Prediction of Local Government Revenue using Data Mining Method

Local Government Revenue or commonly abbreviated as PAD is part of regional income which is a source of regional financing used to finance the running of government in a regional government. Each local government must plan Local Government Revenue for the coming year so that a forecasting method is needed to determine the Local Government Revenue value for the coming year. This study discusses several methods for predicting Local Government Revenue by using data on the realization of Local Government Revenue in the previous years. This study proposes three methods for forecasting local Government revenue. The three methods used in this research are Multiple Linear Regression, Artificial Neural Network, and Deep Learning. In this study, the data used is Local Revenue data from 2010 to 2020. The research was conducted using RapidMiner software and the CRISP-DM framework. The tests carried out showed an RMSE value of 97 billion when using the Multiple Linear Regression method and R2 of 0,942, the ANN method shows an RMSE value of 135 billion and R2 of 0.911, and the Deep Learning method shows the RMSE value of 104 billion and R2 of 0.846. This study shows that for the prediction of Local Government Revenue, the Multiple Linear Regression method is better than the ANN or Deep Learning method. Keywords— Local Government Revenue, Multiple Linear Regression, Artificial Neural Network, Deep Learning, Coefficient of Determination

Religiosity and Halal Certification: Its Effect on Interest in Buying Traditional Food

This study aims to determine (1)—the influence of religiosity on the interest in buying traditional food of sate bandeng. (2). The effect of halal certification on the interest in buying traditional food of sate bandeng. And (3). The impact of religiosity and halal certification on interest in buying traditional food of sate bandeng. This research is the millennial consumers of traditional food of Sate Bandeng Kang Cepi Kaujon, Serang City, Banten Province. The research method used is quantitative. Methods of data collection using a questionnaire. Data were processed using SPSS version 23 software. Data analysis used the multiple linear regression method. The results of this study indicate that (1). Religiosity affects an interest in buying traditional food of Sate Bandeng. (2). Halal certification affects an interest in buying traditional food of sate bandeng (3). Religiosity and halal certification have a positive and significant impact on interest in buying traditional food of Sate Bandeng. Consumers’ interest in buying traditional food of Sate Bandeng is influenced by religiosity and halal certification as much as 48.8 percent. In comparison, the remaining 51.2 percent is influenced by other variables not examined in this study.

PENGARUH EKSPOR MIGAS, PENANAMAN MODAL ASING, UTANG LUAR NEGERI, DAN INFLASI TERHADAP PERTUMBUHAN EKONOMI INDONESIA

This study aims to analyze the partial and simultaneous effect of oil and gas exports, foreign investment, foreign debt and inflation on Indonesia's economic growth in 1975-2019. The research method uses a quantitative approach which will be explained associatively. The data analysis used is multiple linear regression method as an econometric tool to describe the characteristics of a sample or observed location with the help of SPSS 26 for windows. The results of the study prove that partially oil and gas exports, foreign debt, and inflation affect Indonesia's economic growth. Meanwhile, foreign investment has no effect on Indonesia's economic growth. Simultaneously, the variables of oil and gas exports, foreign investment, foreign debt and inflation affect Indonesia's economic growth. This is supported by the R2 value of 0.599 which means that 59.9 percent of the variation in economic growth is influenced by oil and gas exports, foreign investment, foreign debt and inflation, while the remaining 40.1 percent is influenced by other factors not included in the model.

Analysis of factors affecting motor vehicle tax revenue (South Sumatra Province 2006-2020)

This study aims to determine the effect of changes in investment, consumption, DGFB per capita, inflation on motor vehicle tax revenues in South Sumatra Province. Motor vehicle tax revenues were sampled with the research period 2006-2020. The research used the multiple linear regression method. The results showed that changes in investment, consumption, and inflation did not significantly affect motor vehicle tax revenues in South Sumatra in 2006-2020. Meanwhile, DGFB per capita has a significant positive effect on motor vehicle tax revenues in South Sumatra in 2006-2020.

Fakor-Faktor Yang Mempengaruhi Pendapatan Petani Padi Di Kelurahan Pekkabata Kecamatan Duampanua Kabupaten Pinrang

Penelitian ini bertujuan untuk mengetahui Apakah faktor luas lahan, jumlah tenaga kerja ,biaya produkisi dan bibit berpengaruh terhadap pendapatan petani padi di Kecamatan Duampanua Kelurahan Pekkabata dan Untuk mengetahui faktor apa yang paling berpengaruh diantara luas lahan, jumlah tenaga kerja, biaya produkisi dan bibit terhadap pendapatan petani padi di Kelurahan Pekkabata Kecamatan Duampanua Kabupaten Pinrang. Data yang digunakan dalam penelitian ini adalah data primer dan sekunder. Metode anilisis data yang digunakan adalah metode deskriptif dan metode regresi linear berganda. Hasil penelitian menunjukkan bahwa variabel luas lahan jumlah tenaga kerja, biaya produksi memiliki pengaruh yang signifikan terhadap pendapatan petani padi di Kecamatan Duampanua Kelurahan Pekkabata. This study aims to find out whether the factors of land area, number of workers, production costs and seeds affect the income of rice farmers in Duampanua District, Pekkabata Village and to find out what factors are the most influential among land area, number of workers, production costs and seeds on the income of rice farmers in Pekkabata Village, Duampanua District, Pinrang Regency. The data used in this study are primary and secondary data. The data analysis method used is descriptive method and multiple linear regression method. The results showed that the variables of land area, number of workers, production costs had a significant influence on the income of rice farmers in Duampanua District, Pekkabata Village.

FINANCIAL LITERACY ON SMALL AND MICRO BUSINESS OF THE INDIGENOUS PEOPLE OF PAPUA IN JAYAPURA CITY

This study is a quantitative study that aimed to find the level of financial literacy of Papuan Micro, Small, and Medium Enterprises (MSME) and the factors that influence it. The sample consisted of 75 respondents of MSME actors in Jayapura city at Pasar Mama-Mama Papua. The data was analyzed using multiple linear regression method with SPSS version 22.0. The results showed that (1) the level of financial literacy in Jayapura city is low, (2) there is no influence of gender towards the level of financial literacy, (3) there is an influence of last educational level towards the level of financial literacy, (4) there is no influence of monthly profit towards the level of financial literacy, (5) there is an influence of investment towards the level of financial literacy, (6) there is an influence of borrowing and saving in bank towards the level of financial literacy, (7) there is an influence of insurance towards the level of financialliteracy.

An Analysis of Push and Pull Factors towards Purchase Intention to Shop at Batik Trusmi Cirebon

This research is design to analyze how the concept of push-and-pull factors positively impact the purchase intention at Batik Trusmi Cirebon. The research models are made to measure the impact between push factors and pull factors towards purchase intention. The research subject in this research is the customers who have shopped at Batik Trusmi Cirebon. 160 respondents are taken as samples and the data have been analyzed with multiple linear regression method. The result shows that push factors and pull factors are positively impact purchase intention. This means, both of the hypothesis are accepted. Batik Trusmi Cirebon could improve their marketing strategy such as promotion and quality consistency in order to attract more customers and other recommendation are made based on this research finding which is concluded in the last chapter.

Pengaruh Rasio Likuiditas, Rasio Biaya, Kecukupan Modal, dan Risiko Kredit sebagai Moderasi terhadap Profitabilitas Bank

The 2020 pandemic affected the economic sector, including banking sector, especially banks in the BUKU 1 category. This study aims to identify internal factors that affect bank profitability between normal conditions in 2019 and conditions when economic growth experienced a contraction due to the pandemic in 2020. This study is based on the theory of Asset-Liability Management (ALM) and uses multiple linear regression method with ROA as a measure of profitability, LDR, BOPO, and CAR as independent variables, and NPL as quasi moderator. The results of this study provide findings that to maintain profitability, banks need to pay attention to cost efficiency which is reinforced by the risk of bad loans. Meanwhile, in unstable conditions, there are additional liquidity risk factor that must also receive attention. Thus, the results of this study are in line with the liability management approach. Keywords : Bank profitability; Normal Condition, Contraction of Economic Growth.

Construction of new financial e-commerce model for small and medium-sized enterprises financing based on multiple linear logistic regression

This paper expounds on the development prospects of SMEs and E-commerce finance, and illustrates the significance of developing online finance. It also introduces the commonly-used research methods of the two kinds of financial models, such as multiple linear regression method and logistic regression method, and analyzes the reasons for the financing difficulties of SMEs. Currently, the high financing cost is the main reason for the financing difficulties of SMEs. Several reasons are account for the high financing cost. Among them, high financing cost,low-efficiency financial system,long financing cycle and the loan information asymmetry account for 35%, 21%, 19% and25% respectively. In addition, this paper clarifies the advantages and disadvantages of network finance and the necessity of developing online finance.

Personalized Drug-Disease prediction using Multiple Linear Regression with ReLU

Predicting models for personalized Drugs related to specific disease are essential, as traditional methods are expensive and time consuming. The most challenging task in personalized medicine is predicting the status of disease from high dimensionality data. In the biomedical domain the association between drugs and disease plays a vital role as the same drug may treat similar diseases. For the good adaptability to complex and nonlinear behaviour data, Multiple Linear Regression method with ReLU Activation function is used for calculation and to fit the model with Drug –Disease dataset. Based on the results the drug or combination of drugs that treat a specific disease is predicted efficiently.