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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Journal of Information System KOMPUTIKA - Jurnal Sistem Komputer Indonesian Community Service and Empowerment Journal (IComSE) Jurnal Pengabdian Pelitabangsa
Sri Nurhayati
Sistem Komputer, Fakultas Teknik Dan Ilmu Komputer, Universitas Komputer Indonesia
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Journal : Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)

 1 
Application of the Machine Learning Method for Predicting International Tourists in West Java Indonesia Using the Averege-Based Fuzzy Time Series Model Sri Nurhayati; Syahrul Syahrul; Riani Lubis; Mochamad Fajar Wicaksono
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 1 (2023): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i1.25475

Abstract

The purpose of this study is to propose whether an average-based fuzzy time series model is appropriate for use in predicting the number of foreign tourists coming to West Java, Indonesia. Machine learning is a branch of artificial intelligence where machines are designed to learn on their own without human direction. One of the machine learning methods used by data science is for prediction processes, such as predicting the number of tourists. Tourism is one of the economic sectors that has a direct impact on the community's economy. Based on data from the Badan Pusat Statistik (BPS), the number of tourists coming to West Java Indonesia fluctuates, meaning that the number can increase and decrease every month and year. Changes in the number of tourists that fluctuate are one of the problems that have an impact on tourism actors. Therefore, the solution given to answer this problem is that an appropriate model is needed to predict the number of tourists visiting West Java. The contribution of this research is to help related parties in predicting the number of foreign tourists so that it can be used as one to make policies related to tourism preparation and planning efforts in West Java, Indonesia.  The method used in this research is a case study approach, where the case study is taken from data on foreign tourists visiting West Java from 2017 to 2020. For the prediction process, the method used is the fuzzy time series method and the average length-based algorithm as the determinant of the interval length. Effective interval length can affect prediction results with a higher level of accuracy. Based on the prediction test results, the Mean Absolute Percentage Error (MAPE) value is 14.71%. These results indicate that the fuzzy time series model based on the average interval length is good for prediction.
Interactive Solar System Learning Media Using the Raspberry Pi 3B Mochamad Fajar Wicaksono; Myrna Dwi Rahmatya; Syahrul Syahrul; Sri Nurhayati
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.25948

Abstract

The current learning solar system process uses solar system props. This research aimed to create an interactive solar system learning tool for elementary school students. With this tool, students can learn about the planets in the solar system in learning mode. In addition, there is a question mode to test students' knowledge abilities. This research's contribution was to provide an engaging way for sixth-grade elementary school students to learn about and recognize the planets in the solar system. The method used in this research is the experimental method. The primary part of this system is the Raspberry Pi. In this tool, there are two modes: learning mode and question mode. The learning mode involves the input button for eclipse mode and the LDR sensor as a trigger for activating the DC motor and reading solar system material using gTTS. The question mode involves a question bank on the web application, gTTS for reading questions, and speech recognition for processing answers given by students.   The teacher can add, change, or delete questions and learning materials through the web application. The test on the learning tool is 100% successful. In learning mode, the device can read input from the LDR sensor and provide sound output, and in question mode, the device will ask questions, receive answers in voice form and then process the response based on program scenarios. On the other side, Based on UAT results from 20 sixth-grade elementary school student,  95.14% of student agreed that solar system learning media and quiz features make the learning process more engaging, easy to use, help students understand solar system material, and can be used as a learning tool.
Co-Authors Hani Irmayanti Hidayat, Hidayat Iman Immanudin Mochamad Fajar Wicaksono Myrna Dwi Rahmatya R H Nugraha Riani Lubis Syahrul Syahrul Wicaksono, Mochamad Fajar