Development of environmental model performance green productivity for small and medium industries

Small and Medium Industries has a very important role in supporting the Indonesian economy and reduce unemployment. SMEs in Indonesia contributed in employment amounted to 99.74% of the total national uptake and contribute as much as 1013.5 trillion or 56.73%. As a country that is trying to give a full effort in implementing environmental management systems in all sectors of activity, we need to pay attention to the sector of Small and Medium Industries in terms of environmental management systems. Presumably most of the SMEs in Indonesia have never committed any good environmental management. On the other hand, good environmental management which is performed by company may help to improve efficiency, reduce excessive consumption of resources, reduce waste, help the company in meeting the requirements of environmental law, encourage employment to engage in environmental performance and improve company customer relationship. This study examines indicators that influences the ability of the environmental performance of food and beverage SMEs in East Java, and measure the effect of leadership on human resources, process and environmental management as well as the influence of process and environmental management of the Environmental Performance Indicator, to illustrate how the positive and negative effects of this research using Structural Equation Modeling (SEM) approach. Based on the t-value result, shows that significant variable is the leadership on the processes and environmental management, for human resources, process variables and environmental management of the Environmental Performance Indicator and Environmental Performance Indicator environmental performance

Model Analisis Kasus Covid-19 di Indonesia Menggunakan Algoritma Regresi Linier dan Random Forest

Kenaikan kasus covid-19 di Indonesia tidak bisa diperkirakan perkembangannya, sehingga menyebabkan buruknya berbagai aspek kehidupan di Indonesia. Analisis data sangat penting untuk dilakukan, dengan menganalisis maka akan dihasilkan informasi baru yang bisa digunakan untuk menunjang penelitian lebih dalam terhadap permasalahan yang sama. Penelitian ini bertujuan untuk menganalisis data covid-19 di Indonesia dengan cara  mengetahui nilai akurasi yang diperoleh dalam data. Dalam penelitian ini metode yang digunakan yaitu metode regresi linier dan random forest. Hasil penelitian dapat diketahui bahwa dalam penelitian ini cara analisis yang dilakukan yaitu menggunakan perhitungan manual dengan tools microsoft excel, pemrograman bahasa python menggunakan tools google colaboratory dan perangkat lunak pengolahan data menggunakan tools rapidminer. Nilai akurasi dalam setiap metode dapat berbeda sesuai dengan tools yang digunakan. Pada metode regresi linier nilai akurasi tertinggi adalah 99,7% dengan nilai RMSE (root mean squared error) yaitu 26,19, data tersebut dianalisis menggunakan perhitungan manual dengan tools microsoft excel. Sedangkan untuk metode random forest nilai akurasi tertinggi adalah 98,4% dan dianalisis menggunakan tools rapidmine