Judul: Analysis of Inflation using Google Trends Data with ARIMAX model in DKI Jakarta
Abstrak: Inflasi merupakan salah satu indikator ekonomi penting untuk menunjukkan gejala ekonomi tingkat harga daerah. DKI Jakarta merupakan ibu kota negara Indonesia yang dipilih sebagai pusat barometer perekonomian karena dapat memberikan kontribusi dan pengaruh terbesar bagi perekonomian Indonesia. Model ARIMAX digunakan untuk memperkirakan dengan menambahkan variabel independen di data Google Trends. Data Google Trends dieksplorasi berdasarkan tujuh kelompok pengeluaran yang diterbitkan oleh CPI dan data Google Trends digunakan dari Januari 2013 hingga Maret 2019. Tujuan dari penelitian ini adalah untuk membandingkan perkiraan terbaik melalui pendekatan model ARIMA dan ARIMAX dengan menggunakan data BPS dan hasil eksplorasi data Google Trends, data suku bunga, data nilai tukar hingga melihat pengaruh inflasi di DKI Jakarta. Secara spesifik penelitian ini mengupas apakah data Google Trends dapat memberikan informasi yang baik dalam meramalkan inflasi di DKI Jakarta. Hasil analisis data menunjukkan bahwa hasil peramalan mendekati data BPS asli dengan model peramalan terbaik yaitu ARIMAX (2,0,3) semua variabel X. Peramalan dengan menggunakan data Google Trends cukup baik untuk digunakan dalam peramalan inflasi khususnya di DKI Jakarta., Inflation is one of the important economic indicators to show economic symptoms of region’s price level. DKI Jakarta is the capital city of Indonesia which is chosen as the center of the economic barometer because it can provide the largest contribution and influence to the Indonesian economy. ARIMAX model is used to estimate by adding independent variables in Google Trends data. Google Trends data is explored based on seven expenditure groups published by CPI and Google Trends data is used from January 2013 to March 2019. The purpose of this study was to compare the best forecasts through the ARIMA and ARIMAX model approaches by using BPS data and the results of the exploration of Google Trends data, interest rate data, exchange rate data to see the effect of inflation in DKI Jakarta. Specifically, this research explores whether Google Trends data can provide good information in forecasting inflation in DKI Jakarta. The results of data analysis indicate that the forecasting results are close to the original BPS data with the best forecasting model, namely ARIMAX (2,0,3) all X variables. Forecasting using Google trends data is good enough to be used in forecasting inflation, especially in DKI Jakarta.
Keyword: ARIMAX, Google Trends, Inflation, forecasting

Judul: Perbandingan Metode Peramalan Inflasi: Ordinary Least Square (OLS), Exponential Smoothing dan ARIMA
Abstrak: Tujuan dari penelitian ini adalah menganalisis metode terbaik untuk meramalkan tingkat inflasi di Indonesia menggunakan beberapa metode peramalan time series, seperti Ordinary Least Square (OLS), exponential smoothing dan ARIMA. Penelitian ini menggunakan data Indeks Harga Konsumen (IHK) dari bulan Agustus 1983 sampai Desember 2012 untuk menghitung tingkat inflasi, dan diperoleh perhitungan inflasi year on year dari bulan Agustus 1984 sampai Desember 2012. Agustus 1984 sampai Desember 2011 adalah data interval contoh yang digunakan untuk memperoleh hasil peramalan inflasi, sedangkan Januari 2012 sampai Desember 2012 digunakan sebagai data pembanding dengan hasil peramalan inflasi yang telah diperoleh sebelumnya. Berdasarkan hasil uji dari setiap metode dan hasil evaluasi menggunakan Mean Absolute Error (MAE), Mean Square Error (MSE) dan Mean Absolute Percentage Error (MAPE) sebagai perhitungan dari ketepatan prediksi peramalan, diperoleh bahwa metode ARIMA adalah metode terbaik untuk meramal tingkat inflasi karena memiliki nilai MAE, MSE dan MAPE terkecil.
Keyword: Bogor Agricultural University, Institut Pertanian Bogor, IPB, Inflation, Ordinary Least Square, Exponential Smoothing, ARIMA

Judul: Hybrid solar cells of ZnO nanoparticles/chlorophyll was modified metal ions (Zn2+ and Cu2+ )
Abstrak: Zinc Oxide (ZnO) is a n-type semiconductor with a wide the energy band (Band Gap) is 3.37 eV at room temperature and 3.34 eV at low temperature with a large exiton binding energy is 60 meV. ZnO has been synthesized by hydrothermal method, resulting in a decrease in particle size over the duration of the hydrothermal changes. Crystallographic structure of ZnO were characterized using XRD, has shown the characteristic pattern of a hexagonal wurtzite structure, the crystallite size increases to changes in particle size. Changes in particle size has also led to a change in the absorption peak of ZnO as has been demonstrated posted under test using the optical properties of UV-Vis spectrophotometer. Changes of this uptake has also led to changes in the energy band gap, which increases its band gap energy of the particle size. In electronic applications, especially in solar cells. Chlorophyll is considered less effective, because of their very nature are easily degraded as a result of several reactions which are acid, lighting and temperature. The results of the stability test using a halogen lamp 34 W/m2 for 5 hours, that the substitution of chlorophyll with metal ions Zn2+ and Cu2+ has been shown to form more stable than natural chlorophyll. The characterization of the optical properties, the combination of ZnO / chlorophyll in the form of hybrid films has led to a shift in the absorption region of ZnO becomes more widely from the UV to Visible. ZnO/chlorophyll has absorption range of 350-515 nm, ZnO / Zn-feofitin 332-401 nm and 332-632 nm for Cu-feofitin. The combination of ZnO/chlorophyll and CuSCN as a solid electrolite in hybrid solar cell, a modified chlorophyll with metal ions Zn2+ and Cu2+ has been shown to form a more stable I-V curve. It is characterized by its fill factor value greater than natural chlorophyll. Nevertheless, solar cells with natural chlorophyll has been able to produce higher efficiency values of chlorophyll were substituted.
Keyword: Hydrothermal, ZnO/Chlorophyll modified, Hybrid Solar Cell