Minggu, 28 Oktober 2018

Teknologi Sistem Cerdas : Self-Driving dari Tesla model S



Model S

Tesla model S adalah mobil buatan perusahaan otomotif asal Amerika Serikat Tesla. Tesla mengklaim bahwa model S adalah mobil yang paling nyaman , tetapi juga tidak mengesampingkan performa. Model S dilengkapi dengan berbagai teknologi terbaharu , salah satunya adalah Self-Driving. Untuk mendukung teknologi tersebut Tesla menanamkan sensor diberbagai sudut mobil, total ada 8 kamera sensor sehingga mampu mendeteksi apa saja yang ada disekitar dan menyediakan penglihatan 360 derajat melalui layar.

Ada beberapa keunggulan Self-Driving dari Tesla ini diantaranya :

  • Mobil akan menyesuaikan kecepatannya sesuai dengan kondisi di jalan raya.
  • Mobil tetap berada didalam jalur.
  • Otomatis keluar dari jalan TOL ketika tujuan sudah dekat.
  • Self-Parking atau mampu parkir sendiri
  • Mobil bisa menghampiri pemilik dengan sendirinya.




Sumber :
https://www.tesla.com/autopilot




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Senin, 16 April 2018

IT Service Management : SERVICE DESIGN

SERVICE DESIGN

INTRODUCTION
            Once an organisation has determined the IT strategy it wishes to pursue, it uses the service design phase of the lifecycle to create new services which service transition then introduces into the live environment. In so doing, service design aims to take the necessary steps to ensure that the new service will perform as planned and deliver the functionality and benefits intended by the business.

WHY SERVICE DESIGN?
            Without well-established service design, services will become less stable and more expensive to maintain and become increasingly less supportive of business and customer needs. Good service design will deliver a range of business benefits that help to underline its importance in the design of new and changed services.

THE FIVE MAJOR ASPECTS OF SERVICE DESIGN
            ITIL formally recognises five separate aspects of service design that together describe the scope of this part of the service lifecycle:
  • The introduction of new or changed services through the accurate identification of business requirements and the agreed definition of service requirements.
  • The service management systems and tools such as the service portfolio, ensuring mutual consistency with other services and appropriate tools support.
  • The capability of technology architectures and management systems to operate and maintain new services.
  • The capability of all processes, not just those in service design, to operate and maintain new and changed services.
  • Designing in the appropriate measurement methods and metrics necessary for performance analysis of services, improved decision-making and continual improvement.


OBJECTIVES OF SERVICE DESIGN
            From the considerations above, we can appreciate that the main objectives of service design are:
  • to design services that not only satisfy business and stakeholder objectives in terms of quality, ease-of-use, compliance and security, but also minimise the total cost of ownership;
  • to design efficient and effective policies, plans, processes, architectures and frameworks to manage services throughout their lifecycle;
  • to support service transition in identifying and managing the risks associated with introducing new or changed services;
  • to design measurement systems for assessing the efficiency and effectiveness of service design and its deliverables;
  • to contribute to continual service improvement (CSI), particularly by designing in features and benefits and then responding to improvement opportunities identified from the operational environment.


THE SERVICE DESIGN PACKAGE
            The design stage takes a set of new or changed business requirements and develops a solution to meet them. The developed solution is passed to service transition to be built, tested and deployed into the live environment.


Daftar Pustaka : IT_Service_Management_2nd_Edition.pdf

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Senin, 19 Maret 2018

IT Service Management : WHAT IS SERVICE MANAGEMENT?



  • WHAT IS SERVICE MANAGEMENT?

Service management is a set of specialised organisational capabilities for providing value to customers in the form of services.
These ‘specialised organisational capabilities’ include the processes, activities,functions and roles that a service provider uses in delivering services to their customers, as well as the ability to establish suitable organisation structures, manage knowledge, and understand how to facilitate outcomes that create value.

  • ‘BEST PRACTICE’ VERSUS ‘GOOD PRACTICE’

The term ‘best practice’ generally refers to the ‘best possible way of doing something’. The idea behind best practice is that one creates a specification for what is accepted by a wide community as being the best approach for any given situation. Then, one can compare actual job performance against these best practices and determine whether the job performance was lacking in quality somehow. Alternatively, the specification for best practices may need updating to include lessons learned from the job performance being graded.
Enterprises should not be trying to ‘implement’ any specific best practice, but adapting and adopting it to suit their specific requirements. In doing this, they may also draw upon other sources of good practice, such as public standards and frameworks, or the proprietary knowledge of individuals and other enterprises as illustrated in Figure 1.1.

Enterprises deploying solutions based on good and best practice should, in theory, have an optimal and unique solution. Their solution may include ideas that are gradually adopted by other enterprises and, having been widely accepted, eventually become recognised inputs to good and best practice.

  • THE ITIL FRAMEWORK

ITIL is not a standard in the formal sense but a framework which is a source of good practice in service management. The standard for IT service management (ITSM) is ISO/IEC 20000, which is aligned with, but not dependent on, ITIL.
As a formal standard, ISO/IEC 20000 defines a set of requirements against which an organisation can be independently audited and, if they satisfy those requirements, can be certificated to that effect. The requirements focus on what must be achieved rather than how that is done. ITIL provides guidance about how different aspects of the solution can be developed.
The ITIL Library has the following components:
  •  ITIL Core: Publications describing generic best practice that is applicable to all types of organisation that provide services to a business.
  • ITIL Complementary Guidance: A set of publications with guidance specific to industry sectors, organisation types, operating models and technology architectures.

The objective of the ITIL service management framework is to provide guidance applicable to all types of organisations that provide IT services to businesses, irrespective of their size, complexity, or whether they are commercial service providers or internal divisions of a business.

  • THE ITIL CORE

The service lifecycle is an approach to IT service management that emphasises the importance of coordination and control across the various functions, processes and systems necessary to manage the full lifecycle of IT services. The service management lifecycle approach considers the strategy, design, transition, operation and continual improvement of IT services.

  • COMPLEMENTARY MATERIAL

Complementary material may take the form of books or web-based material and may be sourced from the wider industry, rather than from The Cabinet Office/The Stationery Office (TSO). Examples of such material are glossary of terms, process models, process templates, role descriptions, case studies, targeted overviews and study aids for passing examinations. These will typically be officially commissioned and published by TSO.

  • RELATED MATERIAL

Apart from the ISO/IEC 20000 standard, ITIL is also complementary to many other standards, frameworks and approaches. No one of these items will provide everything that an enterprise will wish to use in developing and managing their business. The secret is to draw on them for their insight and guidance as appropri­ate.

  • THE ITIL SERVICE MANAGEMENT MODEL

The design definition is passed to the service transition stage, where the service is built, evaluated, tested and validated, and transitioned into the live environment, where it enters the live service operation stage. The transition phase is also responsible for supporting the service in its early life and the phasing out of any services that are no longer required. Service operation focuses on providing effective and efficient operational services to deliver the required business outcomes and value to the customer. This is where any value is actually delivered and measured.

  • KEY CONCEPTS

Value
From the earlier definition of a service, it is clear that the primary focus is on delivering value to the service consumer. Value is created through providing the right service under the right conditions.

Service assets
Service providers create value through using their assets in the form of resources and capabilities.

Service model
A service model describes how a service provider creates value for a given portfolio of customer contracts by connecting the demand for service from the assets of its customers with the service provider’s service assets.

Functions, processes and roles
The terms function, process and role are often confused. This is not surprising since they are so intertwined. In addition, the way the words are used in ITIL is precise, and may be confused with the way these words are used in a more general context.

Process characteristics
A process transforms a prescribed set of data, information and knowledge into a desired outcome, using feedback as a learning mechanism for process improvement.

Role
A set of responsibilities, activities and authorities granted to a person or team.




Daftar Pustaka : IT_Service_Management_2nd_Edition.pdf

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Senin, 15 Januari 2018

Trend sistem informasi saat ini : AI dan Advanced Machine Learning

AI dan Advanced Machine Learning

Kecerdasan buatan (AI) dan pembelajaran mesin canggih (ML) yang terdiri dari teknologi dan proses seperti pembelajaran yang mendalam (deep learning) dan jaringan saraf. Sebelumnya hal ini dimulai sebagai algoritma untuk mengotomatisasi tugas-tugas manual, meminjam dari teknik statistik canggih yang telah berkembang menjadi kerangka yang lebih luas dan arsitektur yang dapat belajar seperti manusia, dan dapat menggunakan data historis untuk memprediksi masa depan. Sistem ini akan menjadi lebih mudah beradaptasi dan berpotensi beroperasi secara mandiri.

AI dan Machine Learning menimbulkan spektrum implementasi yang cerdas, termasuk perangkat fisik (robot, kendaraan otonom, elektronik konsumen) serta aplikasi dan layanan (asisten pribadi virtual, penasihat cerdas). Implementasi tersebut merupakan sebuah kelas baru pada aplikasi cerdas serta menyediakan hal intelijen yang tertanam untuk berbagai perangkat dan perangkat lunak pada layanan solusi yang ada. Trend teknologi informasi ini akan semakin berguna di tahun 2017.

Machine Learning adalah cabang lanjutan Artificial Intelligent (AI), yang mencakup sistem lebih canggih seperti mampu memahami, mempelajari, memprediksi, beradaptasi, dan berpotensi beroperasi secara mandiri. Machine learning ini diprediksi mampu mengubah perilaku masa depan, yang mengarah pada penciptaan perangkat dan program yang lebih cerdas. Gartner memprediksi AI dan Machine Learning akan lebih banyak digunakan pada robot, kendaraan mandiri, elektronik untuk konsumen, virtual personal assistants, dan smart advisors.

1.Sejarah Machine Learning

Sejak pertama kali komputer diciptakan manusia sudah memikirkan bagaimana caranya agar komputer dapat belajar dari pengalaman. Hal tersebut terbukti pada tahun 1952, Arthur Samuel menciptakan sebuah program, game of checkers, pada sebuah komputer IBM. Program tersebut dapat mempelajari gerakan untuk memenangkan permainan checkers dan menyimpan gerakan tersebut kedalam memorinya.

Istilah machine learning pada dasarnya adalah proses komputer untuk belajar dari data (learn from data). Tanpa adanya data, komputer tidak akan bisa belajar apa-apa. Oleh karena itu jika kita ingin belajar machine learning, pasti akan terus berinteraksi dengan data. Semua pengetahuan machine learning pasti akan melibatkan data. Data bisa saja sama, akan tetapi algoritma dan pendekatan nya berbeda-beda untuk mendapatkan hasil yang optimal.

2.Belajar Machine Learning

Machine Learning merupakan salah satu cabang dari disiplin ilmu Kecerdasan Buatan (Artificial Intellegence) yang membahas mengenai pembangunan sistem yang berdasarkan pada data. Banyak hal yang dipelajari, akan tetapi pada dasarnya ada 4 hal pokok yang dipelajari dalam machine learning.

1. Pembelajaran Terarah (Supervised Learning)

2. Pembelajaran Tak Terarah (Unsupervised Learning)

3. Pembelajaran Semi Terarah (Semi-supervised Learning)

4. Reinforcement Learning

3.Aplikasi Machine Learning

Contoh penerapan machine learning dalam kehidupan adalah sebagai berikut.

1. Penerapan di bidang kedoteran contohnya adalah mendeteksi penyakit seseorang dari gejala yang ada. Contoh lainnya adalah mendeteksi penyakit jantung dari rekaman elektrokardiogram.

2. Pada bidang computer vision contohnya adalah penerapan pengenalan wajah dan pelabelan wajah seperti pada facebook. Contoh lainnya adalah penterjemahan tulisan tangan menjadi teks.

3. Pada biang information retrival contohnya adalah penterjemahan bahasa dengan menggunakan komputer, mengubah suara menjadi teks, dan filter email spam.

Salah satu teknik pengaplikasian machine learning adalah supervised learning. Seperti yang dibahas sebelumnya, machine learning tanpa data maka tidak akan bisa bekerja. Oleh karena itu hal yang pertama kali disiapkan adalah data. Data biasanya akan dibagi menjadi 2 kelompok, yaitu data training dan data testing. Data training nantinya akan digunakan untuk melatih algoritma untuk mencari model yang cocok, sementara data testing akan dipakai untuk mengetes dan mengetahui performa model yang didapatkan pada tahapan testing.

Dari model yang didapatkan, kita dapat melakukan prediksi yang dibedakan menjadi dua macam, tergantung tipe keluarannya. Jika hasil prediksi bersifat diskrit, maka dinamakan proses klasifikasi. Contohnya klasifikasi jenis kelamin dilihat dari tulisan tangan (output laki dan perempuan). Sementara jika kelurannya bersifat kontinyu, maka dinamakan proses regresi. Contohnya prediksi kisaran harga rumah di kota Bandung (output berupa harga rumah).







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