Prediksi Penerimaan Zakat menggunakan Metode Support Vector Regression (SVR) dengan Flower Pollination Algorithm (FPA) - Tusiarti Handayani; Imam Cholissodin; Agus Wahyu Widodo (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2017)
Payment and distribution of zakat in Indonesia managed by Badan Amil Zakat, which of one is Lembaga Amil Zakat Infaq and Shadaqah Muhammadiyah (LAZISMU) Malang. Fluctuations in the level of zakat fund received by LAZISMU Malang affect in the amount of zakat fund that can be distributed to communities in the all of Malang region. Zakat reception forecasting is so needed to determined the amount of zakat received, so that solution anticipation when the fund is less than the distribution target can be done as early as possible. Prediction are made on this research is using Support Vector Regression (SVR) with Flower Pollination Algorithm (FPA) method. SVR used to make prediction of zakat received based on historical data zakat received, and then FPA used to make optimization value from parameter to be used on SVR method. Data used as many as 64 historical data from Juli 2011 up to Oktober 2016 data received of zakat for the one of Lembaga Amil Zakat Nasional at Malang region that is LAZISMU Malang. The results of tests performed on the prediction zakat using SVR with FPA on zakat revenue data from 2011 to 2016 resulted value of 0.2497 in the fitness and 3.0048 in the MAPE which means average difference between of actual data and predict result is Rp144.741.