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All Journal ELINVO (Electronics, Informatics, and Vocational Education)
Puspitasari, Desy Ika
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Computer Science & IT Education Electrical & Electronics Engineering

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Sistem Informasi Geografi (SIG) Pencarian Lokasi Tambal Ban dengan Pemanfaatan Teknologi GPS Puspitasari, Desy Ika; Zaenuddin, Zaenuddin; Yuridka, Fitrah
Elinvo (Electronics, Informatics, and Vocational Education) Vol 4, No 1 (2019): May 2019
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (41.443 KB) | DOI: 10.21831/elinvo.v4i1.23146

Abstract

The occurrence of a tire leak in the middle of a trip can often be caused by many things, such as being hit by a sharp object, the age of the tire is too old, leaking in the former patches, or it can be caused by others. These factors make vehicle users panic and think to immediately find the nearest tire repair location. Almost everyone has a smartphone where there is a Google Map application by utilizing GPS technology so as not to get lost when driving, with GPS technology can be estimated the distance between one location and another. The purpose of this study is to produce a GIS mobile application that provides a tire patch location search feature with information, so that it is expected to be useful for vehicle users if they experience a tire accident or erupt on the road. The workshop information that is presented is the opening / closing time of the workshop, there are nitrogen added facilities or not, tubeless tire patches, can repair motorcycle tire patches or can also tire the car and the contact of the workshop owner, so you can directly contact the nearest tire patch. The results of testing the user's response to the use of the application indicate that the application is useful.
PENERAPAN DATA MINING MENGGUNAKAN PERBANDINGAN ALGORITMA GREEDY DENGAN ALGORITMA GENETIKA PADA PREDIKSI RENTET WAKTU HARGA CRUDE PALM OIL Puspitasari, Desy Ika
Elinvo (Electronics, Informatics, and Vocational Education) Vol 2, No 1 (2017): May 2017
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (560.501 KB) | DOI: 10.21831/elinvo.v2i1.13033

Abstract

Penelitian ini menerapkan data mining pada prediksi harga CPO (Crude Palm Oil) dengan membandingkan pemodelan optimasi seleksi fitur algoritma genetika dan algoritma greedy pada metode neural network (NN). Prediksi harga CPO dilakukan untuk memenuhi kebutuhan investor kelapa sawit, melalui analisa masalah fluktuasi harga CPO time series yang tidak pasti. Guna mempermudah dalam melakukan perhitungan, langkah-langkah dari algoritma Genetika dan algoritma Greedy diimplementasikan dengan program komputer Rapid Miner Studio. Adapun tujuan penelitian ini yaitu mengetahui perbandingan akurasi dengan parameter evaluasi RMSE yang dihasilkan dan waktu eksekusi program yang dibutuhkan oleh algoritma Genetika dan algoritma Greedy dalam menyelesaikan masalah prediksi harga CPO. Hasil pengujian akurasi menunjukkan bahwa penggunaan metode NN optimasi algoritma Genetika secara umum memberikan nilai RMSE yang lebih baik (0,096) dibandingkan algoritma Greedy-forward selection (0,111) dan algoritma Greedy-backward selection (0,101). Akan tetapi jika ditinjau dari waktu eksekusi program yang dibutuhkan dalam menyelesaikan masalah prediksi harga CPO, maka algoritma Genetika membutuhkan waktu yang lebih lama dari pada algoritma Greedy.Kata Kunci: algoritma Genetika, algoritma Greedy, neural network, prediksi harga CPO, time series.
Co-Authors Yuridka, Fitrah Zaenuddin Zaenuddin, Zaenuddin