Penelitian ini merupakan lanjutan dari penelitian sebelumnya tentang peramalan EUR/USD menggunakan metode RBF-NN (Radial Basis Function – Neural Network) yang diop­timasi dengan Algoritma Genetika. Metode yang ditambahkan adalah GRNN (Generalized Regression Neural Network). Sistem RBF-NN dapat diterapkan pada data dengan karakteristik nonlinear dan fluktuatif seperti data EUR/USD, sementara GRNN dapat bekerja dengan baik jika data training tersedia dalam jumlah banyak. Tingkat keakuratan dari peramalan di­tun­jukkan lewat nilai MAPE (Mean Absolut Percentage Error). Dari hasil percobaan, metode GRNN tidak memiliki nilai MAPE yang lebih baik daripada RBF-NN baik pada data daily low maupun data daily high. Teknik pencarian algorima genetika di dekat bobot RBF-NN terbukti lebih efektif daripada pen­dekatan fungsi GRNN dengan spread kecil pada kasus mata uang EUR/USD.

This research is about constructing a prototype of fire detection warning system on Apron Passenger Bus. The prototype can detect certain possibility of fire and give early warning to the driver. It works automatically based on three sensors used, which are smoke sensor, temperature sensor and flame sensor. The prototype is constructed using these three sensors and combined with Arduino microcontroller. This microcontroller has a role of transmitting information to the alarm system as a fire indicator. Method used in this research begins with simulation of a fire warning system and continued by implementation on hardware. The prototype works successfully on detecting fire both on software and hardware basis.

This article provides the results of an in-depth investigation on how the vocational education institution, Service College, under the supervision of the Transportation Ministry carries out the graduates' roles optimally and to realize the well-prepared graduates for work. This research describes vocational education to answer the high demands. The researchers applied the qualitative method with descriptive statistical data analysis. The researchers expected to reveal the portrayal of vocational service college educational governance in the Transportation Ministry. This research answers two questions: the actual conditions of current vocational education and strategies to improve the vocational education quality, especially to keep up with the 4.0 industrial revolution development and technological advancement. The researchers found some improvable elements, such as vocational lecturers' competencies, collaboration, and synergy, vocational education revitalization with teaching factories, re-branding by directly getting involved in industries, benchmarking to the better and advanced education institution, curriculum adjustment, procurement of special institution to improve the career levels and lecturer ranks, and output quality based on budget instead of Tri Dharma achievement.