Eco-Productivity Analysis of the Municipal Solid Waste Service in the Apulia Region from 2010 to 2017

This paper presents a dynamic efficiency study of the solid waste management in the municipalities of the Apulia region (Southern Italy). The study employs the non-parametric Global Malmquist Index to measure the change in productivity of the municipal solid waste service from 2010 to 2017. Three different DEA-based models are implemented to measure productivity. The first model computes the service productivity solely from the economic perspective, while the second and third models compute the service productivity from both the economic and environmental perspectives. Adopting two distinct perspectives provides a more comprehensive insight into the performance of the waste management service considering the productivity and the eco-productivity of service provision. The results from the productivity analysis show that, between 2010 and 2017, the municipal solid waste sector was still facing a transitional period characterized by low cost-efficiency and productivity growth measurements. Vice versa, the efficiency and productivity indicators improve when the analysis is performed accounting for the environmental impact. Indeed, both the eco-efficiency and eco-productivity measures increase from 2010 to 2017. Findings demonstrate the critical importance to include environmental indicators in the efficiency and productivity analysis.

Prediksi Target Sistem Productivity Services menggunakan Penerapan Algoritma C4.5 pada PT. Sanggar Sarana Baja Jakarta

There are many ways that each service provider company does, especially services to win the competition, among others, by increasing service productivity targets. One service provider company that is committed to increasing service productivity targets is PT. Sanggar Sarana Baja. This study aims to predict service productivity system targets using the application of Algortima C4.5 at PT. Sanggar Sarana Baja. The attributes of working time input in this study include area, performance, efficiency, and productivity. In this study, it was found that the results obtained came from several input attributes which resulted in a causal relationship in classifying the results of service productivity targets at PT. Sanggar Sarana Baja. This research is expected to help PT. Sanggar Sarana Baja in increasing customer satisfaction to retain customers and increase profits of PT. Sanggar Sarana Baja. Based on the classification results using the C4.5 Algorithm, it shows that the accuracy reaches 95.00%, which indicates that the C4.5 algorithm is suitable for measuring the target level at PT. Sanggar Sarana Baja. Keywords: Accuracy, Validation, Decision Tree, Data mining, KDD, C4.5 Algorithm, Services Companies, Target Services Productivity Systems Banyak cara yang dilakukan oleh masing - masing perusahaan penyedia jasa, khususnya servis untuk memenangkan persaingan, antara lain dengan meningkatkan target produktivitas servis. Salah satu perusahaan penyedia jasa servis yang berkomitmen dalam meningkatkan target produktivitas servis adalah PT. Sanggar Sarana Baja. Penelitian ini bertujuan untuk memperdiksi target sistem produktivitas servis menggunakan penerapan Algoritma C4.5 pada PT. Sanggar Sarana Baja. Atribut masukan waktu kerja dalam penelitian ini mencangkup daerah, kinerja, efisiensi, dan produktivitas. Dalam penelitian ini, didapatkan bahwa hasil yang didapatkan berasal dari beberapa atribut masukan menghasilkan hubungan sebab -akibat dalam mengklasifikasikan hasil dari target produktivitas servis pada PT. Sanggar Sarana Baja. Penelitian ini diharapkan dapat membantu pihak PT. Sanggar Sarana Baja dalam meningkatkan kepuasan konsumen untuk mempertahankan pelanggan dan meningkatkan laba PT. Sanggar Sarana Baja tersebut. Berdasarkan hasil klasifikasi menggunakan Algoritma C4.5 menunjukkan bahwa diperoleh akurasi mencapai 95,00%, yang menunjukkan bahwa algoritma C4.5 cocok digunakan untuk mengukur tingkat target pada PT. Sanggar Sarana Baja. Kata kunci: Akurasi, Validasi, Decision Tree, Data mining, KDD, Algoritma C4.5, Perusahaan Jasa, Target Sistem Productivity ServicesReferensi[1] Yulia and N. Azwanti, “Data Mining Prediksi Besarnya Penggunaan Listrik Rumah Tangga di Kota Batam Dengan Menggunakan Algoritma C4.5,” Semin. Nas. Ilmu Sos. dan Teknol., vol. 1, no. 1, pp. 175–180, 2018.[2] R. Novita, “Teknik Data Mining?: Algoritma C 4 . 5,” pp. 1–12, 2016.

Antecedents and Outcomes of Quality of Work Life Among Employees in Banks

Quality of work life is the major factor to be considered in working environment of any organization. The performance of employees and the organization lies on the ability of the employees based on working environment. The QWL leads to better working environment which improves the performance of organization. The present study has made an attempt to find the level of factors causing QWL and the impact of outcome of QWL in banks. Since the profile of the banks may be associated with the level of outcomes of QWL, the present study has made an attempt to examine it with the help of one way analysis of variance and t-test. The included outcomes of QWL are job satisfaction, job stress, organizational climate, organizational commitment, employees retention behaviour, service quality employees and service productivity of employees. The highly associated determinants of QWL and the significant difference among the PUSBs and PRSBs have been noticed. The significantly associating important profiles of the banks regarding the existence of outcome of QWL are identified.

Assessing the Ecosystem Services of Various Types of Urban Green Spaces Based on i-Tree Eco

Urban green spaces play a crucial role in maintaining urban ecosystem sustainability by providing numerous ecosystem services. How to quantify and evaluate the ecological benefits and services of urban green spaces remains a hot topic currently, while the evaluation is barely applied or implemented in urban design and planning. In this study, super-high-resolution aerial images were used to acquire the spatial distribution of urban green spaces; a modified pre-stratified random sampling method was applied to obtain the vegetation information of the four types of urban green spaces in Luohe, a common plain city in China; and i-Tree Eco model was further used to assess the vegetation structure and various ecosystem services including air quality improvement, rainfall interception, carbon storage, and sequestration provided by four types of urban green spaces. The modeling results reveal that there were about 1,006,251 trees in this area. In 2013, all the trees in these green spaces could store about 54,329 t of carbon, sequester about 4973 t of gross carbon, remove 92 t of air pollutants, and avoid 122,637 m3 of runoff. The study illustrates an innovative method to reveal different types of urban green spaces with distinct ecosystem service productivity capacity to better understand their various roles in regulating the urban environment. The results could be used to assist urban planners and policymakers to optimize urban green space structure and composition to maximize ecosystem services provision.