Assoc. Prof. Agata Gąsiorowska of the SWPS University of Social Sciences and Humanities ponders if the Poles know how to manage their money wisely.

The article is about substitute coins issued by Jan Turno in his demesne in Słomowo. The author presents a short history of the Turno family and the short biography of Jan Turno, and then explains the circumstances of the issue of the substitute money from Słomowo in Greater Poland, Oborniki County.

The author reflects on the evaluation of the notion of money in history. In many situations coins and banknotes were a proof for the existence of local, independent, political power. People’s attitude toward money was quite an important matter, too; in many situations neither money nor those professionally dealing with money were appreciated socially. Numerous utopian movements disliked money. Communism was one of them. The communist economy was driven — at least in theory — by overwhelming planning rather than by the incentive of money. After the fall of communism a question arised whether all or nearly all public activity should be driven by money or whether some domains of social activity should rather be kept as public domains.

The paper discusses two characters of speculators as shown in two 19th century novels. Zola’s Aristide Saccard incarnates fever, chaos and prodigality of a provincial who has become a millionaire pursuing his dream of fortune. Guy de Maupassant’s William Andermatt is a banker whose extraordinary capacity of making money is based on rationalism, cold calculation and exceptional intuition. Despite all the differences, they both embody three basic features of a businessman: desire, will and power.

The contribution main from this research is modularity and better processing time in detecting community by using K-1 coloring. Testing performed on transaction datasets remittance on P2P platforms where the Louvain Coloring algorithm is better in comparison to Louvain Algorithm Data used is data transfer transactions made by customers on the P2P Online platform. The data is the User data that has information transfer transactions, Card data that has information card, IP data that has IP information, and Device data that has information device. Every user owns unique 128-bit identification, and other nodes representing card, device, and IP are assigned a random UUID. The Device node has the guide, and device properties. IP nodes only have property guide and node User has property fraud Money Transfer, guide, money Transfer Error Cancel Amount, first Charge back Date. Each node has a unique 128-bit guide, with the amount whole of as many as 789,856 nodes. Application technique K-1 staining on Louvain algorithm shows enhancement value modularity and better processing time for detecting community on the network large scale. Through a series of exercises and tests carried out in various scenarios, it shows that the experiments carried out in this paper, namely the Louvain Coloring algorithm, are more effective and efficient than the Louvain algorithm in scenario 1,3, and 5 meanwhile For Scenarios 2 and 4 Louvain Algorithm is better.