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"Pengaturan waktu sinyal adalah solusi terbaik untuk menghasilkan kinerja aliran lalu-lintas yang optimal berdasarkan ketersediaan Ruang Henti Khusus (RHK) dan pengontrol lampu lalu lintas menjadi sangat penting. Tujuan penelitian ini adalah menganalisis kinerja simpang bersinyal berdasarkan analisis waktu sinyal, volume, derajat kejenuhan rata-rata, antrian, kapasitas, jumlah kendaraan henti, tundaan rata-rata dan optimasi ketersediaan ruang henti khusus (RHK) sepeda motor di setiap fase Jalan Boulevard BSD Tangerang Banten. Penghitungan untuk mendapatkan waktu sinyal dapat dilakukan dengan memanfaatkan pengoptimalan Transyt-RHK yang terkandung dalam program komputer Transyt, dan kinerja yang dihasilkan dengan menggunakan program Transyt-RHK lebih kecil daripada penundaan yang dihasilkan oleh data lapangan. Rata-rata penundaan persimpangan data lapangan adalah 44,95 detik / smp, optimalisasi Transyt 16,27 detik / smp dan optimasi Transyt-RHK 12,98 detik /smp. Kesimpulan penelitian sistem lampu lalu lintas dengan Transyt-RHK lebih efektif dibandingkan dengan sistem lalu lintas konvensional (MKJI). ......Signal timing is the best solution to produce optimal traffic flow performance based on the availability of the Advanced Stop Lines (ASL) and the traffic light controller becomes very important. The purpose of this study was to analyze the performance of signalized intersections based on analysis of signal time, volume, degree of average saturation, queuing, capacity, number of vehicle stops, average delay and optimization of motorcycle ASL in each phase of Jalan Boulevard BSD Tangerang Banten. Calculations to get the signal time can be done by utilizing the Transyt-ASL optimization contained in the Transyt computer program, and the performance produced using the Transyt-ASL program is smaller than the delay generated by field data. The average delay in crossing field data is 44.95 seconds/pcb, optimizing Transyt 16.27 seconds/pcb and optimizing Transyt-ASL 12.98 seconds/pcb. Conclusion research on traffic light systems with Transyt-ASL is more effective than conventional traffic systems (MKJI)."

"The purpose of the study was to investigate hand gesture recognition. The hand gestures of American Sign Language are divided into three categories—namely, fingers gripped, fingers facing upward, and fingers facing sideways—using the adaptive network-based fuzzy inference system. The goal of the classification was to speed up the recognition process, since the process of recognizing the hand gesture takes a longer time. All pictures in all of the categories were recognized using K-nearest neighbor. The procedure involved taking real-time pictures without any gloves or censors. The findings of the study show that the best accuracy was obtained when the epochs score was 10. The proposed approach will result in more effective recognition in a short amount of time."