BUSINESS LETTER

A business letter is a letter written in formal language, usually used when writing from one business organization to another, or for correspondence between such organizations and their customers, clients and other external parties. The overall style of letter will depend on the relationship between the parties concerned. There are many reasons to write a business letter. It could be to request direct information or action from another party, to order supplies from a supplier, to identify a mistake that was committed, to reply directly to a request, to apologize for a wrong or simply to convey goodwill. Even today, the business letter is still very useful because it produces a permanent record, is confidential, formal and delivers persuasive, well-considered messages.

Components of business letter :

1.          The Heading
2.           The Inside Address
3.           The Greeting
4.           The Body
5.           The Complimentary Close
6.           The Signature Line
7.           The Subject Line

The Differences of Full block and Semi block Style:

-          Full Block

Block format features all elements of the letter aligned to the left margin of the page. It has a neat and simple appearance. Paragraphs are separated by a double line space.

-          Semi Block Style

Semi-block (also called a modified block) style business letter is justified at the left margin with the exception of the return address (if not using letterhead), the reference line, and your closing, signature, and printed name. These are tabbed about one third to the right of the page.

Examples of full block style and semi block style

a. Semi Block Style

b. Full Block Style

http://www.oxforddictionaries.com/us/words/letter-formats-block-modified-block-and-semi-block-american

wawanoutsider.wordpress.com/2012/10/24/definition-business-letter/

16 Tenses with Example

Tenses is a form of the verb which indicates the occurrence of an event. Whereas in the Oxford Dictionary, tenses mean changes in verb that affect the timing and occurrence of events.

e.g.:

We Studied English yesterday

We will study English Tomorrow

            Verb                Time signal     

Tense by the time it happened there were four:

-          Present

-          Past

-          Future

-          Past future

Based on the character of the events :

-          Simple

-          Continuous

-          Perfect

-          Perfect Continuous

When combined, overall there are 16 tenses :

1. Simple Present

Formula:

(+) S + V1 s/es + O

(-) S + do/does not + V1 + O

(?) Do/Does + S + V1+ ?

Example Of Sentences:

(+) They study English at Locus English Course.

(-)  They don’t study English at Locus English Course.

(?)  Do they study English at Locus English Course?

Use for:

Always

Every day

Every years

Sometimes

Often

Seldom

Usually

2. Present Continuous

Formula:

(+) S + to be + V-ing + O

(-) S + to be + not + V-ing + O

(?) To be + S + V-ing + O+ ?

Example Of Sentences:

(+) I am reading a novel.

(-)  I am not reading a novel.

(?) Are you reading novel?

Use for:

Today

Now

Right now

At the moment

3. Present Perfect

Formula:

(+) S + Have/Has + V3 + O

(-) S + Have/Has + not + V3 + O

(?) have/has + S + V3 + O + ?

Example Of Sentences:

(+) You have written a letter.

(-)  You have not written a letter.

(?) Have you written a letter?

Use for:

Already

Just now

4. Present Perfect Continuous

Formula:

(+)  S + have/has + been + V-ing+ O

(-) S + have/ has + not + been + V-ing

(?) Have/has + S + been + V-ing + O + ?

Example Of Sentences:

(+) Ben and Parker have been doing their homework.

(-)  Ben and Parker have not been doing their homework.

(?) Have Ben and Parker been doing their homework?

Use for:

For

Since

5. Simple Past

Formula:

(+) S + V2 + O

(-) S + did + not + V1 + O

(?) Did + S + V1 + O + ?

Example Of Sentences:

(+) They played football yesterday.

(-)  They didn’t play football yesterday.

(?) Did they play football yesterday?

Use for:

Yesterday

Last

Ago

6. Past Continuous

Formula:

(+) S + to be 2 (was/were) + V-ing + O

(-) S + to be 2 (was/were) + not + V-ing + O

(?)to be 2 (was/were) + S + V-ing + O + ?

Example Of Sentences:

(+) I was waiting for a bus.

(-)  I was not waiting for a bus.

(?) Were you waiting for a bus?

Use for:

When

While

7. Past Perfect

Formula:

(+) S + had + V3 + O

(-) S + had + not + V3 + O

(?) Had + S + V3 + O + ?

Example Of Sentences:

(+) Baim had done the test.

(-) Baim had not done the test.

(?) Had Baim done the test?

Use for:

Since

For

8. Past Perfect Continuous

Formula:

(+) S + had + been + V-ing + O

(-)  S + had + not + been + V-ing + O

(?) Had + S + been + V-ing + O + ?

Example Of Sentences:

(+) Maria’s sister had been studying at university for eight years.

(-)  Maria’s sister had not been studying at university for eight years.

(?) Had Maria’s sister been studying at university for eight years?

Use for:

When

9. Simple Future

Formula:

(+) S + Will/Shall + V1 + O

(-) S + Will/Shall + not + V1 + O

(?) Will/Shall + S + V1 + O + ?

Example Of Sentences:

(+) We will play futsal.

(-)  We won’t play futsal.

(?) Will we play futsal?

Use for:

If

While

Before

After

As soon as

Till

Until

10. Future Continuous

Formula:

(+) S + will/shall + be + V-ing + O

(-) S + will/shall + not + be + V-ing + O

(?) Will/Shall + S + be + V-ing + O+ ?

Example Of Sentences:

(+) I will/shall be having dinner at 19.00

(-)  I won’t/shan’t be having dinner at 19.00

(?) Will you be having dinner at 19.00?

Use for:

At this time tomorrow

At the same time tomorrow

At this time next year

11. Future Perfect

Formula:

(+) S + Will/Shall + Have + V3 + O

(-) S + will/shall + not + have + V3 + O

(?) Will/Shall + S + have + V3 + O + ?

Example Of Sentences:

(+) I will/shall have finished dinner by 20.00

(-) I won’t/shan’t have finished dinner by 20.00

(?) will you have finished dinner by 20.00?

Use for:

By the end of this week

By next week

12. Future perfect continuous

Formula:

(+) S + Will/Shall + Have + Been + V-ing + O

(-) S + will/shall + not + have + been + V-ing + O

(?) Will/Shall + S + have + been + V-ing + O +  ?

Example Of Sentences:

(+) She will have been working here.

(-) She won’t have been working here.

(?) Will she have been working here?

Use for:

By the end of ….

By the end of this year

13. Simple Past Future

Formula:

(+) S + Would/Should + V1 + O

(-) S + Would/Should + Not + V1 + O

(?) Would/Should + S + V1 + O + ?

Example Of Sentences:

(+) You would play tennis.

(-) You wouldn’t play tennis.

(?) Would you play tennis?

Use for:

… if …..

14. Past Future Continuous

Formula:

(+) S + Would/Should + Be + V-ing + O

(-) S + Would/Should + Not + Be + V-ing + O

(?) Would/Should + S + Be + V-ing + O + ?

Example Of Sentences:

(+) I would/should be playing my rent.

(-) I wouldn’t/should’t be playing my rent.

(?) Would you be playing my rent?

Use for:

In January last year

At nine o’clock yesterday

15. Past Future Perfect

Formula:

(+) S + Would/Should + Have + V3 + O

(-) S + Would/Should+ Not + Have + V3 + O

(?) Would/Should + S + Have + V3 + O + ?

Example Of Sentences:

(+) My boss would offered me much money.

(-) My boss wouldn’t have offered me much money.

(?) Would my boss have offered me much money?

Use for:

…. if…..

16. Past Future Perfect Continuous

Formula:

(+) S + Would/Should + Have + Been + V-ing + O

(-) S + Would/Should + Not + Have + Been + V-ing + O

(?) Would/Should + S + Have + Been + V-ing + O + ?

Example Of Sentences:

(+) She would have been watching the film.

(-)  She wouldn’t have been watching the film.

(?) Would she have ben watching the film?

Use for:

By the end of this month + past signal

Explain the differences between TOEFL and TOEIC

TOEFL

The TOEFL test is for people who want to study abroad in a language school or a university. The TOEFL test measures a person’s English ability for academic studies. Basically if you want to study at an ESL program abroad or would like to apply to enter a university or college you need to take the TOEFL test.

The TOEFL test on the other hand is focused on the university and academic worlds. So you could have to read someone's flyer looking for a new roommate or listen to a class lecture on ancient history.

examples of question:

1. Having been served lunch,....

    A. the problems were discussed by the participants.

    B. the participants discuss the problems.

    C. it was discussed by the participants.

    D. A discussion of the problems were made by the participants.

2. East Kalimantan relies heavily on income from oil and natural gas, and....

    A. Aceh province also.

    B. Aceh province too.

    C. Aceh province is as well.

    D. so does Aceh province.

TOEIC

The TOEIC test is for people who want to work in a job that uses English. The TOEIC test measures a person’s English ability in the workplace. So if you are applying for a job or trying to get a promotion this is the test you need to take. Many people also like to use the TOEIC test to better understand how well they can speak English. Even if you don't plan on working in a job where you need English you can still use this test to measure your English ability.

The content is very different between the TOEIC test versus the TOEFL. The TOEIC test is focused on business English so you will see topics ranging from contracts and marketing to eating out and buying a train ticket.

examples of question:

1.      .1. .........is no better season than winter to begin training at Fitness center.

A.    When

B.     It

C.     There

D.    As it

2.      2. The financial audit of Soft Peach Software …….completed on Wednesday by a certified accounting firm.

A.     To be

B.      Having been

C.      Was

D.     Were

www.goodwinenglish.com/toeic-vs-toefl

http://www.kursusmudahbahasainggris.com/2013/10/contoh-soal-toefl-structure-lengkap.html

Softskill Bahasa Inggris Bisnis

Assalamualaikum.wr.wb

Hello, My Name is Farhan Rifqi Mahatidana you can call me farhan. I come from South Tangerang and I was born in Tangerang. I live in Sukun street ciputat, South Tangerang. I am study in Gunadarma University faculty computer science.

My hobby listening music and playing computer. I think music is my best friend, because music always in my life. I never compare while the music still good in my ear, there are many genre that I like.

My favorite job is all about computer, because this is my hobby. And in the future I want to be a IT Profesional, Because the job is connected with computer and I enjoy it.

Farhan Rifqi Mahatidana

2KB07

Tugas Softskill

PENGANTAR STATISTIKA

DISTRIBUSI PROBABILITAS DISKRIT

Dosen :

Harjanto Sutedjo

Disusun oleh :

Farhan Rifqi Mahatidana :      23114962

Kelas :                                     2KB07     

      

UNIVERSITAS GUNADARMA

FAKULTAS ILMU KOMPUTER DAN TEKNOLOGI INFORMASI

SISTEM KOMPUTER

2015-2016

KATA PENGANTAR

Pertama penulis mengucapkan puji syukur atas kehadirat Tuhan Yang Maha Esa, atas segala kebesaran dan kelimpahan nikmat yang diberikan-Nya, sehingga penulis dapat menyelesaikan makalah Pengantar Statistika “Distribusi Probabilitas Diskrit”.

Penulis menyadari bahwa penulisan tugas  ini masih jauh dari sempurna, oleh karena itu kritik dan saran dari semua pihak yang bersifat membangun selalu penulis harapkan demi kesempurnaan penulisan  makalah ini.

Akhir kata, penulis sampaikan terima kasih kepada semua pihak yang telah berperan serta dalam penyusunan makalah  ini dari awal sampai akhir.

DAFTAR ISI

Kata Pengantar............................................................................................ 

Daftar Isi..................................................................................................... 

BAB I PENDAHULUAN

1.1    Pendahuluan......................................................................................... 

BAB II PEMBAHASAN

2.1 Distribusi Probabilitas Diskrit................................................................ 

2.2 Variabel Acak Diskrit............................................................................ 

2.3 Rata-Rata Distribusi Probabilitas........................................................... 

2.4 Variasi Standar dan Deviasi.................................................................. 

2.5 Distribusi Probabilitas Binominal.......................................................... 

2.6 Distribusi Probabilitas Hipergeometris.................................................. 

2.7 Distribusi Probabilitas Poisson............................................................... 

2.8 Distribusi Normal................................................................................... 

BAB III PENUTUP

3.1 Kesimpulan..........................................................................................

Daftar Pustaka .......................................................................................... 

BAB I

PENDAHULUAN

1.1  Pendahuluan

Statistik adalah ilmu yang mempelajari bagaimana merencanakan, mengumpulkan, menganalisis, menginterpresentasi, dan mempresentasikan data. Sedangkan statistik adalah data, informasi, atau hasil penerapan algoritma statistika pada suatu data. Kejadian yang sering atau jarang terjadi dikatakan mempunyai peluang terjadi yang besar atau kecil. Keseluruhan nilai-nilai peluang bisa digunakandalam kehidupan sehari-hari. Dalam mengaplikasikan statistika terhadap permasalahan sains, industri, atau sosial, pertama-tama dimulai dari mempelajari populasi. Tiga buah sebaran teoritis yang paling terkenal, diantaranya tiga buah sebaran yang diskrit dan sebaran yang kontinyu. Kedua sebaran yang teoritis yang deskrit itulah sebaran binomial dan sebaran possion. Sebaran kontinyunya adalah sebaran normal.

BAB II

PEMBAHASAN

2.1 Distribusi Probabilitas Diskrit

Definisi Umum

Distribusi probabilitas : Sebuah daftar berisi seluruh hasil dari suatu ekperimen dan probabilitas yang berkaitan dengan setiap hasil tersebut.

Contoh :

Misal kita tertarik terhadap munculnya “kepala” pada pelemparan koin sebanyak 3 kali. Hasil yang mungkin adalah : nol “kepala”, satu “kepala”, dua dan tiga “kepala”. Bagaimana distribusi probabilitas untuk munculnya “kepala “ ?

Jawab :

Terdapat 8 hasil yang mungkin :

Dua karakter penting distribusi probabilitas.

1. Probabilitas dari suatu hasil harus berada antara 0 dan 1

2. Jumlah dari seluruh probabilitas hasil harus sama dengan 1

Soal Pemahaman :

Hasil yang mungkin dari eksperimen pelemparan dadu, adalah : 1 titik, 2 titik, 3 titik, 4 titik, 5 titik dan 6 titik.

a. Buat distribusi probabilitas untuk hasil tersebut.

b. Gambarkan distribusi probabilitas dalam grafik.

c. Berapa jumlah probabilitasnya ?

2.2 Variabel Acak Diskrit

Varibel acak diskrit adalah variabel acak yang tidak mengambil seluruh nilai yang ada dalam sebuah interval atau variabel yang hanya memiliki nilai tertentu. Nilainya merupakan bilangan bulat dan asli, tidak berbentuk pecahan. Variabel acak diskrit jika digambarkan pada sebuah garis interval, akan berupa sederetan titik-titik yang terpisah.

Contoh :

1.      Banyaknya pemunculan sisi muka atau angka dalam pelemparan sebuah  koin (uang logam).

2.      Jumlah anak dalam sebuah keluarga.

2.3 Rata-Rata Distribusi Probabilitas

Rata-rata disebut juga nilai Ekspektasi ( ∑ ) (x) .

Rata-rata merupakan nilai khas yang digunakan untuk menggambarkan distribusi probabilitas

Rata-rata distribusi probabilitas :

μ=E(x)=∑[x.P(x)]

P (x) = Probabilitas variabel acak

X = variabel acak

2.4 Variasi Standar dan Deviasi

Variansi menggambarkan penyebaran dalam suatu distribusi.

Variansi distribusi probabilitas : σ^(2 )= ∑[(x-μ) ^(2 ) P (x)]

Standar Deviasi:SD= √(σ^2 )

2.5 Distribusi Probabilitas Binominal

Karakteristik distribusi binomial :

a. Hasil dari eksperimen hanya diklasifikasikan menjadi dua, yaitu : Sukses atau Gagal.

b. Variabel acaknya diperoleh dengan cara menghitung jumlah sukses dari suatu percobaan.

c. Probabilitas sukses akan selalu tetap selama percobaan.

d. Setiap percobaan independen, artinya hasil percobaan satu tidak mempengaruhi hasil per cobaan berikutnya

Untuk membentuk distribusi binomial, kita harus mengetahui :

a. Jumlah percobaan ( trial ).

b. Probabilitas sukses untuk setiap percobaan.

Distribusi Probabilitas Binomial : P(x)= n!/x!(n-x)! π^x.〖(1-π)〗^(n-x)

n = jumlah trial / percobaan

x = Jumlah sukses

π = probabilitas sukses untuk setiap percobaan

Beberapa catatan penting mengenai distribusiBinomial :

1. Bila n tetap, tetapi π meningkat dari 0,05 ke 0,95, bentuk distribusi akan berubah. Pada π 5,0 < , grafik miring ke kiri (positive skew), pada π 5,0 = grafik simetris, pada 5,0 > π grafik miring ke kanan (negative skew).

2. Bila π tetap, namun n meningkat, maka bentuk distribusi binomial semakin simetris.

3. Mean (μ) untuk distribusi binomial: μ = n . π

Variansi 〖(σ〗^2) untuk distribusi binomial :σ^(2 )=n .π (1-π)

2.6  Distribusi Probabilitas Hipergeometris

Syarat digunakannya distribusi hipergeometris :

a. Sampel diambil dari suatu populasi terbatas tanpa pengembalian

b. Jumlah sampel n lebih besar dari 5% dari jumlah seluruh populasi N Populasi terbatas (finite population) : suatu populasi yang terdiri dari sejumlah kecil individu, objek, atau pengukuran.

Distribusi Hipergeometri :P(x)= ((sCx)(n-sCn-x))/ΝCn

N = jumlah seluruh populasi

S = jumlah sukses dalam populasi

x = jumlah sukses yang diinginkan ( 0,1,2,3,……)

n = jumlah sampel atau jumlah percobaan / trial

C = Simbol untuk kombinasi

2.7  Distribusi Probabilitas Poisson

Distribusi ini sering disebut “Hukum kejadian yang tidak mungkin”, maksudnya distribusi ini dipakai pada kejadian dengan probabilitas π yang sangat kecil ( ≤ 0,05 ).

Distribusi ini memiliki banyak aplikasi diantaranya : menentukan distribusi kesalahan pada input data, cacat yang terjadi pada proses pengecatan sparepart mobil, jumlah kecelakaan yang terjadi pada Boeing 737 selama 3 bulan terakhir.

DistrbusiPoisson:

P(x)=(u^x.e^(-n))/x!

μ = rata-rata aritmatik dari sukses pada suatu interval waktu

e = konstanta (2,71828)

x = jumlah sukses

P(x) = probabilitas dari suatu x

2.8  Distribusi Normal

distribusi probabilitas Normal". Variabel acak kontinu diperoleh dengan cara mengukur sesuatu, seperti : berat badan, tinggi badan, usia pakai baterai dll.

Karakteristik dari distribusi probabilitas dan kurva normal adalah:

1.      Kurva berbentuk genta atau lonceng dan memiliki satu puncak yang terletak di tengah. Nilai rata-rata hitung (µ) = median (Md) = modus (Mo). Nilai µ = Md = Mo yang berada di tengah membelah kurva menjadi dua bagian yaitu setengah di bawah nilai µ = Md = Mo dan setengah di atas nilai µ = Md = Mo.

2.      Distribusi probabilitas dan kurva normal berbentuk kurva simetris dengan rata-rata hitungnya (µ).

3.      Distribusi probabilitas dan kurva normal bersifat asimptotis.

4.      Kurva mencapai puncak pada saat X = µ.

5.      Luas daerah di bawah kurva normal adalah 1; ½ di sisi kanan nilai tengah dan ½ di sisi kiri.

Jenis-Jenis Distribusi Probabilitas Normal :

1.      Distribusi Probabilitas dan Kurva Normal dengan μ dan σ Berbeda

Bentuk distribusi probabilitas dan kurva normal dengan nilai tengah sama dan standar deviasi yang berbeda, adalah bentuk leptokurtic, platykurtik dan mesokurtik. Kurva normal tersebut mempunyai μ = Md = Mo yang sama, namun mempunyai σ berbeda. Semakin besar σ, maka kurva semakin pendek dan semakin tinggi nilai σ, maka semakin runcing. Oleh sebab itu, σ tinggi cenderung menjadi platykurtik dan σ rendah menjadi leptokurtik. Nilai σ yang tinggi menunjukkan bahwa nilai data semakin menyebar dari nilai tengahnya (μ). Apabila σ rendah, maka nilai semakin mengelompok pada nilai tengahnya.

2.      Distribusi Probabilitas dan Kurva Normal dengan μ Berbeda dan σ Sama

Bentuk distribusi probabilitas dan kurva normal dengan μ berbeda dan σ sama mempunyai jarak antara kurva yang berbeda, namun bentuk kurva tetap sama. Hal demikian bisa terjadi karena kemampuan antar populasi berbeda, namun setiap populasi mempunyai keragaman yang hampir sama.

3.      Distribusi Probabilitas dan Kurva Normal dengan μ dan σ Berbeda

Distribusi kurva normal dengan μ dan σ berbeda. Kurva ini mempunyai titik pusat yang berbeda pada sumbu mendatar dan bentuk kurva berbeda karena mempunyai standar deviasi yang berbeda.

  

BAB III

KESIMPULAN

3.1 Kesimpulan

Kesimpulan yang didapat dari makalah ini adalah :

Berdasarkan deskripsi pendahuluan dan pembahasan yang telah diuraikan sebelumnya, maka pada bagian penutup ini dapat ditarik kesimpulan bahwa :

Distribusi probabilitas merupakan Sebuah daftar berisi seluruh hasil dari suatu ekperimen dan probabilitas yang berkaitan dengan setiap hasil tersebut.

Variabel acak merupakan Variabel yang digunakan untuk memberikan nilai – nilai yang berbeda untuk setiap hasil dari suatu eksperimen.

DAFTAR PUSTAKA

https://vebrianaparmita.wordpress.com/2013/11/10/bab-viii-distribusi-probabilitas-dan-kurva-normal/

http://dedenstatistics.blogspot.co.id/2012/12/variabel-acak-random-variable.html

http://santrimbelink.blogspot.co.id/2012/07/distribusi-probabilitas-diskrit-dan.html