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-- MODULE HANDBOOK DATA STRUCTURE AND ALGORITHMS BACHELOR DEGREE PROGRAM DEPARTEMENT OF STATISTICS FACULTY OF SCIENCE AND DATA ANALYTICS INSTITUT TEKNOLOGI SEPULUH NOPEMBER ENDORSEMENT PAGE MODULE HANDBOOK DATA STRUCTURE AND ALGORITHMS DEPARTMENT OF STATISTICS INSTITUT TEKNOLOGI SEPULUH NOPEMBER Penanggung Jawab Proses Person in Charge Tanggal Process Nama Jabatan Tandatangan Date Name Position Signature Perumus Dr. Kartika Dosen March 28, 2019 Preparation Fithriasari, M.Si Lecturer Pemeriksa dan Dr. Kartika Tim kurikulum April 15, 2019 Pengendalian Fithriasari, M.Si Curriculum Review and team Control Persetujuan Prof. NUR Koordinator July 17, 2019 Approval Iriawan RMK Course Cluster Coordinator Penetapan Dr. Kartika Kepala July 30, 2019 Determination Fithriasari, M.Si Departemen Head of Department MODULE HANDBOOK DATA STRUCTURE AND ALGORITHMS Module name Data Structure and Algorithms Module level Undergraduate Code KS184528 Course (if applicable) Data Structure and Algorithms Semester Fifth Semester (Ganjil) Person responsible for Dr. Kartika Fithriasari, M.Si the module Lecturer Dr. Kartika Fithriasari, M.Si Language Bahasa Indonesia and English th Relation to curriculum Undergradute degree program, mandatory, 5 semester. Type of teaching, Lectures, <50 students contact hours Workload 1. Lectures : 2 x 50 = 100 minutes per week. 2. Practicum : 90 minutes per week. 3. Exercises and Assignments : 2 x 60 = 120 minutes (2 hours) per week. 4. Private learning : 2 x 60 = 120 minutes (2 hours) per week Credit points 2 credit points (SKS) Requirements A student must have attended at least 80% of the lectures to sit in according to the the exams. examination regulations Mandatory Pemrograman Komputer/ Computer Programming prerequisites Learning outcomes CPMK.1 Able to explain and apply the concept of Data PLO – 1 and their Structure for statistical analysis purposes corresponding PLOs CPMK.2 Able to explain Data Structure procedures CPMK.3 Able to apply Data Structure to analyze data and PLO – 3 interpret it, such as doing data management, etc. CPMK.4 Able to identify, formulate, and solve statistical PLO – 4 problems in the Data Structure field CPMK.5 Able to use computing techniques and modern computer devices required in the field of statistics CPMK.6 Have knowledge of current and future issues in PLO – 5 order to be able to make the right decisions for the preparation of data structures based on existing problems and able to communicate the results of analysis both verbally and in writing CPMK.7 Able to communicate effectively and cooperate in interdisciplinary and multidisciplinary teams CPMK.8 Has professional responsibilities and ethics CPMK.9 Able to motivate yourself to think creatively and learn throughout life Content The data structure course discusses the dynamic arrangement of data. The basic knowledge that students must have is programming knowledge. This course is useful for compiling simulation result data. Stack material provides an overview of data processing if the arrangement of data is stacked, pointer, queue and list material provides an overview of data processing sequentially. Material Tree, sort graph and search are useful for sorting data. Study and • In-class exercises examination • Assignment 1, 2, 3 requirements and • Mid-term examination forms of examination • Final examination Media employed LCD, whiteboard, websites (myITS Classroom), zoom. Reading list 1. Goodrich, Tamassia and Goldwasser. 2013. Data Structures and Algorithms in Python. ISBN: 978-1-118-29027-9. 2. Lee, Kent D. and Hubbard, Steve. 2015. Data Structures and Algorithms with Python. ISSN 1863-7310 DOI 10.1007/978- 3-319-13072-9. 3. Shaffer, Clifford A. 2012. Data Structures and Algorithm Analysis in C++. 3rd edition. ISBN: 048648582X and 9780486485829. 4. Weiss, M. A. and Wesley,Addison. 2007. Data Structures and Algorithm Analysis in C++. 3rd edition. ISBN-10: 032144146X dan ISBN-13: 9780321441461 .
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