Analisis Prediksi Kebangkrutan Perusahaan Jasa Sektor Transportasi Di BEI Periode 2019-2021

This research aims to determine the prediction and level of accuracy of bankruptcy predictions between the Altman, Zmijewski, Grover, Springate, Fulmer, and Foster models. The sample used in this research is a transportation sector service company listed on the Indonesia Stock Exchange. The sample was selected using a purposive sampling technique and obtained a sample size of 21 companies from a population of 47 companies. In this research, the data analysis technique used is descriptive analysis. Based on the results of data analysis, there are differences in results between the Altman, Zmijewski, Grover, Springate, Fulmer, and Foster models in predicting bankruptcy. The accuracy levels obtained from the highest to the lowest respectively were the Grover model (76%), Zmijewski model (71%), Springate model (67%). Fulmer model (57%), Altman model (43%), and Foster model (38%). The Grover model is a bankruptcy prediction model that has the highest accuracy rate of 76%.

Allelopathy Evaluation of Weeds for Environmental Risk Assessment

The present study represents the comprehensive screening of allelopathic activity of weeds from Pakistan. The source for existing research of weed control in crops, is the screening of large quantities of plants towards classifying the potent organic compounds. Strong allelopathic weeds species have been acknowledged from analysis to provide direction for further research. A total of 73 weeds species were examined for their allelopathic potentials through latest bioassay activity i.e Sand wich and Dishpack evaluation techniques. Even though from the interference of chemical from other means is cumbersome to separate, also the advance research studies have generated compatible and convincing information in this field of study. As a follow up work of present endeavor; methanolic leaf extracts of strongest allelopathic species (Melilotus indica L., Melilotus alba Desr., Medicago parviflora E.H.L. Krause and Solanum nigrum L.) were tested for fungicidal activities on soil-borne crops pathogens (Rhizoctonia solani, Rhizoctonia oryzae, Fusarium fujikuroi, Fusarium oxysporum, Pythium ultimum and Pyricularia oryzae). Microspectrophotometric assessment technique has been used for the antifungal evaluation. Minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) of the extracts were determined. The amended methanolic extract and known fungicide Nystatin for respective fungal strain were considered as negative and positive control respectively. Results indicated that growth of all the fungal strains mentioned were significantly inhibited. The values of the weed extracts determined ranging between 0.781-25 mg/mL while MFC values ranging between 3.125-25 mg/mL. The extracts of Medicago parviflora showed highest inhibitory activity (119.5%) against Pythium ultimum while Melilotus indica extract showed lowest suppression (97%) against Fusarium oxosporum. Even at very low xiii concentration, all the plants selected showed maximum fungicidal properties. These results support the potential use of these plant extracts in the management of diseases caused by plant tested pathogenic fungi. The research information generated from the present work can be used as a benchmark for future research on the allelochemical identification and characterization. During the follow up work of present endeavor; allelopathic cover crop for biological control of weeds to support agro-environment conservation. In Pakistan, the allelopathic activity evaluation of plants through bioassay techniques is quite rare. There is a dire need to develop a complete data base of plants having strong allelopathic potential through application of these latest techniques