JITCE (Journal of Information Technology and Computer Engineering) 2021-07-12T22:29:17-04:00 Editor JITCE Open Journal Systems <p><strong>JITCE (Journal of Information Technology and Computer Engineering)</strong>&nbsp;is a scholarly periodical. JITCE will publish research papers, technical papers, conceptual papers, and case study reports. This journal is published by<a href=""> Computer System Department</a> at&nbsp;<a href="" target="_blank" rel="noopener">Universitas Andalas</a>, Padang, West Sumatra, Indonesia.</p> <p>One volume of JITCE consisted of two editions, which are published in March and September each year. Articles are written in Bahasa Indonesia (Indonesian language) OR English. Abstracts&nbsp;<strong>must be in English</strong>.</p> A Cardiotocographic Classification using Feature Selection: A comparative Study 2021-07-12T22:29:14-04:00 Septian Eko Prasetyo Pulung Hendro Prastyo Shindy Arti <p>Cardiotocography is a series of inspections to determine the health of the fetus in pregnancy. The inspection process is carried out by recording the baby's heart rate information whether in a healthy condition or contrarily. In addition, uterine contractions are also used to determine the health condition of the fetus. Fetal health is classified into 3 conditions namely normal, suspect, and pathological. This paper was performed to compare a classification algorithm for diagnosing the result of the cardiotocographic inspection. An experimental scheme is performed using feature selection and not using it. CFS Subset Evaluation, Info Gain, and Chi-Square are used to select the best feature which correlated to each other. The data set was obtained from the UCI Machine Learning repository available freely. To find out the performance of the classification algorithm, this study uses an evaluation matrix of precision, Recall, F-Measure, MCC, ROC, PRC, and Accuracy. The results showed that all algorithms can provide fairly good classification. However, the combination of the Random Forest algorithm and the Info Gain Feature Selection gives the best results with an accuracy of 93.74%.</p> 2021-03-31T00:00:00-04:00 ##submission.copyrightStatement## Sistem Monitoring Konsumsi Daya Listrik Dengan Mengimplementasikan Bluetooth Low Energy 2021-07-12T22:29:12-04:00 Budi Rahmadya Rahmadya <p>Electricity becomes a major need for human in this era. PLN's electricity payment system in residential areas is divided into two ways, postpaid electricity and prepaid electricity. Prepaid electricity using digital kWh meter that shows the use of current, electric power, etc on LCD. The usage of current and electric power can be monitored using Android application using Bluetooth Low Energy (BLE) as communication media. BLE has many advantages module compared to classic bluetooth, for example having a wider range, data transfer speeds up to 1 Mbps, and low power consumption. Therefore the writer researched by implementing Bluetooth Low Energy in the electric power monitoring system. The results of this research showed that the electric power monitoring system and the BLE module could send the result of sensor measurement to android applications. From the testing that has been done showed that the BLE send module can be up to 25 meters distance for unhindered conditions and 8 meters with hindered conditions. And the BLE module energy consumption is more efficient than HC-05 energy comparison BLE module 5,728 mW and the HC-05 module 13.47 mW.</p> <p>&nbsp;</p> 2021-03-31T00:00:00-04:00 ##submission.copyrightStatement## Prediksi Energi Listrik Kincir Angin Berdasarkan Data Kecepatan Angin Menggunakan LSTM 2021-07-12T22:29:17-04:00 Muhammad Qubaisy Andiyantama QUBAISYA@GMAIL.COM Iffah Zahira Ade Irawan <p>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.</p> 2021-03-31T00:00:00-04:00 ##submission.copyrightStatement## Implementasi Forward Chaining dan Certainty Factor pada Aplikasi Konsultasi Kecantikan 2021-07-12T22:29:16-04:00 Bunga Ratna Sari Sabar Rudiarto <p>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%.</p> 2021-03-31T00:00:00-04:00 ##submission.copyrightStatement## Sistem Monitoring Perilaku Pengendara Mobil Berbasis Internet of Things 2021-07-12T22:29:15-04:00 Andri Ulus Rahayu <p class="Abstract" style="text-align: justify;"><span lang="EN-US">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 &amp; 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.</span></p> 2021-03-31T00:00:00-04:00 ##submission.copyrightStatement##