Judul: Fitting Model pada Data Jumlah Mahasiswa Baru Institut Pertanian Bogor Menggunakan Metode Fuzzy Time Series Chen dan Hsu
Abstrak: Forecasting is an activity that is carried out to predict the value of a variable in the future. The purpose of this study is to predict the number of the new students at Bogor Agricultural University using Chen’s fuzzy time series (CFTS) method and the fuzzy time series method which is described by Steven (SFTS) and to compare the two methods by looking at the error rate prediction results using the Mean Absolute percentage Error (MAPE). Fuzzy time series forecasting is a method that uses fuzzy sets as a basis for the prediction process. CFTS method and SFTS method have some differences so that the results also different. The result obtained using the CFTS method is equal to 0.96%, while that of SFTS (2013) is 2.96%. So it can be concluded that CFTS method has a smaller error rate in predicting the number of new students at Bogor Agricultural University.
Keyword: Bogor Agricultural University (IPB), number of new students at Bogor Agricultural University, mean absolute percentage error, fuzzy time series

Judul: Perbandingan Metode Fuzzy Time Series dan Holt Double Exponential Smoothing Pada Peramalan Jumlah Mahasiswa Baru Institut Pertanian Bogor
Abstrak: Forecasting is an activity to predict values of a variable in the future. The purposes of this research is predicting the number of new students at Bogor Agriculture University using fuzzy time series method and Holt double exponential smoothing method. This research is also comparing these two methods to find the more appropriate method based on the accuracy of forecasting showed by Mean Absolute Percentage Error (MAPE). Fuzzy time series methods used fuzzy set in the process of forecasting while Holt double exponential smoothing method smooths the value of serial data by reducing them exponentially. In forecasting the number of new students at Bogor Agricultural University, fuzzy time series method, with MAPE as big as 6.412%, shows better forecasting accuracy than Holt double exponential smoothing method which has MAPE as big as 7.75%. After conducting a case study, we conclude that Holt double exponential smoothing method will be more accurate if there are many data available.
Keyword: fuzzy time series, Holt double exponential smoothing, new students of Bogor Agriculture University.

Judul: Komposit NiCu Layered Double Hydroxide sebagai Elektrokatalis Evolusi Oksigen
Abstrak: Elektrolisis air merupakan salah satu cara terbaik dalam memperoleh sumber energi yang dapat diperbarui. Salah satu reaksi yang berperan dalam elektrolisis air adalah reaksi evolusi oksigen (OER). Langkah dalam OER mencakup transfer 4 elektron sehingga secara energetika dan kinetika membutuhkan energi yang besar dan katalis untuk mempercepat reaksi. Elektrokatalis yang dikembangkan dalam penelitian ini adalah komposit NiCu layered double hydroxide (LDH) menggunakan metode kopresipitasi. Linear sweep voltammetry memberikan informasi terkait kemiringan Tafel (b) melalui plot hubungan overpotensial dan log (j). Berdasarkan ciri difraksi sinar X, NiCu LDH berhasil terbentuk dengan membandingkan sudut 2 dengan literatur. Parameter uji aktivitas katalitik pada elektrokatalis tersebut memberikan nilai kemiringan Tafel terendah (44.5 mV/dec ) dan overpotensial terendah (465.1 mV/cm2 pada j=10 mA/cm2), serta koefisien transfer muatan tertinggi (1.3359) pada nisbah 2:1 dengan medium NaOH 1.0 M.
Keyword: aktivitas elektrokimia, elektrokatalis, kopresipitasi, NiCu LDH, overpotensial