The concept of entropy as used in communication is related to

Entropy in Communication:

• The entropy was originally created by Shannon as part of his theory of communication, in which a data communication system is composed of three elements: a source of data, a communication channel, and a receiver. 
• In Shannon's theory, the "fundamental problem of communication" – as expressed by Shannon – is for the receiver to be able to identify what data was generated by the source, based on the signal it receives through the channel.
• Shannon considered various ways to encode, compress, and transmit messages from a data source, and proved in his famous source coding theorem that the entropy represents an absolute mathematical limit on how well data from the source can be losslessly compressed onto a perfectly noiseless channel
• In information theory, the entropy of a random variable is the average level of "information", "surprise", or "uncertainty" inherent in the variable's possible outcomes.
• Entropy refers to messages which convey highly unpredictable information to the receiver. 

Important Points

Conclusion:

• The encode-decode model of communication implies that in order to improve communication two influencing factors should be managed: noise (physical and semantic) should be reduced and capacity (sender-receiver and channel) should be increased.
• In addition, to more effectively transmit a message there should be an appropriate balance between so-called entropy and redundancy.
• Entropy refers to the message that conveys unpredictable information to the receiver. So here entropy is related to the order or sequence in which the message is transferred through a channel to the receiver. Hence, option (3) is correct.