Judul: Price Volatility of Large Red Chili and Its Effect on
Inflation in DKI Jakarta and West Java
Abstrak: Tingginya permintaan dengan ketersediaan pasokan tidak berbanding lurus mengingat produksi cabai merah besar masih belum merata dan hanya difokuskan pada daerah tertentu yang menjadi sentra. Kondisi tersebut mendorong timbulnya karakteristik baru dari komoditas cabai merah besar yakni terjadinya volatilitas harga yang berpotensi mengakibatkan inflasi komponen bergejolak. Perbedaan tingkat produksi antara daerah sentra dan non sentra mengindikasikan adanya perbedaan pengaruh cabai merah besar terhadap nilai inflasi secara spasial. Metode analisis deskriptif dan kuantitatif yang digunakan pada penelitian ini terdiri dari analisis deskriptif untuk melihat disparitas harga, Coefficient of Variation untuk melihat fluktuasi harga, model ARCH/GARCH untuk menganalisis volatilitas harga, serta Error Correction Model untuk menganalisis pengaruh volatilitas harga cabai merah besar terhadap nilai inflasi di DKI Jakarta dan Jawa Barat. Hasil penelitian menunjukkan bahwa terjadi disparitas harga cabai merah besar di antara kedua provinsi tersebut dan harga cabai merah besar di DKI Jakarta lebih volatil dibandingkan dengan Jawa Barat. Volatilitas harga cabai merah besar berpengaruh signifikan terhadap nilai inflasi di DKI Jakarta pada jangka panjang dan pendek. Harga cabai keriting dan harga cabai rawit hijau berpengaruh signifikan terhadap nilai inflasi di Jawa Barat pada jangka pendek. Sementara itu, harga cabai keriting berpengaruh signifikan terhadap nilai inflasi di Jawa Barat pada jangka panjang., The high demand with the availability of supply is not directly proportional considering the production of large red chili is still uneven and only focused on certain areas that become centers. This condition encourages the emergence of new characteristics of chili commodities, such as price volatility, which has the potential to cause volatile component inflation. The differences in production levels between central and non-central areas indicate differences in the effects of large red chili on the inflation rate spatially. Descriptive and quantitative analysis methods used in this study consist of descriptive analysis to see price disparities, Coefficient of Variation to see price fluctuations, ARCH/GARCH models to analyze price volatility, and Error Correction Model to analyze the effect of large red chili price volatility on inflation rates in DKI Jakarta and West Java. The results show that there is a disparity in the price of red chili between the two provinces and the price of large red chili in DKI Jakarta is more volatile than West Java. Large red chili price volatility has a significant effect on the value of inflation in DKI Jakarta in the long and short term. The price of curly chili and the price of green cayenne pepper have a significant effect on the value of inflation in West Java in the short term. Meanwhile, the price of curly chili has a significant effect on the value of inflation in West Java in the long term.
Keyword: Inflasi, cabai merah besar, volatilitas harga, Inflation, large red chili, price volatility

Judul: Analyze Volatility of Large Chilli and Cayenne  Pepper in Indonesia
Abstrak: Komoditas cabai di pasar Indonesia dikenal dalam berbagai jenis di antaranya cabai besar yang terdiri atas cabai merah besar dan cabai keriting serta cabai rawit yang terdiri atas cabai rawit hijau dan cabai rawit merah. Permintaan cabai besar dan cabai rawit memiliki sifat tidak elastis sehingga harganya cenderung volatile. Pola harga yang volatile menyebabkan komoditas cabai termasuk ke dalam kelompok volatile food. Penelitian ini ditujukan untuk mengetahui perbedaan baik pada pola harga cabai besar dan cabai rawit dan volatilitas pada kedua harga cabai tersebut. Metode yang digunakan adalah model ARIMA dan ARCH-GARCH. Hasil penelitian menunjukkan volatilitas yang terjadi pada kedua komoditas tersebut cenderung rendah dan harga cabai rawit memiliki volatilitas yang lebih tinggi dengan koefisien ARCH 0.833003 dibandingkan harga cabai besar yang memiliki koefisien ARCH 0.479061. Harga cabai besar dan cabai rawit memiliki volatilitas yang tinggi yaitu pada periode November sampai dengan Februari. Tingginya volatilitas disebabkan oleh cuaca yang ekstrem sehingga produksi cabai menurun sedangkan permintaan meningkat., The chili commodity in Indonesian market is known in various types, including large chilies consisting of red chilies and curly chilies and cayenne pepper consisting of green cayenne pepper and red cayenne pepper. The demand for large chilies and cayenne pepper is inelastic, so the price tends to be volatile. The volatile price pattern causes the chili commodity to be included in the volatile food category. This study is to determine the differences in both the price patterns of large chili and cayenne pepper and the volatility of the two chili prices. The method that used are ARIMA and ARCH-GARCH models. The results showed that the volatility that occurred in these two commodities tended to be low and the price of cayenne pepper had higher volatility with an ARCH coefficient of 0.833003 compared to the price of large chili which had an ARCH coefficient of 0.479061. The prices of large chilies and cayenne pepper are highly volatile on the November to February. The high volatility was caused by extreme weather so that chili production decreased while demand increased.
Keyword: ARCH-GARCH, ARIMA, Volatility, Cayenne Pepper, Large Chili

Judul: Graphology Analysis Based on Letter a and t Using Perceptron.
Abstrak: Graphology or handwriting analysis is a method of identifying, analyzing, evaluating, and understanding personality through the strokes and patterns revealed by handwriting. A person who can analyze handwriting is called a graphologist. A graphologists can be subjective in their assesments different graphologist can have different analysis of the same handwriting. Therefore, a computer technology may help to minimize the subjectivity. This research used perceptron to analyze personality based on handwriting. Perceptron is one method of neural network. This research analyze two letters to letter a and t image. Letter a are represented by 135 images, consisting of 81 images as training data and 54 images as testing data. There are 150 images used for t images, consisting of 90 images as training data and 60 images as testing data.There are 5 experiments consisting of 2 experiments for letter a and 3 experiments for letter t. The result is the character of each class letter a and t where each parameters there are 3 classes. The accuracy of letter t and letter a was 55% and 88.89% respectively.
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