Prakticum Week ~ 4

Sintaks dan Alur Kontrol

Institut Teknologi Sains Bandung Program Studi Data Science

🟢 Available for collaboration

Hi, I'm Risky

Data Science Student

I turn raw numbers into meaningful insights through statistical modeling and data analysis. Passionate about R programming and machine learning, I make complex data easy to understand.

📍 Samarinda, Indonesia · 🏫 ITSB · NIM 52250030

1 Dataset

This lab uses a sample dataset of employees as practice data for analyzing using conditional statements and loops.

library(readxl)
library(knitr)

dataset <- read_excel("dataset.xlsx")
kable(dataset, caption = "Sample Employee Dataset")

Sample Employee Dataset
ID	Name	Age	Salary	Position	Performance
1	Bagas	25	5000	Staff	Good
2	Joan	30	7000	Supervisor	Very Good
3	Alya	27	6500	Staff	Average
4	Dwi	35	10000	Manager	Good
5	Nabil	40	12000	Director	Very Good

2 Conditional Statement

This section uses a conditional statement to determine the employee bonus based on their performance level.

Determine the bonus amount based on employee performance:

Very Good \(\rightarrow\) 20% of salary
Good \(\rightarrow\) 10% of salary
Average \(\rightarrow\) 5% of salary

library(knitr)

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 <- function(salary, performance) {
  if (performance == "Very Good") {
    salary * 0.20
  } else if (performance == "Good") {
    salary * 0.10
  } else {
    salary * 0.05
  }
}

employees$Bonus_Pct <- ifelse(
  employees$Performance == "Very Good", "20%",
  ifelse(employees$Performance == "Good", "10%", "5%")
)

employees$Bonus <- mapply(calculate_bonus, employees$Salary, employees$Performance)

for (i in seq_len(nrow(employees))) {
  cat(sprintf("Name: %s, Bonus: %g\n", employees$Name[i], employees$Bonus[i]))
}

## Name: Bagas, Bonus: 500
## Name: Joan, Bonus: 1400
## Name: Alya, Bonus: 325
## Name: Dwi, Bonus: 1000
## Name: Nabil, Bonus: 2400

2.1 Results in the Table

results <- data.frame(
  ID          = employees$ID,
  Name        = employees$Name,
  Position    = employees$Position,
  Performance = employees$Performance,
  Salary      = formatC(employees$Salary, format = "f", digits = 0, big.mark = "."),
  `% Bonus`   = employees$Bonus_Pct,
  Bonus       = formatC(employees$Bonus,  format = "f", digits = 0, big.mark = "."),
  check.names = FALSE
)

kable(results, align = c("c","l","l","c","r","c","r"),
      caption = "Employee Bonus Calculation Table")

Employee Bonus Calculation Table
ID	Name	Position	Performance	Salary	% Bonus	Bonus
1	Bagas	Staff	Good	5.000	10%	500
2	Joan	Supervisor	Very Good	7.000	20%	1.400
3	Alya	Staff	Average	6.500	5%	325
4	Dwi	Manager	Good	10.000	10%	1.000
5	Nabil	Director	Very Good	12.000	20%	2.400

3 Loops (For & While)

3.1 For Loop

This section uses a for loop to display employees whose salary is more than 6,000.

for (i in seq_len(nrow(dataset))) {
  if (dataset$Salary[i] > 6000) {
    cat(sprintf("Name: %s, Salary: %g\n",
      dataset$Name[i],
      dataset$Salary[i]
    ))
  }
}

## Name: Joan, Salary: 7000
## Name: Alya, Salary: 6500
## Name: Dwi, Salary: 10000
## Name: Nabil, Salary: 12000

salary_filter <- employees[employees$Salary > 6000, ]

results_table <- data.frame(
  ID          = salary_filter$ID,
  Name        = salary_filter$Name,
  Age         = salary_filter$Age,
  Position    = salary_filter$Position,
  Performance = salary_filter$Performance,
  Salary      = formatC(salary_filter$Salary, format = "f", digits = 0, big.mark = ".")
)

kable(results_table, align = c("c","l","c","l","c","r"),
      caption = "List of Employees with Salary > 6,000")

List of Employees with Salary > 6,000
ID	Name	Age	Position	Performance	Salary
2	Joan	30	Supervisor	Very Good	7.000
3	Alya	27	Staff	Average	6.500
4	Dwi	35	Manager	Good	10.000
5	Nabil	40	Director	Very Good	12.000

Interpretation

The code iterates through the dataset and displays the names and salaries of employees whose salary is greater than 6,000.

3.2 While Loop

This section uses a while loop to display employee data until a Manager position is found.

i <- 1
while (i <= nrow(dataset)) {
  cat(sprintf("Name: %s, Position: %s\n",
    dataset$Name[i],
    dataset$Position[i]
  ))
  if (dataset$Position[i] == "Manager") break
  i <- i + 1
}

## Name: Bagas, Position: Staff
## Name: Joan, Position: Supervisor
## Name: Alya, Position: Staff
## Name: Dwi, Position: Manager

Interpretation

The code displays the names and positions of employees in order and stops when a Manager position is found.

3.3 Break

This section uses a break statement to stop the loop when a certain condition is met.

for (i in seq_len(nrow(dataset))) {
  if (dataset$Salary[i] > 10000) {
    cat("Loop stopped! Found an employee with salary above 10,000:\n")
    cat(sprintf("Name: %s, Salary: %g\n",
      dataset$Name[i],
      dataset$Salary[i]
    ))
    break
  }
  cat(sprintf("Name: %s, Salary: %g\n",
    dataset$Name[i],
    dataset$Salary[i]
  ))
}

## Name: Bagas, Salary: 5000
## Name: Joan, Salary: 7000
## Name: Alya, Salary: 6500
## Name: Dwi, Salary: 10000
## Loop stopped! Found an employee with salary above 10,000:
## Name: Nabil, Salary: 12000

Interpretation

The code will stop the loop when it finds an employee with a salary of more than 10,000.

3.4 Continue

This section uses the continue statement in a loop to skip employee records with “Average” performance.

for (i in seq_len(nrow(dataset))) {
  if (dataset$Performance[i] == "Average") next
  cat(sprintf("Name: %s, Performance: %s, Salary: %g\n",
    dataset$Name[i],
    dataset$Performance[i],
    dataset$Salary[i]
  ))
}

## Name: Bagas, Performance: Good, Salary: 5000
## Name: Joan, Performance: Very Good, Salary: 7000
## Name: Dwi, Performance: Good, Salary: 10000
## Name: Nabil, Performance: Very Good, Salary: 12000

Interpretation

The code displays the names, performance ratings, and salaries of employees, except for those with an “Average” performance rating.