1	Course Title:	SYSTEM ANALYSIS AND PLANNING IN AGRICULTURAL MACHINERY
2	Course Code:	BSM5027
3	Type of Course:	Optional
4	Level of Course:	Third Cycle
5	Year of Study:	1
6	Semester:	1
7	ECTS Credits Allocated:	6
8	Theoretical (hour/week):	3
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:	None
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Prof. Dr. Halil Ünal
16	Course Lecturers:	Yok
17	Contactinformation of the Course Coordinator:	Prof. Dr. Halil ÜNAL e-posta : hunal@uludag.edu.tr Telefon: 0 224 2941607 Adres: Bursa Uludağ Üniversitesi, Ziraat Fakültesi, Biyosistem Mühendisliği Bölümü, Görükle Kampüsü, 16059, Nilüfer/BURSA
18	Website:
19	Objective of the Course:	To provide theoretical and practical learning of numerical estimation methods, operations research techniques, linear programming and network analysis methods. It is the ability of students to show a systematic approach to the problems they may encounter, to think analytically, to make predictions for the future and to gain the skills of project planning and evaluation.
20	Contribution of the Course to Professional Development	Learn theoretically and practically operations research techniques and linear programming and network analysis methods. Learns analytical thinking, making predictions for the future. It is the acquisition of project planning and evaluation skills.

21

Learning Outcomes:

1 Learns numerical estimation methods.; 2 Learn theoretically and practically operations research techniques and linear programming and network analysis methods.; 3 The student can show a systematic approach to the problems he / she may encounter.; 4 Learns analytical thinking, making predictions for the future.; 5 It is the acquisition of project planning and evaluation skills.;

22	Course Content:

Week	Theoretical	Practical
1	The system concept, basic structural elements of the system, system operation and classification of systems according to their behavior.
2	Model definition, types and explanation of modeling principles.
3	Explanation of working stages in system analysis.
4	Systematic approach to agricultural mechanization.
5	Distribution charts, time series models (sliding averages, trend projections), causal estimation methods (single and multiple regression) and judicial Delphi method, which are included in numerical estimation methods.
6	Distribution charts, time series models (sliding averages, trend projections), causal estimation methods (single and multiple regression) and judicial Delphi method, which are included in numerical estimation methods.
7	Distribution charts, time series models (sliding averages, trend projections), causal estimation methods (single and multiple regression) and judicial Delphi method, which are included in numerical estimation methods.
8	Distribution charts, time series models (sliding averages, trend projections), causal estimation methods (single and multiple regression) and judicial Delphi method, which are included in numerical estimation methods.
9	Reliability and method comparisons in forecasting.
10	Linear Programming Applications and Problem Formulation definition and explanation with examples,
11	Linear Programming Applications and Problem Formulation definition and explanation with examples,
12	Canonical and Standard Form models and explanation of inequality transformations.
13	Simplex Method definition, graphical method in bivariate model analysis, Simplex algorithm, artificial variables technique,
14	Some special cases encountered in analysis, sensitivity analysis.

23	Textbooks, References and/or Other Materials:
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	0	0
Quiz	0	0
Homeworks, Performances	4	40
Final Exam	1	60
Total	5	100
Contribution of Term (Year) Learning Activities to Success Grade		40
Contribution of Final Exam to Success Grade		60
Total		100
Measurement and Evaluation Techniques Used in the Course	Measurement and evaluation is carried out according to the principles of Bursa uludag University Graduate Education Regulation.
Information	Results are determined with the letter grade determined by the student automation system.

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ECTS / WORK LOAD TABLE

Activites	NUMBER	TIME [Hour]	Total WorkLoad [Hour]
Theoretical	14	3	42
Practicals/Labs	0	0	0
Self Study and Preparation	0	0	0
Homeworks, Performances	4	32	128
Projects	0	0	0
Field Studies	0	0	0
Midtermexams	0	0	0
Others	0	0	0
Final Exams	1	3	3
Total WorkLoad			173
Total workload/ 30 hr			5,77
ECTS Credit of the Course			6

26	CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 PQ7 PQ8 PQ9 PQ10 PQ11 PQ12 LO1 4 4 4 5 3 4 4 4 4 4 3 5 LO2 4 4 5 4 3 4 4 4 3 4 4 4 LO3 3 4 4 4 4 4 5 5 4 3 4 4 LO4 4 3 3 4 4 5 5 5 4 4 4 4 LO5 4 4 4 4 3 4 3 4 4 4 4 3

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High