destination country for overseas exhibitions at the Batik Hatta Boutique. By knowing all the data and information of a country, boutique owners can decide which country to visit in the batik exhibition. Because if you attend the cast in all countries, there will be overruns in costs. The methods used are AHP and MAUT. The AHP method is used as a weighting using a linguistic value scale. Weights are obtained from the pairwise comparison matrix between two elements of all elements that occur at the same hierarchical level. The MAUT method is used to determine the importance of each alternative for the ranking process. The results of this study indicate that Cambodia was chosen as the location to be visited for the batik exhibition. The results of the validation using the Spearman Rank correlation comparison obtained a value of 0.951 meaning that this method can be used as a decision making.]]>
