Programing Sains Data 1

1 Calculation of Bonuses for Each Employee

💰

PRACTICUM 2.5

Employee Bonus Calculation
with R

📊

Employee Dataset

ID	Name	Age	Salary	Position	Performance
1	Bagas	25	$5,000	Staff	Good
2	Joan	30	$7,000	Supervisor	Very Good
3	Alya	27	$6,500	Staff	Average
4	Dwi	35	$10,000	Manager	Good
5	Nabil	40	$12,000	Director	Very Good

📋 Bonus Rules

Very Good

20%

Good

10%

Average

📟

R Program Code

📌 R Script - Bonus Calculation RUN

# Create employee data frame
employees <- data.frame(
  ID = c(1, 2, 3, 4, 5),
  Name = c("Bagas", "Joan", "Alya", "Dwi", "Nabil"),
  Age = c(25, 30, 27, 35, 40),
  Salary = c(5000, 7000, 6500, 10000, 12000),
  Position = c("Staff", "Supervisor", "Staff", "Manager", "Director"),
  Performance = c("Good", "Very Good", "Average", "Good", "Very Good"),
  stringsAsFactors = FALSE
)

# Calculate bonus based on performance
for (i in 1:nrow(employees)) {
  performance <- employees$Performance[i]
  salary <- employees$Salary[i]
  bonus <- 0
  
  if (performance == "Very Good") {
    bonus <- 0.2 * salary
  } else if (performance == "Good") {
    bonus <- 0.1 * salary
  } else if (performance == "Average") {
    bonus <- 0.05 * salary
  }
  
  # Display results
  cat(paste0("Name: ", employees$Name[i], ", Bonus: $", bonus, "\n"))
}

📈

Bonus Calculation Results

👤

Bagas

$500

Good (10%)

👤

Joan

$1,400

Very Good (20%)

👤

Alya

$325

Average (5%)

👤

Dwi

$1,000

Good (10%)

👤

Nabil

$2,400

Very Good (20%)

#RProgramming #EmployeeBonus #DataScience #Practicum25

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2 Loops For dan While

🔁

PRACTICUM 2.5.3

Loops (For & While)
with R

📊

Employee Dataset

ID	Name	Age	Salary	Position	Performance
1	Bagas	25	$5,000	Staff	Good
2	Joan	30	$7,000	Supervisor	Very Good
3	Alya	27	$6,500	Staff	Average
4	Dwi	35	$10,000	Manager	Good
5	Nabil	40	$12,000	Director	Very Good

📋 Task Requirements

FOR Loop

Display employees with salary > 6000

WHILE Loop

Display employees until “Manager” is found

📟

R Program Code — FOR Loop

📌 R Script — FOR Loop (Salary > 6000) RUN

# Create employee data frame
employees <- data.frame(
  ID          = c(1, 2, 3, 4, 5),
  Name        = c("Bagas", "Joan", "Alya", "Dwi", "Nabil"),
  Age         = c(25, 30, 27, 35, 40),
  Salary      = c(5000, 7000, 6500, 10000, 12000),
  Position    = c("Staff", "Supervisor", "Staff", "Manager", "Director"),
  Performance = c("Good", "Very Good", "Average", "Good", "Very Good"),
  stringsAsFactors = FALSE
)

# FOR loop — display employees with salary > 6000
for (i in 1:nrow(employees)) {
  if (employees$Salary[i] > 6000) {
    cat(paste0("Name: ", employees$Name[i],
            ", Salary: ", employees$Salary[i], "\n"))
  }
}

📈

FOR Loop Results

👤

Joan

$7,000

Supervisor

👤

Alya

$6,500

Staff

👤

Dwi

$10,000

Manager

👤

Nabil

$12,000

Director

📟

R Program Code — WHILE Loop

📌 R Script — WHILE Loop (Until Manager Found) RUN

# WHILE loop — display employees until "Manager" is found
i <- 1
while (i <= nrow(employees)) {
  if (employees$Position[i] == "Manager") {
    cat(paste0("Name: ", employees$Name[i],
            ", Position: ", employees$Position[i],
            " (Stop here)\n"))
    break
  } else {
    cat(paste0("Name: ", employees$Name[i],
            ", Position: ", employees$Position[i], "\n"))
  }
  i <- i + 1
}

📈

WHILE Loop Results

👤

Bagas

Staff

✓ Continue

👤

Joan

Supervisor

✓ Continue

👤

Alya

Staff

✓ Continue

🛑

Dwi

Manager

Stop here!

💡

Code Explanation

🔵 FOR Loop — Display Employees with Salary > 6000

STEP 1 — DATA SETUP

employees
<- data.frame(…)

A data frame is created with 5 employees, storing ID, Name, Age, Salary, Position, and Performance.

stringsAsFactors
= FALSE

keeps text columns as plain strings.

STEP 2 — LOOP ITERATION

for
(i in 1:nrow(employees))

Iterates from row 1 to the total number of rows using nrow(). Every employee is checked on every iteration — no rows are skipped.

STEP 3 — CONDITION CHECK

if
(employees$Salary[i] > 6000)

Filters only rows where Salary exceeds 6000. Bagas ($5,000) is skipped; Joan, Alya, Dwi, and Nabil pass the condition and are printed.

STEP 4 — OUTPUT

cat(paste0(“Name:”,
…, “, Salary:”, …))

paste0() combines text and values without spaces. cat() prints the result to the console with a newline .

🟡 WHILE Loop — Display Employees Until “Manager” Found

STEP 1 — INDEX INIT

i
<- 1

Unlike the FOR loop, the WHILE loop uses a manual index starting at 1 (R is 1-indexed). This index is used to access each row of the data frame.

STEP 2 — LOOP CONDITION

while
(i <= nrow(employees))

The loop runs as long as i does not exceed the total rows. This prevents an out-of-bounds error if “Manager” is never found.

STEP 3 — STOP CONDITION

if
(employees$Position[i] == “Manager”) { break }

When Position equals “Manager” (row 4 = Dwi), the employee is printed with “(Stop here)” and break exits the loop immediately.

STEP 4 — INCREMENT

i
<- i + 1

The index is manually incremented at the end of each iteration. Without this, the loop would run forever (infinite loop) on the same row.

#RProgramming #ForLoop #WhileLoop #Practicum253

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2.1 Loops break and continue

⚡

PRACTICUM 2.5.4

Break & Continue (Next)
with R

📊

Employee Dataset

ID	Name	Age	Salary	Position	Performance
1	Bagas	25	$5,000	Staff	Good
2	Joan	30	$7,000	Supervisor	Very Good
3	Alya	27	$6,500	Staff	Average
4	Dwi	35	$10,000	Manager	Good
5	Nabil	40	$12,000	Director	Very Good

📋 Task Requirements

BREAK

Stop the loop when salary > 10,000 is found

NEXT (continue)

Skip employees with “Average” performance

📟

R Program Code — BREAK

📌 R Script — Stop loop when Salary > 10,000 RUN

# Create employee data frame
employees <- data.frame(
  ID          = c(1, 2, 3, 4, 5),
  Name        = c("Bagas", "Joan", "Alya", "Dwi", "Nabil"),
  Age         = c(25, 30, 27, 35, 40),
  Salary      = c(5000, 7000, 6500, 10000, 12000),
  Position    = c("Staff", "Supervisor", "Staff", "Manager", "Director"),
  Performance = c("Good", "Very Good", "Average", "Good", "Very Good"),
  stringsAsFactors = FALSE
)

# Use break to stop when salary above 10,000 is found
for (i in 1:nrow(employees)) {
  if (employees$Salary[i] > 10000) {
    cat(paste0("(Stopped because ", employees$Name[i],
            " has a salary above 10,000)\n"))
    break
  }
  cat(paste0("Name: ", employees$Name[i],
          ", Salary: ", employees$Salary[i], "\n"))
}

📈

BREAK Results

👤

Bagas

$5,000

✓ Printed

👤

Joan

$7,000

✓ Printed

👤

Alya

$6,500

✓ Printed

👤

Dwi

$10,000

✓ Printed

🛑

Nabil

$12,000

break!

Name: Bagas, Salary: 5000

Name: Joan, Salary: 7000

Name: Alya, Salary: 6500

Name: Dwi, Salary: 10000

(Stopped because Nabil has a salary above 10,000)

💡

Code Explanation — BREAK

HOW BREAK WORKS

if
(Salary > 10000) { break }

The loop checks each employee’s salary. When Nabil’s salary ($12,000) exceeds 10,000, break immediately exits the loop — no further rows are processed.

PRINT ORDER

cat(…)
is called BEFORE the if-break check

The if block is checked first. If salary > 10,000 → print stop message and break. Otherwise → print the employee’s name and salary normally.

📟

R Program Code — NEXT (continue)

📌 R Script — Skip employees with “Average” performance RUN

# Use next to skip employees with "Average" performance
for (i in 1:nrow(employees)) {
  if (employees$Performance[i] == "Average") {
    next
  }
  cat(paste0("Name: ", employees$Name[i],
          ", Performance: ", employees$Performance[i], "\n"))
}
cat('(Alya is skipped because the performance is "Average")\n')

📈

NEXT Results

👤

Bagas

Good

✓ Printed

👤

Joan

Very Good

✓ Printed

⏭️

Alya

Average

next! skipped

👤

Dwi

Good

✓ Printed

👤

Nabil

Very Good

✓ Printed

Name: Bagas, Performance: Good

Name: Joan, Performance: Very Good

Name: Dwi, Performance: Good

Name: Nabil, Performance: Very Good

(Alya is skipped because the performance is “Average”)

💡

Code Explanation — NEXT

HOW NEXT WORKS

if
(Performance == “Average”) { next }

next skips the rest of the current iteration and jumps to the next row. Unlike break, the loop continues — only Alya is skipped.

BREAK vs NEXT

break
→ exits the entire loop

next
→ skips current row only

Alya (row 3, “Average”) triggers next, so her row is not printed. Rows 4 (Dwi) and 5 (Nabil) are still processed normally.

#RProgramming #BreakNext #LoopControl #Practicum254

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Programing Sains Data 1