Judul: Analysis the Effect of Large Red Chili Prices and Green Cayenne Pepper Prices in Indonesia Using Vector Autoregressive Model
Abstrak: Berdasarkan Pusat Informasi Harga Pangan Strategis, cabai merupakan salah satu dari sepuluh komoditas yang memiliki kontribusi signifikan dalam pembentukan angka inflasi pada sektor bahan makanan di Indonesia. Oleh karena itu, cabai dapat dikatakan komoditas penting bagi perekonomian Indonesia. Harga komoditas cabai sering mengalami lonjakan harga dan fluktuatif. Oleh karena itu, analisis terhadap harga cabai dibutuhkan untuk membantu pengambilan kebijakan stabilisasi harga. Variabel pada penelitian ini adalah harga cabai merah besar dan harga cabai rawit hijau yang termasuk sebagai komoditas pangan strategis. Perkembangan harga cabai merah besar dan harga rawit hijau selama beberapa tahun membentuk data time series. Model Vector Autoregressive (VAR) adalah model peramalan data deret waktu multivariat. Model tersebut tidak hanya bergantung pada lag dari peubah itu sendiri tetapi juga dipengaruhi oleh lag peubah lainnya. Keunggulan Model Vector Autoregressive (VAR) adalah tidak perlu menentukan variabel bebas dan variabel terikat. Hasil penelitian menunjukkan model terbaik untuk menggambarkan harga cabai merah besar dan harga cabai rawit hijau adalah VAR(8). Nilai MAPE untuk harga cabai merah besar sebesar 8,59% dengan R^2 sebesar 80,00% dan untuk harga cabai rawit hijau sebesar 7.05% dengan R^2 sebesar 83,33%. Berdasarkan uji kausalitas Granger cabai merah besar dan cabai rawit hijau memiliki hubungan dua arah., According to the Information Center for Strategic Food Prices, chili is one of ten commodities that have a significant contribution to the inflation rate in the food sector in Indonesia. Therefore, chili can be said to be an important commodity for the Indonesian economy. Chili commodity prices often spike and fluctuate. Therefore, an analysis of chili prices is needed to assist price stabilization policymaking. The variables in this study are the prices of large red chilies and the prices of green cayenne peppers, which were included as strategic food commodities. The price of large red chili and the prices of green cayenne pepper over several years form a time series. The Vector Autoregressive (VAR) model is a multivariate time series data forecasting model. The model does not only depend on the lag of the variable itself but is also affected by the lag of other variables. The advantage of the Vector Autoregressive Model (VAR) is that there is no need to determine dependent and independent variables. The results showed that the best model to describe the price of large red chilies and green cayenne peppers was VAR(8). The MAPE value for the price of large red chili is 8.59% with R^2 of 80.00% and for the price of green cayenne pepper is 7.05% with R^2 of 83.33%. Based on the Granger causality test, the price of large red chilies and the price of green cayenne pepper have a two-way relationship.
Keyword: VAR, uji kausalitas Granger, Granger causality test

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: Penyusunan Overlap Graph menggunakan Suffix Tree pada DNA Sequence
Abstrak: The DNA sequence assembly is very important in genome analysis. This step aims to reconstruct contigous DNA fragment (contigs) from short fragment by concatenating fragments based on the overlap region among them. This method employs overlap graph for solving the problems. In this graph, nodes represent fragments and edges represent overlap. This research developed a software for constructing overlap graph using suffix tree. The evaluation was conducted by measuring the number of nodes, number of edges, and the execution time in many values of minimum overlap. The minimum overlap is defined as the minimum length of substring which is considered as the overlap region between two fragments. The evaluation results showed that the number of nodes, the number of edges, and the execution time were increased with the decreasing of the minimum overlap value.
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