PERANCANGAN KULIAH LECTURE PLAN MAKLUMAT KURSUS (COURSE INFORMATION) SEMESTER/SESI (SEMESTER/SESSION) :II 2015 / 2016 KOD KURSUS (COURSE CODE) :BIT 10703 NAMA KURSUS (NAME OF COURSE) BEBAN AKADEMIK PELAJAR (STUDENT ACADEMIC LOAD) Kategori Aktiviti (Category of Activities) UNIVERSITI TUN HUSSEIN ONN MALAYSIA FAKULTI SAINS KOMPUTER DAN TEKNOLOGI MAKLUMAT :DATA STRUCTURE AND :ALGORITHMS Aktiviti Pembelajaran Jumlah Jam/ Semester (Learning Activities) (Total Hours/ Semester) Kuliah (Lecture) 28 Pembelajaran bersemuka (Face-to-face learning) Pembelajaran kendiri (Independent study) Tutorial / Amali (Tutorial / Practical) 28 Aktiviti pembelajaran berpusatkan pelajar lain (Other student centered learning activities) Penyediaan tugasan, projek dan lain-lain (Preparing assignment, project and others) Ulangkaji (Revision) Persediaan bagi pentaksiran (Preparation for assessment) 6 14 28 10 Pentaksiran rasmi (Formal assessment) Pentaksiran berterusan (Continuous assessment) Peperiksaan akhir (Final examination) JUMLAH JAM BELAJAR PELAJAR (JBP) (TOTAL STUDENT LEARNING TIME (SLT)) 3 3 120 Matapelajaran Pra-syarat (Pre requisite subjects) Nama Pensyarah (Lecturer s name) : BIT 10303 COMPUTER PROGRAMMING : DR NOOR AZAH BINTI SAMSUDIN
Disediakan oleh (Prepared by) : Tandatangan (Signature) : Nama (Name) : Dr. Noor Azah binti Samsudin Tarikh (Date): 14th February 2016 Disahkan oleh (Approved by) : Tandatangan (Signature) : Nama (Name) : Dr. Nureize binti Arbaiy Tarikh (Date): 14th February 2016 MATLAMAT (GOALS) : To provide students with a good understanding on data structures and their implementation. SINOPSIS (SYNOPSIS) : This course introduces students to data concept, data structure and types of data structure, array, pointer, abstract data type, searching, sorting, trees and graph. HASIL PEMBELAJARAN (LEARNING OUTCOMES) : By the end of the course, students should be able to: (1) Design problem solving process using data structure techniques. (C5, CTPS) (2) Construct a computer application using data structuure technques. (P4, Practical Skill) (3) Demonstrate the implementation of data structure techniques in any high level programming language. (A3, LL) ISI KANDUNGAN (CONTENT) : MINGGU KANDUNGAN (WEEK) (CONTENT) 1-2 BAB 1: JENIS DATA DAN JENIS DATA ABSTRAK (4 Jam) Data Type and Abstract Data Type(4 hours) PENTAKSIRAN (ASSESSMENT) 1.1 Jenis Data, Tatasusunan, Penuding Data types, Array, Pointer 1.2 Jenis Data Abstrak dan Implementasi Abstract Data Types and Implementation 1.3 Objek, Kelas dan Bahasa Pengaturcaraan Sokongan untuk Jenis Data Abstrak Object, Class and Support Programming Language for Abstract Data Type 3-4 BAB 2: STRUKTUR DATA (4 Jam) DATA STRUCTURE(4 hours) 2.1 Pengenalan kepada Jenis-jenis Struktur Data Introduction to type of Data Structure 2.2 Timbunan Stack 2.3 Baris Gilir Queue 2.4 Rekursif Recursive 2.5 Isihan dan Carian Sorting and Searching
2.6 Pepohon Trees 2.7 Graf Graph 5-6 BAB 3: SENARAI BERPAUT (4 Jam) Linked List (4 hours) 3.1 Konsep Senarai Berpaut Linked List Concept 3.2 Jenis-Jenis Senarai Berpaut Types of linked list 3.3 Operasi-Operasi Senarai Berpaut Linked List Operations Kuiz 1/Quiz 1 7 BAB 4: TIMBUNAN (2 Jam) Stack (2 hours) 4.1 Pengenalan kepada Timbunan Introduction to Stacks 4.2 Implementasi dan Operasi Timbunan Implementation and Operation of Stacks 8 BAB 5: BARIS GILIR (2 Jam) Queue (2 hours) 5.1 Pengenalan kepada Baris Gilir Introduction to Queue 5.2 Jenis-jenis baris gilir Types of queue 5.3 Implementasi dan Operasi Baris Gilir Implementation and Operation oof queues Ujian/Test 9-10 BAB 6: CARIAN DAN ISIHAN (4 Jam) Searching and sorting (4 hours) 6.1 Big Oh Notation 6.2 Penggelintaran Jujukan (Sequential Searching) 6.3 Penggelintaran Dedua (Binary Searching) 6.4 Isihan Selitan (Inserting Sort) 6.5 Isihan Pilihan (Optional Sort) 6.6 Shell Sort 6.7 Isihan Cepat (Quick Sort) 6.8 Isihan Cantuman (Merge Sort) 6.9 Radix Sort 6.10 Stack Sort 6.11 Teknik Cincang (Hash Technique) 6.12 Teknik Menganalisis Isihan dan Gelintar Sorting and Searching Analysis Techniques 11-12 BAB 7: PEPOHON (4 Jam) Tree (4 hours) 7.1 Pengenalan kepada Pepohon dan Pepohon Dedua Introduction to Tree and Binary Tree 7.2 Penyusuran Pepohon Dedua Binary tree traversal 7.3 Gelintaran Pepohon Dedua Binary Tree Searching 7.4 Operasi Pepohon Dedua Binary tree operation Kuiz 2 / Quiz 2 13-14 BAB 8: GRAF (4 Jam) Graph (4 hours) 8.1 Graf ADT ADT Graph
8.2 Graf Traversal Traversal Graph 8.3 Algoritma Depth-first dan Breadth-first Algorithm Depth-first and Breadth-first 8.4 Shortest Paths, Best-first 14 PEMBENTANGAN PROJEK PEPERIKSAAN AKHIR FINAL EXAMINATION TUGASAN / PROJEK (ASSIGNMENT / PROJECT) (i) (ii) (iii) Tugasan (Assignment) Tugasan adalah berdasarkan tugasan praktikal yang dijalankan setiap minggu di makmal seperti dinyatakan di bahagian (iii). Assignments will be based on the weekly lab activities in the laboratory as stated in (iii). Projek (Project) Pelajar akan membangunkan sebuah sistem ringkas menggunakan konsep struktur data. Ia adalah aktiviti secara kumpulan. Students will develop a simple system using C using data structure concept. It is a group activity. Amali (Practical) MINGGU (WEEK) AMALI (CONTENT) 1 Mengimplementasikan pointers dan array dalam pengaturcaraan Implementation of pointers and array in programming 2 Mengimplementasikan pointers dan array dalam pengaturcaraan Implementation of pointers and array in programming 3 Aplikasi struct struct application 4 Mengimplementasikan operasi Linked List Implementation of Linked list operations 5 Mengimplementasikan operasi Linked List Implementation of Linked list operations 6 Aplikasi Stack dan Queue Stack and Queue applications 7 Aplikasi isihan dan kaedah pencarian Sorting and searching applications 8 Mengimplementasikan pepohon Tree implementation 9 Mengimplementasikan graph Graph implementation 10 Aktiviti berkumpulan- mengaplikasi konsep struktur data dalam kajian kes Group activity application of data structure in a case study 11 12 13 Persembahan Projek Project Presentation 14 Persembahan Projek Project Presentation PENILAIAN (ASSESSMENT) : (1) Quiz : 5 % (2) Test : 15 %
(3) Lab Assignment : 20 % (4) Project : 20 % (5) Final Examination : 40 % : Total : 100 % RUJUKAN (REFERENCES) : 1. Weiss, M.A., 2014. Data structures and algorithm analysis in C++. 4th ed. Harlow: Addision Wesley. Call number: QA76.73.C153.W44 2014. 2. Main, M. & Savitch, W. J., 2011. Data structures & other objects using C++. 4th ed. Boston, MA : Addison Wesley. Call number : QA76.73.C153.M38 2011 3. Malik, D.S., 2009. Data structures using C++. 2nd ed. Boston: Course Technology. 4. Dale, N. B., 2007. C++ plus data structures. 3rd ed. Sudbury, MA : Jones & Bartlett Publishers. Call number : QA76.73.C153.D346 2007. 5. Brandle, S., Geisler, J., Roberge, J. & Whittington, D., 2009. C++ data structures : a laboratory course. 3rd ed. Sudbury, MA : Jones and Bartlett Publishers. Call number : QA76.73.C153.D37 2009. KEHADIRAN / PERATURAN SEMASA KULIAH (LECTURE ATTENDANCE / REGULATION) (1) Pelajar mesti hadir tidak kurang dari 80% masa pertemuan yang ditentukan bagi sesuatu mata pelajaran termasuk mata pelajaran Hadir Wajib (HW) dan mata pelajaran Hadir Sahaja (HS). Students must attend lectures not less than 80% of the contact hours for every subject including Compulsory Attendance Subjects (Hadir Wajib HW) and Attendance Only Subjects (Hadir Sahaja HS) (2) Pelajar yang tidak memenuhi perkara (1) di atas tidak dibenarkan menghadiri kuliah dan menduduki sebarang bentuk penilaian selanjutnya. Markah sifar (0) akan diberikan kepada pelajar yang gagal memenuhi perkara (1). Manakala untuk mata pelajaran Hadir Wajib (HW), pelajar yang gagal memenuhi perkara (1) akan diberi Hadir Gagal (HG). Students who do not fulfill item (1) will not be allowed to attend further lectures and sit for any further examination. Zero mark (0) will be given to students who fail to comply with item (1). While for Compulsory Attendance Subjects (Hadir Wajib HW), those who fail to comply with item (1) will be given Failure Attendance (Hadir Gagal HG). (3) Pelajar perlu mengikut dan patuh kepada peraturan berpakaian yang berkuatkuasa dan menjaga disiplin diri masing-masing untuk mengelakkan dari tindakan tatatertib diambil terhadap pelajar. Students must obey all rules and regulations of the university and must discipline themselves in order to avoid any disciplinary actions against them. (4) Pelajar perlu mematuhi peraturan keselamatan semasa pengajaran dan pembelajaran. Student must obey safety regulations during learning and teaching process. MATRIK HASIL PEMBELAJARAN SUBJEK DAN HASIL PEMBELAJARAN PROGRAM (SUBJECT LEARNING OUTCOMES AND PROGRAMME LEARNING OUTCOMES MATRIX) Dilampirkan (Attached)
MATRIK HASIL PEMBELAJARAN KURSUS DAN HASIL PEMBELAJARAN PROGRAM MATRIX OF COURSE LEARNING OUTCOMES AND PROGRAMME LEARNING OUTCOMES Fakulti (Faculty) : FACULTY OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Matrik ini perlu digunakan bersama: (This matrix is to be used with) Program (Programme) : BACHELOR OF COMPUTER SCIENCE 1. Objektif Pendidikan Program (PEO) (Programme Educational Objectives (PEO)) Kod Kursus (Course Code) : BIT 10703 2. Hasil Pembelajaran Program (PLO) (Programme Learning Outcomes (PLO)) Nama Kursus (Course Title) : DATA STRUCTURE AND ALGORITHMS Bil. (No.) Hasil Pembelajaran Kursus (Course Learning Outcomes) 1 Design problem solving process using data structure techniques. 2 Construct a computer application using data structure techniques. 3 Demonstrate the implementation of data structure techniques in any high level programming language. PLO1 PLO2 P4 Pematuhan kepada PLO (Compliance to PLO) PLO3 PLO4 PLO5 PLO6 PLO7 PLO8 PLO9 PLO10 PLO11 C5 A3 PLO12 PLO13 Kaedah Penyampaian (Method of Delivery) Lectures, Tutorial Assignment/ Project Project Kaedah Pentaksiran (Method of Assessment) Quiz, Test, Final Examination, Assignment, Project Assignment, Project, Presentation Assignment, Project, Presentation KPI At least 50% of the students get 50% and above of their cognitive total marks. At least 50% students get 50% and above of their psychomotor total marks. At least 50% students get 50% and above of their total affective marks. Jumlah (Total) Taksonomi Pembelajaran (Learning Taxonomy) Kognitif (Cognitive) Psikomotor (Psychomotor) Afektif (Affective) C1 Pengetahuan (Knowledge) P1 Persepsi (Perception) A1 Menerima (Receiving) C2 Pemahaman (Comprehension) P2 Set (Set) A2 Memberikan Maklum Balas (Responding) C3 Aplikasi (Application) P3 Respons Berpandu (Guided Response) A3 Menilai (Valuing) C4 Analisis (Analysis) P4 Mekanisme (Mechanism) A4 Mengorganisasi (Organising) C5 Sintesis (Synthesis) P5 Respons Ketara Kompleks (Complex Overt Response) A5 Menghayati Nilai (Internalising) C6 Penilaian (Evaluation) P6 Adaptasi (Adaptation) P7 Lakuan Tulen (Origination)