Algorithm is the heart of computer science or informatics.
Many branches of computer science that were referred to in terms of algorithms.
An algorithm must be expressed in a form that can be understood by the processor.

So the processor must:
1. Understanding each step in the algorithm
2. Doing operations corresponding to these steps.
3. Mechanism of the conduct of Algorithm By Others Computer is only one processor.
To be implemented by a computer, the algorithm must be written in a programming language notation, so called programs.
So the program is the embodiment or technical implementation algorithm written in a particular pemrogaman that can be implemented by a computer.

Learning Programming?

Programming Language Learning?

Learning Programming Programming Languages And Learning

Learning to program is
learn about the methodology of solving the problem, then poured it in a particular notation is easy to read and understand.
Learning about problem solving strategies, methodologies and systematic problem solving and then write it in an agreed common notation
Is understanding the problem, analysis and synthesis
emphasis: designer program

Learning a programming language that
learn to use a language of the rules of grammar,
instructions,
operating procedures of its compiler, and
use these instructions to make programs written in that language only just.
center of gravity: coder

Programming
Is a process to implement the algorithm by using a programming language
Type Programming Language
Low Level Language
Designed so that each instruction is done by computer, without a translator Machine
High Level Language
Making programming more accessible.
Need to be translated by a language translator (compiler)

Products produced programmers:
program with a good design (methodological, systematic)
Can be executed by a machine
Function correctly
Able to serve all possible input
Accompanied by documentation
Learning to program, center of gravity: designer program

Algorithms
Action:
Events that occurred in a limited time interval (starting at T0 and ends at time T1)
The net effect is a well-defined and planned
Example:
Tati’s mother peeling potatoes to make dinner .. (wide scope)
Because of wide scope, it must be defined initial state and the net effect of the planned (and Final State Initial State)
Initial State (initial state): T0 existing dikantong potato potatoes, and placed on the kitchen shelf where the mother will strip Tati
Final State (final state): T1 potatoes in the pot terkupas, ready to be cooked and the bag must be returned to the shelves again.
Genesis: the order of several actions that occur in sequence.
The cumulative effect of all the action happens to be the net effect of the incident
Characterization of an event into action is relative depending on the point of view.
Independent Algorithm Notation Language Programming And Against? Engine Computer
Algorithm notation can be translated into various languages.
Although each different computer technology, but in general all the computers can perform basic operations in programming such as:
data reading operation,
comparison operation,
arithmetic operations,

Procedural Programming (1)
The algorithm contains a sequence of steps resolution.
The algorithm is a procedural process.
Definitions of Procedural according to Indonesian Dictionary:
Stages of activities to complete an activity.
The method step by step exactly in solving a problem.

Procedural Programming (2)
Distinguish between the program data with the instruction.
Section consists of instruction sequences (sequence) instructions executed one by one in sequence by the processor.
Instruction execution flow may change because of the conditional branching.
The data stored in the memory instrusi manipulated by successive or procedural.
Such programming paradigm called procedural programming.
RULE? WRITING PROGRAM

Writing Rules Algorithm
The algorithm contains a step-by-step problem-solving.
The steps it can be written in any notation, provided easy to read
Corresponding algorithm corresponding notation with the notation of programming languages in general.
Writing Rules Algorithm
Each algorithm will always consist of three parts namely:

1. Title (Header)
2. Compiler
3. Algorithms

Definition? Computers
Electronic system to manipulate the data quickly and accurately as well as designed and
organized, automatically receive & Storing input data, process it and produce output under interface is a step or instruction program stored in memory

Input Devices
a. Keyboard: the most popular input device
b.Mouse: pointing input device
- Trackball
- Optic

Output device
a. Display device
Element Computers
1. Hardware
2. Software
3. Brainware
Computer System
Collection of elements or components that are mutually
connected to form a unity for achieve a particular goal.

Characterization Computers

• Computer Analog

Used for the continuous nature of data and not the figure of data, but in physical form
Characterization Computers

• Computer Digital

Used for the data in the form of numbers or letters.

Digital computer is usually used for business applications & Techniques Characterization Computers

• Hybrid Computer

Combination of an Analog Computer & Digital Based User
Computer Special Purpose
Computer to handle things and certain areas, for example, health, chemical plants,
oil refineries, steel factories, military, navigation onboard submarines & ships flying

Based User
General Purpose Computer

Computer to handle the various areas of science and the various issues Jobs Based Capacity & size
Micro Computer

Personal Computer / Desktop Computer which its main memory sizes ranging from 16KB-1MB with Operation configuration register 8bit, 16bit, 32 bit

Based Capacity & size

• Mini Computer

Mini computer can be a multi user, a mini computer can have several terminals can be used with the reply-sam by many users.

• Small Computer

Using Multi-programming systems, virtula Multi Processing and storage, and is multiuser with the number of terminals to hundreds of fruit.

• Medium Computer

Using Multi-programming systems, virtula Multi Processing and storage, and is multiuser with the number of terminals to hundreds of fruit, DPP Distributed Data Processing jg collapsible stand alone

• Large Computer

Implement effectively allows Time Sharing system, hundreds of users can use these computers simultaneously from their respective terminals at the same time

• Super Computer

Implement effectively allows timesharing system, thousands of terminals can be connected with the Super Computer and thousands of users can use simultaneously.

THANK YOU!

What is statistics?
Definition:
Statistics is a science which studies ways to collect, process, organize, present, analyze, and interpret the data rates in order to help effective decision making.

Role and Development of Statistics?
As something to do with the data rate, in statistics originally used for government purposes only, such as:
Population data collection, taxation, military personnel records, etc..
Today the growing use of statistics and widespread in various fields of activities such as:
Business and industry (eg banking, hospitality, trade, manufacturing).
Education.
Politics.
Health field.
Law,
Etc..

Types of statistics:
1. Descriptive statistics are statistical methods used to describe the data that has been collected.
Referring to the definition of statistics that includes procedures for arranging, presenting, and analyzing the data rate ..

2. Statistical Inference is the methods used to make decisions about population characteristics based on a sample.
Referring to the definition of statistics that includes procedures for interpreting the data rate.

Statistical methodology based on the assumption of distribution, including:
1. Statistical parametric
When developed using the assumption that the input variables have a particular form of distribution.
2. Non-parametric statistics
When developed without the assumption of certain forms of distribution.

Some important terms:
Population
The set or collection of all objects that will be examined.
Sample
Subsets of the population.
Samples should provide a picture as possible of the population, so by taking a number of members of the population, then we can talk about the members of the population as a whole.

Census:
Is how to collect data where all members of the population were observed one by one as a whole.

Sampling:
Is how to collect data where the investigation is an element of a population sample.

Parameters:
Is a quantity that states the conditions of the population.
Which is often used is the average (), variance ( 2), standard deviation ().
Statistics:
Is a quantity that states the condition of the sample.
Which is often used is the average, variance (S2), standard deviation (S).
Data:
The process always involves statistical data as input.
Data are:
Something that is known / sought to give a picture of a situation or problem.
Data is usually associated with the place and time.
Uses Data:
1. The basis of a planning
Aiming for capabilities planning in accordance with the planning in order to avoid the difficult to implement (ambitious).
2. Control tool
Aiming to be known immediately errors or irregularities occur, so it can be remedied or corrected.
3. Basic evaluation
From the end of the work. Is the target achievable? if not achieved, what factors affect

Good data requirements:

• Objective,

Data must be in accordance with actual conditions.

• Representative

Data should be representative of the observed object.

• Standard error (standard error) is small.

Having a high level of accuracy.

• Time.

As a means of control or evaluation, then the right conditions is very important at this time.

• Relevant.

The data collected must be something to do with the problem to be solved.

The division of data:

According to its nature:

• Qualitative data and quantitative data.

According to the source:

• Internal data and external data.

According to how acquired:

• Primary data and Secondary data

Collection ways, a.l.:

1. Interviews
2. Questionnaire
3. Observation

Measurement Scale:
have distinguishing characteristics.

Some Sample Data Collection Method:

1. Simple Random Samples withdrawal (Simple Random Sampling)
2. Systematic Random Samples withdrawal (Systematic Random Sampling)
3. Random Samples withdrawal Structured (stratified random sampling)
4. Sample Withdrawal Cluster (Cluster Sampling)

Simple Random Samples withdrawal (Simple Random Sampling):
Is a sampling method where the selection of population elements to be a member of the sample is such that each element has the same chance of being selected.
The easiest way for this method is to use a random number table (Table of Random Numbers).
Example Table Random Numbers:
For example, will choose 5 of 22 members of the population.
Systematic Random Samples withdrawal (Systematic Random Sampling):
Is a sampling method in which the population elements arranged in a certain way – for example: according to alphabet, according to the date received, etc .- and then selected a random starting point and every element of k is selected as the sample population.

Pros: Simple in selecting the sample and easily checked

Weaknesses: If the sampling interval associated with a periodic sequence of the population, can cause great variability

Random Samples withdrawal Structured (stratified random sampling):

Is a sampling method where the initial population is divided into several sub-groups, called strata, then a random sample selected from each stratum.
After that sample selection can be done in a way proportional, which means requiring proportionate number of elements in each stratum equal to the proportion found in the population.

For example, 352 firms are divided into 5 strata. And will be selected among 50 companies to do more in-depth research. So to determine the amount taken as a sample from each stratum is as follows:

Pros: Ensure representation of all groups in the sample

Weaknesses: Need accurate information in each stratum; if the list of strata is not yet available, the cost of expensive preparation
Sample Withdrawal Cluster (cluster sampling):
Is a sampling method where the population is spread in some areas (clusters), each of which has characteristics (characteristics) are nearly equal, then one or several areas can be selected at random as a sample.

For example, will be observed in the rural poverty problem in a district. In these districts there are 50 villages which have almost the same diversity in many ways (education, employment, welfare, etc..).
Since each village (as a cluster) has a similar diversity, then one of the villages can be selected as a sample to represent other villages.

Pros: This method does not require that the sampling frame to determine who will be selected sample is much easier than other methods.
Weaknesses: with the flexibility in determining the sample, the value of the observation sampling error is often quite large.

“Do the best and let God do the rest”