Pemrograman Sains Data I
Syntax and Control Flow
PRAKTIKUM
Dataset
| PENGENAL | Nama | Usia | Gaji | Posisi | Pertunjukan |
|---|---|---|---|---|---|
| 1 | Bagas | 25 | 5000 | Staf | Baik |
| 2 | Joan | 30 | 7000 | Pengawas | Sangat bagus |
| 3 | Alya | 27 | 6500 | Staf | Rata-rata |
| 4 | Dwi | 35 | 10000 | Manajer | Baik |
| 5 | Nabil | 40 | 12000 | Direktur | Sangat bagus |
Conditional Statements
Menghitung Bonus Berdasarkan Kinerja
## Name: Bagas, Bonus: 500
## Name: Joan, Bonus: 1400
## Name: Alya, Bonus: 325
## Name: Dwi, Bonus: 1000
## Name: Nabil, Bonus: 2400Loops (For & While)
For Loop
Filter Karyawan dengan Gaji > 6000
## Name: Joan, Salary: 7000
## Name: Alya, Salary: 6500
## Name: Dwi, Salary: 10000
## Name: Nabil, Salary: 12000While Loop
Jalankan Loop Hingga Menemukan Manajer
## Name: Bagas, Position: Staff
## Name: Joan, Position: Pengawas
## Name: Alya, Position: Staff
## Name: Dwi, Position: Manajer
## (Stop here)Break
Break Jika Gaji > 10.000
## Name: Bagas, Salary: 5000
## Name: Joan, Salary: 7000
## Name: Alya, Salary: 6500
## Name: Dwi, Salary: 10000
## Name: Nabil, Salary: 12000
## (Stopped because Nabil has a salary above 10,000)Continue
Melewati Karyawan dengan Kinerja “Rata-rata”
## Name: Bagas, Performance: Baik
## Name: Joan, Performance: Sangat bagus
## Name: Dwi, Performance: Baik
## Name: Nabil, Performance: Sangat bagus## (Alya is skipped because the performance is 'Average')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