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ANALISIS KEMAMPUAN, MOTIVASI DAN LINGKUNGAN KERJA TERHADAP KINERJA KARYAWAN (STUDI KASUS PT. THAMRIN BROTHERS YAMAHA PALEMBANG) M Yunus; Ngudiantoro Ngudiantoro; Oki Dwipurwani
ILTIZAM Journal of Shariah Economics Research Vol. 2 No. 2 (2018): Iltizam Journal of Shariah Economic Research
Publisher : Islamic Economics Department, Faculty of Islamic Economics and Business, UIN SULTHAN THAHA SAIFUDDIN JAMBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (444.183 KB) | DOI: 10.30631/iltizam.v2i2.161

Abstract

Penelitian ini bertujuan untuk mengetahui pengaruh kemampuan, motivasi, dan lingkungan kerja terhadap kinerja karyawan. Penelitian dilakukan terhadap 80 karyawan PT. Thamrin Brothers Yamaha Palembang. Metode yang digunakan yaitu Analisis Komponen Utama dan Analisis Regresi Komponen Utama. Dari hasil analisis komponen utama diperoleh satu komponen utama bersama yaitu komponen utama internal (kemampuan, motivasi, dan lingkungan kerja) yang dipertahankan dengan kontribusi keragaman 72,193%. Hasil pemodelan menunjukkan bahwa satu komponen utama bersama tersebut berpengaruh nyata terhadap kinerja karyawan perusahaan dengan koefisien determinasi 42,8%. Secara parsial, komponen utama internal berpengaruh nyata terhadap kinerja karyawan sebesar 48,5%. Berdasarkan hasil tersebut, maka peningkatan kinerja karyawan berdasarkan komponen utama internal dapat dilakukan dengan meningkatkan, berturut-turut, motivasi kerja, kemampuan kerja, dan lingkungan kerja.
Analisis Pertumbuhan Ekonomi Provinsi Jambi 2012-2019 M Yunus; Novi Mubyarto; Robi Agustin
ILTIZAM Journal of Shariah Economics Research Vol. 4 No. 2 (2020): Iltizam Journal of Shariah Economic Research
Publisher : Islamic Economics Department, Faculty of Islamic Economics and Business, UIN SULTHAN THAHA SAIFUDDIN JAMBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/iltizam.v4i2.598

Abstract

The development achievement of an economic activity can be measured by economic growth. Economic growth will improve if there are activities carried out by humans for the prosperity of the earth and their prosperity. An important factor for increasing economic growth is international trade, one of which is exports. Allah SWT has created in every region and country the advantages and disadvantages. The main factor that also has an influence on the economic development of a country / region is investment activities. Regarding investment in the Al Qur’an, it is clearly stated that investing is a way that is ordered by Allah SWT not to leave the weak generation. In this study, an analysis of the economic growth of the province of Jambi was conducted in 2012-2019. The method used is multiple linear regression analysis. Based on the results of using the R application, there is a significant influence between the export variable and the investment variable on the economic growth variable. The modeling results obtained are Y = 5848.0543 + 0.8886X1 + 0.7929X2. Every increase in exports of 1 billion and investment is considered constant, it will increase economic growth by 0.8886 billion. Every increase in investment of 1 billion and exports are considered constant, it will increase economic growth by 0.7929 billion. The coefficient of determination of 94.06 percent means that the diversity of economic growth variables can be explained by the export and the investment, the remaining 5.94% is explained by other variables not included in the regression model.
PERBANDINGAN ORDINAL FOREST DAN REGRESI LOGISTIK ORDINAL Yunus, M.; Khairil Anwar Notodiputro; Bagus Sartono
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 15 No 2 (2023): Journal of Statistical Application and Computational Statistics
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v15i2.399

Abstract

Terdapat banyak metode yang digunakan untuk mengidentifikasi prediktor penting dan memprediksi nilai dari peubah respons ordinal. Namun saat ini, terdapat metode prediksi untuk peubah respons ordinal yang tidak menggunakan sifat ordinal dari peubah respons tersebut. Penelitian ini menggunakan metode ordinal forest dan sebagai pembanding digunakan juga metode regresi logistik ordinal. Nilai akurasi dan kappa metode ordinal forest pada setiap ulangan (5 ulangan) selalu lebih besar dari pada regresi logistik ordinal. Selanjutnya, nilai akurasi dan kappa setiap kelompok berdasarkan PDRB pada metode ordinal forest selalu lebih besar dari pada regresi logistik ordinal. Sehingga didapatkan metode ordinal forest lebih baik digunakan pada data peringkat status indeks desa membangun Provinsi Maluku Utara tahun 2020.
PENGARUH IMPOR TERHADAP PERTUMBUHAN EKONOMI DI PROVINSI JAMBI Muhamad Subhan; M. Yunus; Robi Agustin
Al-Iqtishad: Jurnal Ekonomi Syariah Vol. 2 No. 02 (2021): Januari-Juni 2021
Publisher : Program Studi Ekonomi Syariah

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Economic growth is a measure of the progress of an economic movement. Islamic economic growth has existed during the dialogue of classical Muslim thought, namely the so-called "prosperity of the earth". The term prosperity of the earth contains knowledge related to economic growth, according to what Ali bin Abi Talib Radhiyallahu Anhu conveyed to the governor in Egypt: “You should pay attention to land prosperity with a higher concern than tax collection, because the tax can be increased by making land prosperous. Whoever collects taxes without considering the welfare of the land, the nation is headed for destruction”. Some of the basic knowledge related to economic growth is viewed from the perspective of sharia, namely a description of economic problems. Islam explains that the case is in line with the role prepared by Allah Subhanahu Wa Ta'ala for human needs in order to solve the problems of human life. Export and import activities generate many benefits for the participating countries. This study looked at the effect of the import variable on the economic growth variable in Jambi province. The method used is simple correlation and regression analysis. The result of using correlation analysis shows that there is a very strong positive relationship between the import variable and the economic growth variable. Based on the results of simple regression analysis, there is an influence between the import variables on the economic growth variable. Every increase in imports of 1 billion rupiah so that it will increase economic growth, namely 1.433 billion rupiah. The coefficient of determination (R2) is 77.39%, meaning that the diversity of economic growth can be explained by imports. Furthermore, 22.61% is explained by other variables that are not included in the regression model.
PEMODELAN STATISTICAL DOWNSCALING DENGAN LASSO DAN GROUP LASSO UNTUK PENDUGAAN CURAH HUJAN M. Yunus; Asep Saefuddin; Agus M Soleh
Indonesian Journal of Statistics and Applications Vol 4 No 4 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i4.724

Abstract

One of the rainfall prediction techniques is the Statistical Downscaling Modeling (SDS). SDS modeling is one of the applications of modeling with covariates conditions that are generally large and not independent. The problems that will be encountered is the problem of ill-conditional data i.e multicollinearity and the high correlation between variables. The case of highly correlated data causes a linear regression coefficient estimators obtained to have a large variance. This research was conducted to make the statistical downscaling modeling using the lasso and group lasso for the prediction of rainfall. Group of the covariate scenario is applied based on the adjacent area, the high correlation between covariates and correlation between covariates and responses, and also the addition of dummy variables. Scenario six (grouping which is done by considering the covariates that have a positive correlation to the response is divided into 3 groups, 1 individual and the covariates that are negatively correlated with the response are divided into 2 groups, 1 individual) is better than the other scenarios in linear modeling without a dummy. Then, linear modeling with a dummy is better than without a dummy for both techniques. In linear modeling with a dummy, the Group lasso technique can be considered more in SDs modeling, because the difference in the RMSEP statistical value and the correlation coefficient value is significant.