Judul: Pemetaan Tingkat Serangan Hama Kutu Kebul (Bemisia tabaci) Berbasis Mobile Android
Abstrak: Dalam proses penanganan serangan hama, tahap monitoring merupakan tahap yang cukup penting. Pada tahap ini dilakukan pemantauan tingkat serangan hama kutu kebul. Informasi serangan hama berguna untuk menentukan metode penanganan hama yang efektif dan pendugaan arah penyebaran hama. Implementasi sistem dilakukan pada lingkungan mobile berbasis android. Penggunaan mobile android dimaksudkan untuk mempercepat pengiriman data dari lapangan. Beberapa teknologi yang mendukung penelitian ini antara lain Google Map dan GPS. Metode yang digunakan dalam penelitian ini adalah perancangan sistem, akusisi data, praproses, segmentasi citra, perhitungan nilai serangan hama untuk satu daun, perhitungan nilai serangan hama untuk satu tanaman, perhitungan nilai serangan hama untuk satu area, dan pemetaan tingkat serangan hama. Data citra yang digunakan pada penelitian ini yaitu 25 citra daun tanaman sayuran. Hasil perhitungan untuk lima area yang disimulasikan menghasilkan akurasi 100%. Hal ini menunjukkan bahwa dalam skala yang besar, kesalahan segmentasi pada beberapa daun tidak terlalu mempengaruhi hasil akhir.
Keyword: Bemisia tabaci, Google Map, Plant mapping, Whitefly, Mapping, Akuisisi data, Image segmentation, Tingkat serangan hama, Pemetaan hama, Metode segitiga

Judul: Segmentasi Citra Menggunakan Metode Segitiga untuk Pengukuran Tingkat Kerapatan Hama Kutu Kebul
Abstrak: Whitefly, Bemisia tabaci (Gennadius) (Homoptera: Aleyrodidae), is one of the major important pests of vegetables. Its small size and the insufficient number of pest observers have cause difficulties in monitoring the pests. One solution to overcome this problem is by using digital image processing. With digital image processing techniques, pest density can be measured accurately. In this study, triangle method is used to get the dynamic threshold value to be used in the segmentation process. The Images of vegetable used in this study are 23 images of eggplant leaves. The image will pass through several stages, including preprocessing, image segmentation and density calculations. The result of Image segmentation for 23 images using the triangle method has an accuracy of 75.36%. This suggests that the triangle method can be used for the segmentation process of whitefly pests in vegetable crops leaf image. By using this method, pest density calculation can be done optimally.
Keyword: Bemisia tabaci, triangle method, whitefly

Judul: The Effects of Variance of Interest rate to Variance of Annuity Future Values
Abstrak: Time value of money is a concept that refers to the difference of the value of money due to time difference. The value of money for present time would not be the same as the value of money in the future. The value of money for present time is called as Present Value (PV) of the money and the value of money for future time is called Future Value (FV) of the money. Determination the value of money, for present and future time, depends on the time and rate of return. The value of money is determined by several factors such as inflation, fluctuation of interest rates, and government policy in securities and taxation. Due to fluctuation of the value of money we need a FV formulation, it is useful for knowing whether an investment can be profitable or not, and this information is useful also in budget analysis. Annuity is defined as a series of payments made for a specific period. The payment, fixed or varied, can be made at the beginning or at the end of the period. Annuity paid at the beginning of the period is called annuity-due and annuity paid at the end of the period is called immediate annuity-certain. The accumulated value of the annuity after few years later is called as a final value or a future value. Burnecki et al. (2003) have discussed about the FV of a fixed-rate annuity in which payments are made according to the arithmetic or geometric series. They have also examined FV for annuities in which payments are made according to arithmetic or geometric series with random rates of interest. This paper examines FV for annuity-due in which payments are made according to arithmetic or geometric series with interest rates as a random variable, which is normal distribution ,  . Future value formula is expressed in recursive form. FV for annuity-due which payments are made according to the arithmetic or geometric series with random rates of interest is calculated by theoretical way and simulation way. The random rates of interest is denoted as k k i  i  , where k i an independent random variable; i is a constant and k  is a random variable which has normal distribution ,  . By using the determined parameters, a sequence of random rates of interest are generated for theoretical calculation. Meanwhile for the simulation, the random rates of interest is generated 1000 times for the simulation. The generated data give mean value, variance, and standard deviation. Moreover, error of mean value, variance, and standard deviation from the theoretical and simulation results are calculated. Error calculation uses Symmetric Mean Absolute Percentage Error (SMAPE). The smaller the value of SMAPE is the more accurate the simulation. The interest rate variances are varied from 0.000036 to 0.0001 to study the relationship between variance of rates of interest and variance of future value. The theoretical and simulation results show that when the variance of random rates of interest increases, then the variance of FV increases linearly. FV of the annuity-due in
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