Background: Human face is a biometric feature. Artificial Intelligence (AI) called Artificial Neural Network (ANN) can be used in recognising such a biometric feature. In ANN, the learning process is divided into two: supervised and unsupervised learning. In supervised learning, a common method used is Backpropagation, while in the unsupervised learning, a common one is Kohonen Self Organizing Map (KSOM). However, the application of Backpropagation and KSOM need to be adjusted to improve the performance.Objective: In this study, Backpropagation and KSOM algorithms are rewritten to suit face image recognition, applied and compared to determine the effectiveness of each algorithm in solving face image recognition.Methods: In this study, the methods used and compared in the case of face image recognition are Backpropagation dan Kohonen Self Organizing Map (KSOM) Artificial Neural Network (ANN).Results: The smallest False Acceptance Rate (FAR) value of Backpropagation is 28%, and KSOM is 36%, out of 50 unregistered face images tested. While the smallest False Rejection Rate (FRR) value of Backpropagation is 22%, and KSOM is 30%, out of 50 registered face images. The fastest time for the training process using the backpropagation method is 7.14 seconds, and the fastest time for recognition is 0.71 seconds. While the fastest time for the training process using the KSOM method is 5.35 seconds, and the fastest time for recognition is 0.50 seconds.Conclusion: Backpropagation method is better in recognising face images than KSOM method, but the training process and the recognition process by KSOM method are faster than Backpropagation method due to the hidden layers. Keywords: Artificial Neural Network (ANN), Backpropagation, Kohonen Self Organizing Map (KSOM), Supervised learning, Unsupervised learning

Juanda International Airport is the third busiest airport, after Soekarno Hatta International Airport and Ngurah Rai International Airport. Because the number of Airplane, passengers, luggage and cargo at Juanda International Airport is increasing every year, it is important to improve infrastructure facilities and services, and all facilities at Juanda Airport. In this research, it was designed and built a forecasting system for Airplane, passenger, luggage and cargo. This research is expected to be a consideration in increasing the readiness of infrastructure and services, and all facilities at Juanda Airport. In addition, this system is also expected to be one of the decision supporting system for the management. This system uses one of the Artificial Intelligent methods, Backpropagation Artificial Neural Network. It is known in previous research that Backpropagation is a method of artificial neural networks with the best performance in pattern recognition, or forecasting. The forecasting system has two main processes, the training process and the forecasting process.

Citra wajah merupakan salah satu fitur biometrik yang dapat dijadikan sebagai bukti autentik dari seseorang. Sistem pengenalan wajah (Face Recognition) secara komputerisasi, akan mengetahui identitas diri seseorang. Dalam proses pelatihan citra wajah, penggunaan piksel dari citra wajah secara langsung dapat mengakibatkan banyaknya fitur-fitur wajah yang tidak dapat terekstraksi dengan baik. Maka dari itu diperlukan suatu pemrosesan awal yang dapat mengekstraksi fitur-fitur wajah dengan baik. Dimana pada penelitian ini digunakan Discrete Cosine Transform (DCT) sebagai pemrosesan awal dan Penggunaan Jaringan Syaraf Tiruan Self Organizing Map (SOM)/Kohonen dalam proses pelatihannya. Dengan menggunakan DCT jaringan akan cepat belajar dan dapat mengenali citra dengan kesalahan yang minimum sehingga didapatkan sistem yang dapat bekerja cukup baik dan efisien.

ABSTRAK Routing merupakan proses mengirim data dari satu network ke network lain. Dengan dynamic routing maka mekanisme routing dilakukan secara dinamis dengan menentukan jarak terpendek secara cepat dan akurat antara peralatan pengirim dan penerima. Open Shortest Path First (OSPF) merupakan salah satu protokol dynamic routing yang menggunakan algoritma link-state untuk membangun dan menghitung jalur terpendek ke semua tujuan yang diketahui. OSPF mendistribusikan informasi routing antara router-router autonomous system (AS). OSPF memiliki titik berat pada kinerja processor, kebutuhan memori dan konsumsi bandwidth. Oleh karena itu perlu mengoptimalkan kinerja protokol routing OSPF terutama masalah pengaruh bandwith dengan menentukan model dan area jaringan routing OSPF. Kata kunci : routing, rynamic routing, OSPF ABSTRACT Data sending processes from one to the other networks is called to be Routing. Using the dynamic routing, the routing mechanism is dynamically done by swiftly and accurately determining the shortest route between sender and receiver. One of the dynamic routing protocols is the Open shortest path first (OSPF) using link-state algorithm to build and count the shortest route to the all known destination. OSPF distributes routing information between system autonomous routers (AS). The focus of OSPF is in the processor activity, memory needs and bandwidth consumption.  There are needs to optimize OSPF routing protocol activity by determining OSPF routing network area and model especially to the bandwidth influence. Key words: routing, dynamic routing, OSPF

On Time Performance (OTP) merupakan ukuran kinerja dalam memberikan layanan secara tepat waktu. Dalam penerbangan, OTP merupakan hal terpenting yang sangat mempengaruhi kualitas layanan transportasi. Namun informasi ini jarang disampaikan secara real time kepada calon penumpang sehingga manfaat informasi tersebut kurang maksimal bagi para pengguna jasa transportasi udara. Penelitian ini bertujuan membuat desain sistem informasi OTP dengan studi kasus Bandar Udara Internasional Juanda sebagai bandar udara tersibuk ketiga di Indonesia. Desain sistem informasi OTP dibuat dalam bentuk purwarupa website sehingga dapat diakses secara mudah, up to date, lebih detail, dan real time. Dalam perancangan dan pembangunan sistem informasi OTP ini, penulis menggunakan metodeprototype. Alur proses dari metode ini yaitu analisis kebutuhan, perancangan sistem, pengujian sistem, launching sistem, dan evaluasi sistem. Data OTP penerbangan diambil dari PT Angkasa Pura 1 Bandar Udara Juanda Surabaya untuk diolah dan ditampilkan di sistem OTP. Pada evaluasi sistem, dilakukan penilaian kinerja purwarupa sistem informasi OTP ini dengan kerangka kerja PIECES. Hasil dari penelitian ini menunjukkan bahwa desain sistem informasi OTP sudah cukup baik. Di masa depan, sistem OTP ini dapat diaplikasikan dalam skala yang lebih luas untuk memberikan informasi yang lebih bermanfaat bagi pengguna jasa penerbangan.