Calculation of the weight of an animal is very important because in the body of an animal there are many things that can be utilized, one of which is cattle. Therefore, beef cattle weigh the cattle in order to estimate the weight of the beef using a conventional method. However, this use is considered inefficient because the number of scales is very limited and it is not easy to carry around. Therefore, for the process of estimating the body weight of the cattle, it is very important for livestock owners to know the body weight of the cattle. Information System for Estimating Beef Weight Based on Android is designed on Android operating system with minimum API 22 (Lollipop) and target API 26 or 27 (Oreo). For testing the application will be carried out on Asus Zenfone 2 with the Marshmallow version of the Android operating system (API 23). In this case the method used is the Indonesian Winter Formula, namely by measuring the chest circumference and body length. Based on the test results on the design of information systems for estimating the weight of beef based on Android, it can be identified and can be concluded as follows; based on the results of testing and measurements on 5 (five) cows showing an accuracy value of up to 98.75%, and the results of measuring the body weight of the cow depend on the calculation of the length and chest circumference of the cow where the process will greatly affect the calculation results.

The Asian-Australian monsoon circulation specifically causes the Indonesian region to go through climate changebility that impacts on rainfall variability in different Indonesia's zone. Local climate conditions such as rainfall data are commonly simulated using General Circulation Model (GCM). This study tries to model the statistical downscaling of GCM in the form of 7x7 matrix using Support Vector Regression (SVR) for rainfall forecasting during drought in Bireuen Regency, Aceh. The output yields optimal result using certain parameter i.e. C = 0.5, γ = 0.8, d = 1, and ↋= 0.01. The duration of computation during training and testing are ± 45 seconds for linear kernels and ± 2 minutes for polynomials. The correlation degree and RMSE values of GCM and the actually observed data at Gandapura wheather station are 0.672 and 21.106. The RSME value obtained in that region is the lowest compared to the Juli station which is equal to 31,428. However, the Juli station has the highest correlation value that is 0.677. On the other hand, the polynomial kernel has a correlation degree and RMSE value equal to 0.577 and 29,895 respectively. To summary, the best GCM using SVR kernel is the one at Gandapura weather station in consideration of having the lowest RMSE value with a high correlation degree. PENDAHULUANPengaruh fenomena regional seperti sirkulasi monsun Asia-Australia merupakan daerah pertemuan angin antar tropis yang merupakan daerah pertumbuhan awan, serta terjadi perubahan suhu permukaan laut di sekitar wilayah Indonesia [1] [2]. Berbagai fenomena tersebut secara spesifik menyebabkan wilayah Indonesia terjadinya keragaman iklim, pengaruh dari faktor keragaman iklim tersebut dapat dijadikan sebagai indikator dalam kaitannya terhadap tanaman adalah curah hujan bagi sektor pertanian khususnya padi di Provinsi Aceh.Pada tahun 2018 sebanyak 451 hektar sawah di Provnsi Aceh yang berisi tanaman padi dilanda kekeringan, delapan hektar diantaranya termasuk kategori berat, 39 hektar termasuk kategori sedang, dan 403 hektar termasuk kategori ringan, dengan fenomena seperti ini bahkan satu hektar diantaranya sudah puso atau gagal panen. Daerah yang kerap sekali terjadinya kekeringan yaitu Aceh Besar 179 hektar, Gayo Lues 12 hektar dan sementara ini daerah paling luas terkena bencana kekeringan yaitu Kabupaten Bireuen seluas 260 hektar, Fenomena kekeringan tersebut dapat mempengaruhi penurunan hasil produksi tanaman pangan khususnya padi di Kabupaten Bireuen Provinsi Aceh [3].Dari berbagai macam data model time series dapat digunakan untuk menduga curah hujan dimusim kemarau, salah satunya adalah luaran General Circulation Model (GCM) sebagai variabel peubah bebas dan dapat digunakan untuk menghasilkan kondisi iklim lokal seperti curah hujan dan temperatur [4]. GCM merupakan model yang dirancang untuk mensimulasikan time series tertentu dari variabel iklim secara global

Global climate phenomena, including El-Nino and Southern Oscillation, Indian Ocean Dipole and Madden Julian Oscillation, have affected rainfall behavior in Indonesia. This study attempts to model a statistical downscaling of the General Circulation Model (GCM), which is usually used as learning data for the prediction of climate change, using Support Vector Regression (SVR) to predict rainfall during the dry season in Bireuen, Aceh Province. Data consists of observational rainfall data at 7 (seven) weather stations and 10 models of 7x7grid-scale hindcasts of GCM data collected within 24 years (1990-2013). The RBF kernel was found to produce the best performance (correlation value: 0.828; RMSE: 24.035) compared to the linear (correlation value: 0.538; RMSE: 27.207) and polynomial kernel (correlation value: 0.639; RMSE: 25.584). Among GCM downscaling output, CMC1-CanCM3 was considered to be the best model for rainfall prediction in Bireun District, particularly in Peudada and Gandapura regions. This model is recommended to be used as a rainfall forecasting tool during drought and would help in optimizing the arrangement of cropping strategy in Bireun area to prevent possible crop failure.

Program Bantuan Keluarga Miskin (PBKM) adalah program pemerintah dalam mengentaskan kemiskin dalam bentuk bantuan dan pemberdayaan masyarakat miskin. Proses pemilihan warga dalam penerima PBKM dari pihak Desa Karang Anyar Kecamatan Darul Makmur Kabupaten Nagan Raya Provinsi Aceh selama ini masih menggunakan cara konvensional, sehingga cara tersebut setelah diamati sering terjadi permasalahan yaitu kriteria-kriteria warga yang disurvei tidak sesuai dengan ketentuan yang diharapkan. Berdasarkan permasalahan tersebut maka diperlukan Perancangan Sistem Pengambilan Keputusan Untuk Menentukan Penerima Program Bantuan Keluarga Miskin (PBKM) Menggunakan Metode AHP (Analitical Hierarchy Process). Metode perancangan perangkat lunak yang digunakan dalam penelitian ini yaitu metode waterfall dengan bahasa pemrograman PHP dan database MySQL. Kriteria yang digunakan berupa ekonomi keluarga, jumlah keluarga, pekerjaan kepala keluarga dan beban daya listrik. Hasil penelitian diperoleh bahwa aplikasi yang telah dibangun dapat memberikan kemudahan bagi pihak pemerintahan Desa dalam menentukan penerima bantuan dengan cara cepat, sistematis, terstruktur dan terarah serta dapat memudahkan kinerja petugas dalam menghasilkan laporan keputusan penerima bantuan keluarga miskin pada kantor Desa Karang Anyar Kecamatan Darul Makmur Kabupaten Nagan Raya.

Dayah Istiqamatuddin Raudhatul Mu'arrif is a traditional Islamic school/ dayah salafi located at Hamlet Alue Seuneuhi, Gampong Neuheun, Grand Mosque districts, Aceh Besar. Administrative process and management of students and educators data of the Islamic school of Istiqamatuddin Raudhatul Mu'arrif still use the manual method by relying on the master book. The use of computers for dayah administration is still not maximized, depending only on Microsoft Word and Microsoft Excel applications. Therefore, when the data is needed cannot be obtained in a fast time. The system was built to help recap student and teacher data more efficiently to minimize errors in report generation. It is designed and built using the Laravel framework so that the structure of the codes becomes neater and safer from external attacks. In addition, the MySQL query language is used for database access and management. The results obtained are an information system application that can display the complete profile of Dayah Istiqamatuddin Raudhatul Mu'arrif and monitor the administration management. Furthermore, it can be printed and downloaded by the administrative manager