Task 1: Business English 2

PRONOUN ANALYZE OF THE OPINION ABOUT MACHINE LEARNING THAT WOULD BE PRIMA DONNA IN THE FUTURE

1.1       BACKGROUND

The term Business English can cover a multitude of things. Business English is the type of English used in business contexts, such as international trade, commerce, finance, insurance, banking, and many office settings. As such, Business English is the kind of English typically used in, for example business meetings, sales presentations, negotiations, business correspondence, business reports, executive summaries. The purpose of learning Business English is to equip and establish the nature of professionalism to communicate in English effectively. 

The development of the world Information Technology nowadays is growing rapidly.  This happens because the strength of the era globalization in which computers and the internet dominate a wide range of human activities. One of the technologies are evolving rapidly in 2018 is machine learning. According to Garry Briscoea and Terry Caelli in his book which is entitled “a Compendium Of Machine Learning”, Machine Learning is a relatively new branch of artificial intelligence. The field has undergone a significant period of growth in the 1990s, with many new areas of research and development being explored. Machine Learning also provides the ability to learn and learn from experience without being explicitly programmed. It focuses on the development of computer programs that can access data and use it learn for themselves.

With the presence of this new technology, indicates that the existence of progress such as the emergence of new jobs, new business models, and new industries. According to Oracle, Machine Learning technologies will become the most important technology after the internet. It is estimated that this technology can be facilitate and make the work more effective and efficient. Whereas according to D'Avolio, the ultimate goal, Machine Learning is for the industry to view AI and Machine Learning of the US just another analysis tool to be used alongside the statistics and data queries. Reaching this point, however, IT will require its teams to quell the hype and improve understanding within their own systems.

Beside that, Machine Learning is also available in the software such as smartphone, in the car, or in some other advanced devices. The existence of Machine Learning in some software, like in smartphone, it can facilitate people to access information that would produce a better decisions, more quickly, and efficiently. In addition to the software, Machine Learning can be used in “Diagnosing Myocardial In Diagnosing Myocardial Infarction in Patients With Chest Pain”, Researchers have found that Machine Learning can improve the sensitivity and specificity of diagnosis of myocardial infarction (MI) in patients with chest pain who present at emergency departments (EDs). In other words, It can be said that the Machine Learning improves prediction of MI in patients presenting with chest pain in the ED. Its potential role as a decision support should be further studied. (Cardiology Advisor, March 12, 2018).

Machine Learning can also be utilized in business as reported by in information-age.com on March 5, 2018, saying that “Machine Learning is changing the face of business communications”, In recent years, this mindset has changed. Now, in the era of digital transformation, it is believed an organisation's biggest asset is not its people, but rather its data. Data is what shapes products and services, improves customer experiences, and ultimately defines brands. To downplay the role of people, is to fundamentally misunderstand the way that businesses work and the way that ideas are well-formed collaboratively. The fact is that tomorrow's organisations will be defined by both people and data. According in the Forbes on March 14, 2018, that Identity as the key to better security, because security could be part of strategy to discover and lock out bad actors. Centrify’s solution is an excellent example of how machine learning can improve the efficacy and experience for security administrators and employees.

In my opinion, with the presence of a new technology i.e. Machine Learning in an era of digitization is beneficial for people in the whole of life, such as business, medicine, security and many more. Machine Learning is useful in changing patterns of life and habits in working for the better, because the technology of machine Learning is capable of assisting humans in adding a broader insight as well as helping all activities human activities become more effective and efficient.

Application of maching learning can also be helpful in making smarter decision and able to predict for supporting result of decision that would be useful as a solution in handling problems such as that offered in the Cardiology Advisor on March, 12, 2018 “Diagnosing Myocardial In Diagnosing Myocardial Infarction in Patients With Chest Pain”, and in the Information-age.com on March, 5, 2018 “Machine Larning is changing the face of business communication”, as well as in the Forbes on March, 14, 2018 “Machine Learning is used as a new Weapon in your security Arsenal”. Therefore, I strongly agree thet the emergence of this new Technology. I agree that Machine Learning is able to be solutions in business, medicine, security, as well as other and reducing the time to predict an accurate and reliable decisions, as well as provide long-term strategic value in an decisions. Therefore, it is true that Oracle offered in Liputan6.com that is "Machine Learning that would be Prima donna in the future”.

1.2       BASIC THEORY

A.  PRONOUNS 
           A pronouns is a word that takes the place of a noun. Pronouns are used in place of a noun that has already been mentioned or that is already known, often to avoid repeating the noun. Pronouns are used so that our language is not cumbersome with the same nouns being repeated over and over in a paragraph. 

KINDS OF PRONOUNS

1.      PERSONAL PRONOUNS

SINGULAR				PLURAL
	subjective	Objective	possessive	subjective	objective	Possessive
1st person	I	Me	my, mine	we	us	our, ours
2nd person	you	You	your, yours	you	you	your, yours
3rd person	he she it	Him her it	his her,  hers its	they	them	their, theirs

  

Personal Pronouns have the following characteristics

1.      Persons (points of view)

• 1st person - the one(s) speaking (I, me, my, mine, we, us, our, ours) 
• 2nd person - the one(s) spoken to (you, your, yours)  
• 3rd person - the one(s) spoken about (he, him, his, she, her, hers, it, its, they, their, theirs)

Examples:

2.   Genders  

• Feminine (she, her, hers) 
• Masculine (he, him, his) 
• Neuter (it, its, they, them, their, theirs) 

Examples:

3.     Numbers 

• Singular (I, me, my, mine, you, your, yours, he, him, his, she, her, hers, it, its) 
• Plural  (we, us, our, ours, you, your, yours, they, them, their, theirs) 

Examples:

4.     Cases

• Subjective (I, you, he, she, it, we, they)  
• Possessive (my, mine, your, yours, his, her, hers, our, ours, their, theirs) 
• Objective   (me, you, him, her, it, us, them)

Examples - Subjective Case

Examples - Possessive Case

Examples - Objective Case

 2.     DEMONSTRATIVE PRONOUNS

 

A.  Demonstrative pronouns can also be used as qualifiers

Example:   

She wanted that much money? (that describes the adjective much)

B.  Demonstrative pronouns can also be used as determiners

Example:

Hand me that hammer. (that describes the noun hammer)

3.     REFLEXIVE / INTENSIVE PRONOUNS
These pronouns can be used only to reflect or intensify a word already there in the sentence.

A.  Reflexive / intensive pronouns CANNOT REPLACE personal pronouns

Examples:

I saw myself in the mirror. (Myself is a reflexive pronoun. reflecting the pronoun I)

I’ll do it myself. (Myself is an intensive pronoun. Intensifying the pronoun I)

4.     INDEFINITE PRONOUNS

These pronouns do not point to any particular nouns, but refer to things or people in general. Some of them are: another, anybody, anyone, anything, each, either, enough, everybody, everyone, everything, little, much, neither, nobody, no one, nothing, one, other, somebody, someone, something.

Example:

Everyone is already here.

A.    Singular: 

One	Someone	Anyone	No one	Everyone
Each	Somebody	Anybody	Nobody	Everybody
(N)either	Something	Aything	Nothing	Everything

Examples:

Somebody is coming to dinner.

Neither of us believes a word Harry says.  

B.  Plural:  

Both

Several

Few

Many

Others

 

Examples:

Both are expected at the airport at the same time.

Several have suggested canceling the meeting.

C.  Singular with non-countables / Plural with countables:

Some

Any

None

All

Most

More

 

Examples:

Some of the dirt has become a permanent part of the rug.

Some of the trees have been weekened by the storm.

A.  Indefinite pronouns use apostrophes to indicate possessive case.

Examples:

The accident is nobody’s fault.

How all the roadwork affect one’s daily commute?

B.  Some indefinite pronouns may also be used as determiners

One, each, either, neither, some, any, one, all, both, few, several, many, most

Examples:

Note the differences:

Each person has a chance. (Each is a determiner describing person)

Each has a chance. (Each is an indefinite pronoun replacing a noun)

5.      INTERROGATIVE PRONOUNS

Interrogative pronouns produce information questions that require more than a “yes” or “no” answer. These pronouns are used to begin a question: who, whom, which, what, whoever, whomever, whichever, and whatever.

Who

Whose

Whom

Which

What

Examples:

What do you want?

Who is there?

6.      RELATIVE PRONOUNS

These pronouns are used to connect a clause or phrase to a noun or pronoun. These are: who, whom, which, whoever, whomever, whichever, and that.

Who

Whom

Which

That

Whoever

Whomever

Whichever

A.  Relative pronouns introduce relative (adjectival) clauses.

Note:

Use who, whom, and whose to refer to people.

Use that and which to refer to things.

1.3       ANALYSIS               

A.        Paragraph 1

The term Business English can cover a multitude of things. Business English is the type of English used in business contexts, such as international trade, commerce, finance, insurance, banking, and many^[1] office settings. As such, Business English is the kind of English typically used in, for example business meetings, sales presentations, negotiations, business correspondence, business reports, executive summaries. The purpose of learning Business English is to equip and establish the nature of professionalism to communicate in English effectively. 

Analysis Pronoun

1.      Many, as Indefinite Pronouns Plural Determiners

B.        Paragraph 2

The development of the world Technology Information nowadays is growing rapidly.  This^[2] happens because the strength of the era globalization in which^[3] computers and the internet dominate a wide range of human activities. One of the technologies are evolving rapidly in 2018 is machine learning. According to Garry Briscoea and Terry Caelli in his^[4] book which^[5] is entitled “a Compendium Of Machine Learning”, Machine Learning is a relatively new branch of artificial intelligence. The field has undergone a significant period of growth in the 1990s, with many^[6] new areas of research and development being explored. Machine Learning also provides the ability to learn and learn from experience without being explicitly programmed. It^[7] focuses on the development of computer programs that^[8] can access data and use it^[9] learn for themselves.

Analysis Pronoun

2. This, as Demonstrative Pronouns Singular (near) (This describes the noun The development of the world Technology Information).

3.      Which, as Relative Pronouns.

4.      His book, as Personal Subjective Pronouns Singular 3rd person.

5.      Which, as Relative Pronouns.

6.      Many, as Indefinite Pronouns Plural Determiners.

7.      It, as Personal Subjective Pronouns Singular 3rd Neuter.

8.      That, as Relative Pronouns.

9.      It, as Personal Objective Pronouns Singular 3rd Neuter.

C.        Paragraph 3

With the presence of this^[10] new technology, indicates that^[11] the existence of progress such as the emergence of new jobs, new business models, and new industries. According to Oracle, Machine Learning technologies will become the most^[12] important technology after the internet. It^[13] is estimated that^[14] this^[15] technology can facilitate and make the work more^[16] effective and efficient. Whereas^[17] according to D'Avolio, the ultimate goal, Machine Learning is for the industry to view AI and Machine Learning of the US just another analysis tool to be used alongside the statistics and data queries. Reaching this^[18] point, however, IT will require its^[19] teams to quell the hype and improve understanding within their^[20] own systems.

Analysis Pronoun

10.  This, as Demonstrative Pronouns Singular (near) (This describes the noun New Technology).

11.  That, as Relative Pronouns.

12.  Most, as Indefinite Pronouns Singular with non-countables / Plural with countables Determiners

13.  It, as Personal Subjective Pronouns Singular 3rd Neuter.

14.  That, as Relative Pronouns.

15.  This, as Demonstrative Pronouns Singular (near) (This describes the noun Technology).

16.  More, as Indefinite Pronouns Singular with non-countables / Plural with countables

17.  Whereas, as Demonstrative Pronouns

18.  Its, as Personal Pronouns possessive Adjective 3rd Prular Neuter.

19.  This, as Demonstrative Pronouns Singular (near) (This describes the noun point).

20.  Their, as Personal Pronouns Possesive Adjective 3rd Prular

D.        Paragraph 4

Beside that^[21], Machine Learning is also available in the software such as smartphone, in the car, or in some^[22] other advanced devices. The existence of Machine Learning in some^[23] software, like in smartphone, it^[24] can facilitate people to access information that^[25] would produce a better decisions, more^[26] quickly, and efficiently. In addition to the software, Machine Learning can be used in “Diagnosing Myocardial In Diagnosing Myocardial Infarction in Patients With Chest Pain”, Researchers have found that^[27] Machine Learning can improve the sensitivity and specificity diagnosis of myocardial infarction (MI) in patients with chest pain who^[28] present at emergency departments (EDs). In other^[29] words, it^[30] can be said that^[31] the Machine Learning improves prediction of MI in patients presenting with chest pain in the ED. Its^[32] potential role as a decision support should be further studied. (Cardiology Advisor, March 12, 2018).

Analysis Pronoun

21. That, as Demonstrative Pronouns Singular

22. Some, as Singular with non-countables / Plural with countables

23. Some, as Singular with non-countables / Plural with countables

24. It, as Personal Subjective Pronouns Singular 3rd Neuter.

25. That, as Relative Pronouns.

26. More, as Indefinite Pronouns Singular with non-countables / Plural with countables

27. That, as Relative Pronouns.

28. Who, as Relative Pronouns.

29. Other, as Indefinite Pronouns Singular

30. It, as Personal Subjective Pronouns Singular 3rd Neuter.

31. That, as Relative Pronouns.

32. Its, as Personal Pronouns possessive Adjective 3rd Prular Neuter.

E.        Paragraph 5

Machine Learning can also be utilized in business as reported by in information-age.com on March 5, 2018, saying that^[33] “Machine Learning is changing the face of business communications”, In recent years, this^[34] mindset has changed. Now, in the era of digital transformation, it^[35] is believed an organisation's biggest asset is not its^[36] people, but rather its^[37] data. Data is what^[38] shapes products and services, improves customer experiences, and ultimately defines brands. To downplay the role of people, is to fundamentally misunderstand the way that^[39] businesses work and the way that^[40] ideas are well-formed collaboratively. The fact is that^[41] tomorrow's organisations will be defined by both people and data. According in the Forbes on March 14, 2018, that^[42] Identity as the key to better security, because security could be part of strategy to discover and lock out bad actors. Centrify’s solution is an excellent example of how machine learning can improve the efficacy and experience for security administrators and employees.

Analysis Pronoun

33.  That, as Relative Pronouns.

34.  This, as Demonstrative Pronouns Singular (near) (This describes the noun Mindset).

35.  It, as Personal Subjective Pronouns Singular 3rd Neuter.

36.  Its, as Personal Pronouns possessive Adjective 3rd Prular Neuter.

37.  Its, as Personal Pronouns possessive Adjective 3rd Prular Neuter.

38.  Who, as Relative Pronouns.

39.  That, as Relative Pronouns.

40.  That, as Relative Pronouns.

41.  That, as Relative Pronouns.

42.  That, as Relative Pronouns.

F.         Paragraph 6

In my^[43] opinion, with the presence of a new technology i.e. Machine Learning in an era of digitization is beneficial for people in the whole of life, such as business, medicine, security and many^[44] more^[45]. Machine Learning is useful in changing patterns of life and habits in working for the better, because the technology of machine Learning is capable of assisting humans in adding a broader insight as well as helping all activities human activities become more^[46] effective and efficient.

Analysis Pronoun

43.  My, as Personal Pronouns Possessive Singular 1st Person.

44.  Many, as Indefinite Pronouns Plural Determiners

45.  More, as Indefinite Pronouns Singular with non-countables / Plural with countables

46.  More, as Indefinite Pronouns Singular with non-countables / Plural with countables

G.        Paragraph 7

Application of maching learning can also be helpful in making smarter decision and able to predict for supporting result of decision that^[47] would be useful as a solution in handling problems such as that^[48] offered in the Cardiology Advisor on March, 12, 2018 “Diagnosing Myocardial In Diagnosing Myocardial Infarction in Patients With Chest Pain”, and in the Information-age.com on March, 5, 2018 “Machine Larning is changing the face of business communication”, as well as in the Forbes on March, 14, 2018 “Machine Learning is used as a new Weapon in your security Arsenal”. Therefore, I^[49] strongly agree thet the emergence of this^[50] new Technology. I^[51] agree that^[52] Machine Learning is able to be solutions in business, medicine, security, as well as other^[53] and reducing the time to predict an accurate and reliable decisions, as well as provide long-term strategic value in an decisions. Therefore, it^[54] is true that^[55] Oracle offered in Liputan6.com that^[56] is Machine Learning would be Prima donna in the future”.

Analysis Pronoun

47.  That, as Relative Pronouns.

48.  That, as Relative Pronouns.

49.  I, as Personal Subjective Pronouns Singular 1st Person.

50.  This, as Demonstrative Pronouns Singular (near) (This describes the New Technology).

51.  I, as Personal Subjective Pronouns Singular 1st Person.

52.  That, as Relative Pronouns.

53.  Other, as Indefinite Pronouns Singular

54.  It, as Personal Subjective Pronouns Singular 3rd Neuter.

55.  That, as Relative Pronouns.

56.  That, as Relative Pronouns.

 

1.4       CONCLUSION

Machine Learning is beneficial for people in the whole of life, such as business, medicine, security and many more. Machine Learning is also useful in changing patterns of life and habits in working for the better, because the technology of Machine Learning is capable of assisting humans in adding a broader insight as well as helping all human activities become more effective and efficient. From the results of the analysis of the pronoun against the background of the above Machine Learning, it can be concluded that there are 6 types of pronouns include Personal Pronouns, Demonstrative Pronouns, Reflexive/Intensive Pronouns, Indefinitie Pronouns, Interrogrative Pronouns, and Relative Pronouns, but used only 4 i.e Personal Pronouns, Demonstrative Pronouns, Indefinitie Pronouns, and Relative Pronouns. Because of the pronouns it will make uncomplicated and unrepeated sentences.

1.5      SOURCE      

NEWS

1. https://www.thecardiologyadvisor.com/acc-2018-meeting-highlights/machine-learning-techniques-diagnosis-mi-acute-stable-ischemic-heart/article/749780/ 
2. http://www.information-age.com/machine-learning-business-communication-123471014/ 
3. https://www.forbes.com/forbes/welcome/?toURL=https://www.forbes.com/sites/maribellopez/2018/03/14/machine-learning-a-new-weapon-in-your-security-arsenal/&refURL=https://www.google.com/&referrer=https://www.google.com/ 
4. http://tekno.liputan6.com/read/3216467/oracle-teknologi-machine-learning-jadi-primadona-di-2018

BASIC THEORY

1. https://www.ef.com/english-resources/english-grammar/pronouns/ 
2. https://webapps.towson.edu/ows/pronouns.htm 
3. https://en.oxforddictionaries.com/grammar/pronouns