PENINGKATAN KREATIVITAS MAHASISWA MELALUI PENYUSUNAN INSTRUMEN PENELITIAN

Instrumen merupakan alat ukur dari sebuah penelitian yang dilakukan. Keberadaan instrumen adalah hal yang tidak bisa dipisahkan dari sebuah penelitian. Karena apa yang menjadi topik pembicaraan dalam penelitian tentu akan tertuang dalam instrumen. Tujuan pelaksanaan pengabdian ini yaitu agar mahasiswa mampu menggali kemampuan yang dimiliki dalam menyusun berbagai instrumen penelitian sesuai dengan bidang ilmu yang ditekuni. Metode pendekatan yang dilakukan yaitu coaching class. Hasil yang diperoleh melalui pelaksanaan pengabdian ini yaitu pengetahuan tentang pentingnya mengetahui pola penyusunan instrumen penelitian yang pada akhirnya tentu akan meringankan proses penyelesaian berbagai kasus dikehidupan sehari-hari bahkan jurusan masing-masing

Small Area Estimation Terhadap Pengeluaran Per Kapita Di Kabupaten Banyuwangi Dengan Metode Hierarchical Bayes Dan Empirical Bayes

Salah satu indikator ekonomi yang banyak digunakan untuk mengukur tingkat kemakmuran dan kesejahteraan adalah pendapatan per kapita. Namun data pendapatan yang akurat sulit diperoleh. Dalam kegiatan Susenas data pendapatan didekati melalui data pengeluaran rumah tangga. Penelitian ini menggunakan metode Hierarchical Bayes (HB) dan Empirical Bayes (EB) yang diaplikasikan pada Small Area Eastimation (SAE) untuk menduga pengeluaran per kapita di Kabupaten Banyuwangi. Hasil penelitian menunjukkan bahwa estimasi tidak langsung menggunakan pendekatan Hierarchical Bayes dan Empirical Bayes menghasilkan nilai RMSE yang lebih kecil dari pada estimasi langsung. Disisi lain, Metode HB menghasilkan nilai RMSE yang lebih kecil daripada metode EB, sehingga penelitian ini menyarankan untuk menggunakan metode HB untuk memperkirakan pengeluaran per kapita di Kabupaten Banyuwangi daripada perkiraan langsung yang digunakan saat ini. ================================================================================== One of the economic indicators that are widely used to measure the level of prosperity and welfare is per capita income. However, an accurate income data is difficult to be obtained. In Susenas this data is approached by using data on expenditures per capita. This study employ Hierarchical Bayes (HB) and Empirical Bayes (EB) methods to be applied to Small Area Estimation (SAE) to estimate the expenditure per-capita in Banyuwangi. The results showed indirect estimation using hierarchical Bayes and Empirical Bayes produce RMSE values smaller than the direct estimation. The HB method, on the other hand, produces smaller RMSE value than the EB method. Finally, this research suggests to use HB method to estimate the expenditure per-capita in Banyuwangi rather than direct estimation which is used nowadays

Small Area Estimation Of Expenditure Per-capita in Banyuwangi with Hierarchical Bayesian and Empirical Bayes Methods

One of the economic indicators that are widely used to measure the level of prosperity and welfare is per capita income. However, an accurate income data is difficult to be obtained. In Susenas this data is approached by using data on expenditures per capita. This study employ Hierarchical Bayes (HB) and Empirical Bayes (EB) methods to be applied to Small Area Estimation (SAE) to estimate the expenditure per-capita in Banyuwangi. The results showed indirect estimation using hierarchical Bayes and Empirical Bayes produce RMSE values smaller than the direct estimation. The HB method, on the other hand, produces smaller RMSE value than the EB method. Finally, this research suggests to use HB method to estimate the expenditure per-capita in Banyuwangi rather than direct estimation which is used nowadays

PERAMALAN INDEKS HARGA YANG DIBAYAR PETANI (PUPUK DAN PESTISIDA) DI PROVINSI NUSA TENGGARA BARAT MENGGUNAKAN METODE ARIMA INTERVENSI

The level of farmer welfare can be measured through the Farmer’s Terms of Trade (FTT), one of the indicators used to measure it is the Price Paid by Farmers Index (IB). IB is expenditure by farmers in the form of goods or services for household consumption, production costs, and additional capital goods, while the prices of fertilizers and pesticides contribute to determining the IB value in the production cost category. Because the FTT is largely determined by the IB in the fertilizer and pesticide category, a more in-depth analysis of the development of this index value is needed so that forecasts can be made regarding the development of the IB in the fertilizer and pesticide category for the next period. The data used in this research is data on the Price Index Paid (IB) of farmers for production costs in the form of fertilizers and pesticides from January 2017 to December 2021. The research method used is ARIMA intervention because of the drastic decline in IB during the pandemic COVID. IB forecasting results for the next six months show an upward trend, and in June 2022 it will reach a price index of 120.937

Structural Equation Modeling-Partial Least Square for Poverty Modeling in Papua Province

Poverty in Papua Province in 2018 has increased from the previous year. The poverty rate in Papua Province in March 2018 reached 27,74%. This study aims to analyze the factors that influence it so that it can be handled properly. The research method used in this research is Structural Equation Modeling (SEM) with the Partial Least Squares (PLS) approach. The research variables used consisted of 4 latent variables (Poverty, Economy, Human Resources (HR), and Health) with 16 indicators (manifest variables). Based on the analysis that has been done, it is found that economic and health variables have a negative and significant effect on poverty with path coefficients of -0,421 and -0,270, respectively. The health variable has a positive and significant effect on HR with a path coefficient of 0,496. Meanwhile, the HR variable has a positive and significant effect on the economy with a path coefficient of 0,801. It can be concluded that there are two variables that have a significant effect on poverty in Papua Province, including the economy and health

Clustrering of BPJS National Health Insurance Participant Using DBSCAN Algorithm

In the current era of Big Data, getting data is no longer a difficult thing because they can access easily it via the internet, which is open access. A large amount of data can cause many problems in the data, such as data that deviates too far from the average (outliers). The method used to handle outlier data is DBSCAN which is density based clustering. The DBSCAN can be applied in various fields, one of which is the social sector, namely the participation of the JKN BPJS Health in West Nusa Tenggara. This study sees the distribution of BPJS Health participation groups, and to detect outliers so that objects with noise are not included in the cluster. The results of the study using the DBSCAN algorithm show that the optimal epsilon value is between 0.37 points by observing the knee of a curve. and MinPts 3, with the highest silhouette value of 0.2763. The highest JKN BPJS participants are in cluster 1 with 5 sub-districts, the second highest cluster is cluster 3 with 5 sub-districts, while the lowest cluster is cluster 2 with 93 sub-districts. The 13 sub-districts are not included in any group because they are noise data

MODEL ARIMA BOX-JENKINS UNTUK MERAMALKAN JUMLAH KUNJUNGAN WISATAWAN MANCANEGARA DI KABUPATEN LOMBOK BARAT

The development of tourism in West Lombok is supported by geographical conditions with scattered clusters of small islands (gili), tropical climate, and the cultural peculiarities of the Sasak tribe, so that it becomes an attraction in the development of global tourist destinations. West Lombok tourism development will be even more attractive with the establishment of the Mandalika National Tourism Development Strategic Area. West Lombok can play a role concurrently with this strategic policy momentum. Developing new growth centers based on the tourism sector in collaboration with other sectors and packaging the village's potential to become a thematic tourism village. Methods for predicting the number of tourist visits to West Lombok Regency are urgently needed to assist the district government in preparing appropriate facilities and infrastructure if there is a possibility of an increase in tourist visits. The method used in this study is the Box-Jenkins ARIMA method to predict the number of foreign tourist visits in West Lombok Regency. The data used in this study is secondary data sourced from the West Lombok Regency Tourism Office from January 2014 to December 2021. The results showed that the ARIMA model (2,1,2) is the most suitable model for predicting the number of foreign tourist visits to West Lombok Regency because this model produces the smallest Sum of Squared Errors (SSE) and Mean Squared Error (MSE) values compared to other models

Model Regresi Zero Inflated Poisson Pada Data Overdispersion

Overdispersion is a phenomenon of the data variance greater than the average. One of the causes of overdispersion is too many zero value (excess zero) on the response variable. Zero inflated Poisson regression model (ZIP) is one of the method that can be used to overcome problems due to excess zeros. The purpose of this research is to estimate the regression parameters model Zero -inflated Poisson (ZIP) and applying to the data of unsuccessful students in national examinations in senior high school and vocational school in the city of Mataram. Parameter estimation Zero inflated Poisson regression model using the maximum likelihood and maximization expectation algorithm with Newton Rhapson approach. Zero inflated Poisson regression model obtained on the data is: dan With  is school accreditation; and  is the proportion of teachers who are already certifie