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"In recent years, crisis of oil and global competition have become big problems for industries. Rising of oil prices in global market may affect Pertamina as an Indonesian oil industry to escalate gasoline price for transportation. However, psychologically increment of gasoline price causes customer requesting more attractive and effective service quality at gas station. For improving service performance, customer needs and customer satisfaction is necessary to be identified by conducting a survey. This survey which will describe customer needs of gas station will be analyzed using Multivariate Analysis and importance Performance Analysis. Importance Performance Diagram as a result of Importance Performance Analysis displays the service attributes and service performance that required to be improved to fulfill customer needs. Afterwards, House of Quality as the basis of Quality Function Deployment is designed to verify that prominence customer needs have been prioritized and managed accurately. In this study, the 'House ofQuality' is based on company strategy and ability. This study is hopefully able to help Pertamina to enhance its service performance and achieve its customer satisfaction."

"The subject of multivariate splines has become a rapidly growing field of mathematical research. The author presents the subject from an elementary point of view that parallels the theory and development of univariate spline analysis. To compensate for the missing proofs and details, an extensive bibliography has been included. There is a presentation of open problems with an emphasis on the theory and applications to computer-aided design, data analysis, and surface fitting. Applied mathematicians and engineers working in the areas of curve fitting, finite element methods, computer-aided geometric design, signal processing, mathematical modelling, computer-aided design, computer-aided manufacturing, and circuits and systems will find this monograph essential to their research."

"Dalam penelitian ini dilakukan simulasi pengendalian temperatur dan level air (multivariable) pada proses pencampuran dalam suatu tangki berkapasitas 80 liter menggunakan MATLAB Simulink. Tujuan dari penelitian ini adalah menjaga temperatur dan level air di set point pada sebuah proses dengan mengendalikan debit air dingin dan panas yang masuk ke tangki pencampuran. Keterkaitan antara satu variabel dengan variabel lainnya dapat direduksi menggunakan decoupling. Sistem akan diuji dengan banyak perubahan set point dan diberikan input gangguan berupa ketidakakuratan temperature transmitter dalam membaca temperatur air campuran. Pengujian sistem dilakukan menggunakan pengendali PI dan ANFIS. Pengendali PI digunakan sebagai data training ANFIS. Pada penelitian ini diberikan batasan bahwa debit maksimal yang digunakan adalah 15 l/min, temperatur maksimum pada tangki campuran adalah 90℃, dan level air maksimum tangki adalah 75 cm. Performa dari kedua pengendali akan dibandingkan dengan melihat parameter-parameter seperti RMSE, rise time, settling time, dan %Overshoot sebagai data kualitatif. Penelitian ini menunjukkan bahwa pengendali ANFIS secara keseluruhan lebih baik daripada pengendali PI dalam pengujian perubahan set point yang dapat dilihat dari nilai RMSE ANFIS untuk kendali temperatur berada di angka rata-rata 0.174 dan level pada angka 0.196. RMSE pengendali PI untuk kendali temperatur adalah 0.21 dan level 0.2. Pemberian input gangguan menunjukkan pengendali ANFIS lebih baik daripada pengendali PI dalam menangani adanya kesalahan pembacaan sensor oleh temperature transmitter.

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In this research, a simulation program for temperature and level control on a liquid (water) mixing process with assumed to have a tank volume 80 liter is proposed using MATLAB Simulink. The purpose of this study is to maintain the temperature and water level at the set point in a process by controlling the flowrate of cold and hot water that enters the mixing tank. The influence of one variable with others can be reduced using decoupling technique. The system will be tested with many set point changes and given input an inaccurate transmitter temperature in reading the temperature of the mixed water. System testing is performed using a PI and ANFIS Controller. PI Controller is used to generate the ANFIS training data. In this research, a limit is given that the maximum discharge used is 15 liters/min, the maximum temperature and level in the mixed tank is 90℃ and 75 cm. The performance of those two controllers will be compared by observing parameters such as RMSE, rise time, settling time, and %Overshoot as qualitative data. This research shows that ANFIS controllers are generally better than PI controllers when tested with set point changes which can be seen from the ANFIS RMSE values ​​for temperature control at an average rate of 0.174 and a level of 0.196. The RMSE of the PI controller for temperature control is 0.21 and level 0.2. Tests with disturbance input show that ANFIS controllers are better at handling inaccurate transmitter temperature in reading the temperature of the mixed water than PI Controller."