Judul: Pemodelan Jaringan Syaraf Tiruan untuk Memprediksi Awal Musim Hujan Berdasarkan Suhu Muka Laut
Abstrak: Anjatan-Indramayu is the one of agriculture regions in Indonesia. The success or failure of the harvest each year depends on water availability in the region. Therefore we need an accurate method to predict the beginning of rainy season. The method used to predict in this research is artificial neural network (ANN) backpropagation. Result of ANN prediction accuracy is measured by R2 and RMSE. This research uses ECHAM4p5_CA sea surface temperature (SST) is one of the sea surface temperature models with the months of June, July and August. The domain of SST is selected based on the correlation of 5% and 10% for each of the month June, July, and August. This research uses ANN architecture with two parameters: neuron hidden (NH) and learning rate (LR). The number of hidden neurons used in this research are 5, 10, 20, and 40, and the learning rates are 0.3, 0.1, and 0.01. The best prediction result correlation of 5% using the ANN is for June with R2 is 51% and RMSE 3.03 at NH 10 and LR 0.01, July with R2 is 48% and RMSE 3.39 at NH 20 and LR 0.1, and August with R2 is 75% and RMSE 2.51 at NH 40 and LR 0.01. The best prediction result correlation of 10% using the ANN is for June with R2 is 44% and RMSE 3.32 at NH 5 and LR 0.3, July with R2 is 42% and RMSE 3.42 at NH 10 and LR 0.1, and August with R2 is 71% and RMSE 3.37 at NH 20 and LR 0.01. The conclusion from this research is the neuron hidden and learning rate with different values affect R2 and RMSE.
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Judul: Prediksi Awal Musim Hujan di Wilayah Waingapu Menggunakan Jaringan Syaraf Tiruan Backpropagation
Abstrak: Curah hujan merupakan faktor utama dari iklim. Kondisi iklim yang tidak menentu dapat menjadi penyebab kegagalan dalam bertani. Hal ini, membuat para petani sulit dalam memprediksi waktu yang pas untuk bercocok tanam. Oleh karena itu, diperlukan berbagai informasi hasil prediksi iklim sehingga lebih bermanfaat dalam bidang pertanian. Salah satunya adalah dengan memprediksi awal musim hujan (AMH) untuk menekan risiko gagal panen. Penelitian ini bertujuan menentukan awal musim hujan berdasarkan data curah hujan harian di wilayah Waingapu berdasarkan teori Liebmann, menentukan korelasi dalam penentuan prediktor JST antara awal musim hujan dengan peubah indeks iklim global, dan menerapkan metode jaringan syaraf tiruan (JST) untuk memprediksi awal musim hujan. Data indeks iklim global yang digunakan adalah data Southern Oscillation Index (SOI) dan SST Nino 3. Hasil perhitungan menggunakan teori Liebmann AMH terjadi antara bulan September sampai Desember. Prediktor yang digunakan adalah bulan Juli, Agustus dari data SOI dan bulan Juli, Agustus dari data SST Nino 3.4. Hasil penelitian prediksi ini memperoleh model terbaik dengan nilai 𝑅������2 sebesar 0.69 dan nilai RMSE sebesar 25.39.
Keyword: awal musim hujan, jaringan syaraf tiruan, SOI, SST Nino 3.4

Judul: In Vitro Release of Ibuprofen from Microcapsules Coated Polyblend of Poly(lactic acid) and Poly(ε-caprolactone)
Abstrak: Ibuprofen is an anti-inflammatory drug that has a short biological half-life and imposes adverse gastrointestinal reaction. Microencapsulation could be used to minimize its disadvantages. In this experiment, microencapsulation of ibuprofen was done by emulsification method. Coating material which was used were polyblend of poly(lactic acid) and poly(ε-caprolactone) which are biodegradable and biocompatible. Polyvinylalcohol was used as an emulsifier at concentrations of 1.5%. The microencapsulation was carried out with various quantities of ibuprofen. The increase in quantities of ibuprofen would improve encapsulation efficiency. Encapsulation of ibuprofen showed an efficiency of more than 71% with the highest score of 84.13% in microcapsule with ratio of polyblend-ibuprofen 5:1.5. The dissolution test results in basic medium showed that the encapsulation efficiencies affected ibuprofen release from the microcapsule. Microcapsules with the higest encapsulation efficiency released ibuprofen ranged from 26.71 to 28.78% for 6 hours. Kinetic of ibuprofen release followed first order kinetic model. The microcapsules particle sizes ranged from 38 to 250 μm.
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