Ketepatan waktu lulus mahasiswa menjadi salah satu indikator penilaian kelayakan program studi sebagai unit pelaksana pendidikan pada perguruan tinggi. Mengetahui faktor yang mempengaruhi waktu lulus mahasiswa akan membantu program studi dan dosen dalam mengambil keputusan untuk meningkatkan kuantitas mahasiswa lulus tepat waktu. Tujuan dari penelitian ini adalah untuk mendapatkan gambaran tentang karakteristik mahasiswa yang mempengaruhi ketepatan waktu lulus mahasiswa program studi S1 Matematika dengan menggunakan metode Ensemble Tree. Metode Ensemble tree yang digunakan adalah Bagging CART, dengan harapan dapat menghasilkan performa klasifikasi yang tinggi dan gambaran kharateristik mahasiswa yang baik. Data yang digunakan adalah data mahasiswa program studi S1 Matematika dari tahun 2010 sampai dengan 2019. Kebaikan klasifikasi dilihat dari nilai Accuracy, Sensitivity dan Specificity. Metode pohon klasifikasi tunggal (CART) memberikan nilai Accuracy sebesar 82.1% , sensitivity sebesar 68.2 % dan specificity sebesar 91.2 %. Sedangkan dengan metode Bagging CART diperoleh Accuracy sebesar 85.7% , sensitivity sebesar 77.3 % dan specificity sebesar 91.2 %. Berdasarkan perbandingan nilai akurasi yang diperoleh dapat disimpulkan bahwa menerapkan metode Bagging pada pohon klasifikasi tunggal CART dapat meningkatkan performa klasifikasi.
Hujan adalahn unsur iklim yang sangat penting karena curah hujan berpengaruh terhadap perubahan iklim dan iklim berpengaruh terhadap banyak sektor seperti pertanian dan perikanan. Hal ini menjadikan permodelan curah hujan sangat penting untuk dikaji. Kota Bengkulu terdiri dari dua musim (Hujan dan Kemarau) dan juga memiliki cuaca yang sangat cepat berubah karena letak geografis Bengkulu yang berbatasan dengan Samudra Hindia yang berakibat jika terjadi tekanan rendah di Samudra Hindia maka Bengkulu akan mengalami hujan yang tinggi. Curah hujan yang terdiri dari dua musin dan terjadi secara berulang, sehingga curah hujan termasuk kedalam pola monsunal yang dicirikan oleh tipe curah hujan yang bersifat unimodial (satu puncak musim hujan). Jika menggunakan data curah hujan masa lalu maka metode yang tepat untuk memodelkan curah hujan adalah metode Seasonal Autoregressive Integrated Moving Average (SARIMA). Tujuan yang ingin dicapai dalam penelitian ini adalah mengetahui model SARIMA yang terbentuk pada data curah hujan mingguan Kota Bengkulu. Hasil yang diperoleh model SARIMA (0,1,1)(0,1,1)12 merupakan model curah hujan bulanan di Kota Bengkulu yang terbaik dengan AIC 207,40 dan SBC 215,06. Model ini selanjutnya dapat digunakan untuk peramalan.
The aim of this study was to describe the numeracy abilities of junior high school students in Bengkulu City in solving math problems based on minimum competency assessment questions. The results of this study for the long term can be used to prepare students’ abilities to face the minimum competency assessment test. The research method used is survey research with a qualitative descriptive approach. The population in this study were all Class VIII students from the State and Private junior high schools of Bengkulu City, namely 40 schools. Sample selection was done in two stages: stratified random sampling and simple random sampling. The research sample consisted of 8 junior high schools in Bengkulu City that met the sample criteria. Data was collected using the minimum competency assessment level 4 math test instrument with 8 items based on the minimum competency assessment grid. Data analysis was carried out with descriptive statistics to describe students' abilities, and prediction tests were conducted using regression tests to describe students' readiness to take the minimum competency assessment test. The results of the study based on the material aspect showed that: (1) students' mastery of number material was 54.47%, (2) algebraic material mastery was 46.44%, (3) students' mastery of geometry material was 33.15%, and (4) material data and opportunities of 18.81%. The analysis results of the level of student knowledge about implementing minimum competency assessment are, on average, in the less category with a percentage of 48.42%. Based on the results of the study, it is recommended that there be the socialization of the application of minimum competency assessment to teachers and students as well as the preparation of special questions so that students are accustomed to solving minimum competency assessment-based questions.
Pertumbuhan ekonomi Provinsi Bengkulu sangat penting untuk diperhatikan karena Provinsi Bengkulu merupakan termiskin di Pulau Sumatra pada tahun 2019. Pertumbuhan ekonomi dapat dilihat dari YoY PDRB ADHK (%) setiap triwulan yang dipublikasikan oleh BPS Provinsi Bengkulu. Analisis data pada penelitian ini bertujuan melakukan peramalan dengan menggunakan teknik pemulusan yang cocok: Single Moving Average (SMA), Single Eksponential Smoothing (SES) dan Ensemble kedua pemulusan tersebut. Peramalan SMA, SES dan Ensemble mengahasilkan urutan MAPE terbaik yaitu pada SMA 1,779416%, kemudian ensemble 2,064708% dan terakhir SES 2,350206%. Hasil ini menunjukkan bahwa teknik pemulusan yang paling baik ialah SMA dengan m=4 dengan nilai MAPE yang diperoleh untuk data in sample 5.752% dan data out sample (dua periode) diperoleh MAPE 1,780%.
Keterbukaan informasi merupakan hal yang sangat penting di era digital saat ini. Pengabdian kepada masyarakat yang dilakukan bertujuan untuk peningkatan skill perangkat desa sehingga mampu memberikan informasi yang valid, informatif dan terperinci tentang kependudukan desa. Informasi data desa yang tersaji secara menarik, informatif dan terperinci akan menjelaskan kondisi desa kepada seluruh masyarakat desa dan umum. Lokasi pendampingan ialah Desa Pekik Nyaring Kecamatan Pondok Kelapa, Kabupaten Bengkulu Tengah. Desa ini termasuk kedalam daerah pemekaran menjadi kabupaten baru sehingga keterbukaan data penduduk sangat penting. Pelatihan pembuatan publikasi data desa dilakukan dalam tiga tahap yaitu sosialisasi, pelatihan, publikasi hasil pelatihan. Sosialisasi yang disambut baik oleh kepala desa dan perangkatnya menjadikan pelatihan dapat dilaksanakan dengan baik. Data kependudkan desa yang dianalisis secara statistik deskriptif menggunakan Ms.Excel dengan pivot table, chart, data validation, dan fungsi statistika yang telah tersedia. Selanjutnya hasil analisis deskriptif di analisis dan di desain menjadi menarik dan dipublikasikan. Hasil publikasi dapat menjelaskan semua informasi kependudukan desa seperti jumlah penduduk, pekerjaan, agama, tingkat pendidikan, demografi desa, kepala keluarga dan jumlah penduduk. Pendampingan yang mendapat respon positif dengan ditunjukkannya adanya publikasi data desa pertama kali yang berbentuk infografis desa yang dapat diperoleh di tempat umum.Kata Kunci: data kependudukan; infografis; pendampingan. Assistance of Village Apparatus for Training on Making Village Population Data Infographics ABSTRACTInformation disclosure is very important in the digital era. Community service aims to improve the skills of village officials so that they are able to provide valid, informative and detailed information on village population. The village data information presented in an interesting, informative and detailed manner will explain the condition of the village to all village communities and the general public. The location of the assistance was Pekik Nyaring Village, Pondok Kelapa District, Bengkulu Tengah Regency. This village is a region that has become a new regency so open disclosure of population data is very important. The training on making village data publications was carried out in three stages: socialization, training, publication. The socialization was welcomed by the village head and his apparatus. Village population data were analyzed using descriptive statistics using Ms. Excel with pivot tables, charts, validation data, and statistical functions that were available. Furthermore, the results of descriptive analysis are analyzed and designed to be interesting and published. The results of the publication can explain all village population information such as population, occupation, religion, education level, village demographics, family heads and population. Assistance that received a positive response by showing the existence of the first village data publication in the form of village infographics that can be obtained in public places.Keywords: population data; infographic; accompaniment.
The objectives of this dedication program is to build up and to guide the students in understanding, analyzing, and solving the problem in Mathematics Olympic, thus they know the strategies and the quickest way to solve the Olympic question precisely. This program is also to prepare the students participating the mathematics Olympic to get more competitive in higher level. The methods used in this dedication program are collecting the materials and the latest Olympic paper test, selecting potential students in mathematics, pre-testing, building up, and post-testing. One of the result of this dedication program showed that the knowledge of SMAN 8 Kota Bengkulu students toward mathematic Olympic was good, moreover some students have participated Mathematic Olympic in junior high level.
Poverty is a global problem that is of concern to the world. It can be seen from the SDGs declaration, which makes poverty a top priority. Good poverty management will help solve other world problems such as hunger, health, welfare, education, and sanitation. To achieve the goal of handling poverty quickly and maximally, an analysis that can identify poor households correctly can be designed so that a targeted program can be designed according to the characteristics of households classified as poor households. One of the statistical methods used to see these characteristics is a classification tree such as the Classification and Regression Tree (CART). The weakness of the cart method if there is an unbalanced dataset type can be overcome by the SMOTE method. In addition to the CART method, classification will be carried out using Random Forest and Xgboost. The results show that the random forest CART model has the highest AUC value in balanced data. It is indicated that this method is better than the others. Based on random forest, variables that determine the most determined poor households are number of household members, last diploma of the head of the home, and floor area of the house.
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