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PREDIKSI KEPADATAN KENDARAAN BERMOTOR BERDASARKAN TINGKAT KEBISINGAN LALU LINTAS DENGAN MENGGUNAKAN LOGIKA FUZZY

Jurnal Informatika

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Title PREDIKSI KEPADATAN KENDARAAN BERMOTOR BERDASARKAN TINGKAT KEBISINGAN LALU LINTAS DENGAN MENGGUNAKAN LOGIKA FUZZY
 
Creator Lim, Resmana; Faculty of Industrial Technology, Petra Christian University
Thiang, Thiang; Faculty of Industrial Technology, Petra Christian University
Kuntjoro, Jusak Agus; Alumnus, Faculty of Industrial Technology, Petra Christian University
 
Subject noise based vehicle flow prediction, noise prediction, fuzzy logic prediction system.
 
Description The paper describes a fuzzy logic based system to predict the number of vehicle flow based on its noise. The system equipped by a sensor using a microphone an a 8088 microprocessor. The prediction results are displayed on 7-segment display. The fuzzy inference system used a strategy of MIN-MAX with 3 inputs which are: noise level, the width of road & a correction factor. A Defuzzification method of COG (Center of Gravity) is depployed in the system to produce prediction result in number of vehicle per minnute. The experimental results are presented to figure out the performance of the prediction comparing to the actual number of vehicle. The result shows that the prediction error of the system is about 7-10% comparing to the prediction by using human ear resulting the error of 4-5%.


Abstract in Bahasa Indonesia :

Paper ini menyajikan pengembangan sebuah sistem prediksi jumlah kendaraan bermotor yang lewat pada suatu jalan berdasarkan tingkat kebisingan lalu lintas dengan menggunakan logika fuzzy. Alat yang dibuat menggunakan sistem mikroprosesor 8088 yang dilengkapi dengan sensor bising berupa mikropon. Hasil prediksi jumlah kendaraan ditampilkan pada display 7-segment led. Sistem inferensia fuzzy yang dipakai di sini menggunakan strategi MIN-MAX dengan tiga crisp input yaitu: level kebisingan, lebar jalan di mana alat ini dipakai dan faktor koreksi. Sedangkan metode defuzifikasi menggunakan COG (Center of Gravity) untuk menghasilkan crisp output berupa prediksi jumlah kendaraan per menit. Pengujian sistem dilakukan dengan 2 cara yaitu membandingkan hasil prediksi alat dengan jumlah kendaraan sebenarnya, dan ke dua adalah membandingkan hasil prediksi dengan hasil perhitungan berdasarkan pendengaran telinga manusia dengan mata tertutup. Hasil percobaan menujukan kesalahan prediksi pada percobaan pertama adalah 7-10% sedangkan kesalahan prediksi alat bila dibandingkan hasil perhitungan telinga manusia adalah sekitar 4-5%.

Kata kunci: prediksi jumlah kendaraan berdasarkan kebisingan, sistem prediksi fuzzy logic.
 
Publisher Institute of Research and Community Outreach - Petra Christian University
 
Date 2004-06-21
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier http://jurnalinformatika.petra.ac.id/index.php/inf/article/view/15817
10.9744/informatika.3.2.pp. 53-58
 
Source Jurnal Informatika; Vol 3, No 2 (2002): NOVEMBER 2002; pp. 53-58
 
Language eng
 
Relation http://jurnalinformatika.petra.ac.id/index.php/inf/article/view/15817/15809
 
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