Kajian dalam buku ini berangkat dari sebuah fenomena ketidakadilan yang semakin masif. Peradilan—mulai tingkat pertama hingga kasasi—sebagai institusi untuk mewujudkan keadilan, ‘mati suri’ dengan mengeluarkan putusan- putusan yang tidak adil. Adagium putusan hakim tidak adil, adalah sebuah stigma yang menggejala dalam proses respons masyarakat. Adil kian absurd di saat peradilan meniadakan eksistensinya menjadi lebih buram dan abu-abu. Studi tentang putusan, khususnya putusan kasasi melibatkan seluruh dari tiga lapisan ilmu hukum yakni filsafat hukum, teori hukum, dan dogmatik hukum. Setiap dari lapisan ini memberikan karakteristik analisisnya masing-masing. Hanya saja, nuansa filsafat hukumnya lebih kental dan mewarnai. Filsafat hukum sebagai metateori dari teori hukum dan mewarnai dogmatik hukum. Akhirnya, masih banyak yang kurang daripada lebihnya. Untuk itu, perlu autokritik dari semua pihak agar buku lebih sempurna. Buku Persembahan Penerbit PrenadaMediaGroup
Pasal 45 ayat (1) Undang-Undang Nomor 11 Tahun 2008 tentang Informasi Transaksi Elektronik dalam Surat Dakwaan Jaksa Penuntut Umum NO. REG. PERKARA: PDM-432/TNG/05/2009. Berdasarkan putusan PN. NO. 1269/PID.B/2009/ PN.
Mit viel Witz bringen Ihnen die Autoren Geraldine Rauch, Konrad Neumann, Ulrike Grittner, Carolin Herrmann und Jochen Kruppa die Prinzipien der Biostatistik näher.
The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes. In this setting, states of nature of the application area under consideration are described by Boolean vectors de ned on some attributes. That is, by data points de ned in the Boolean space of the attributes. It is postulated that there exists a partition of this space into two classes, which should be inferred as patterns on the attributes when only several data points are known, the so-called positive and negative training examples. The main problem in DM&KD is de ned as nding rules for recognizing (cl- sifying) new data points of unknown class, i. e. , deciding which of them are positive and which are negative. In other words, to infer the binary value of one more attribute, called the goal or class attribute. To solve this problem, some methods have been suggested which construct a Boolean function separating the two given sets of positive and negative training data points.
This is due to the wide use of fast and affordable computing power and data storage media and also the gathering of huge amounts of data in almost all aspects of human activity and interest.
This Book Is Mainly Intended For It Students And Professionals To Learn Or Implement Data Warehousing Technologies. It Experiences The Real-Time Environment And Promotes Planning, Managing, Designing, Implementing, Supporting, Maintaining And Analyzing Data Warehouse In Organizations And It Also Provides Various Mining Techniques As Well As Issues In Practical Use Of Data Mining Tools.The Book Is Designed For The Target Audience Such As Specialists, Trainers And It Users. It Does Not Assume Any Special Knowledge As Background. Understanding Of Computer Use, Databases And Statistics Will Be Helpful.
Introduction 249 1.1 What is Data Mining 251 1.2 Definitions 252 1.3 Data Mining
Process 253 1.4 Data Mining Background 254 1.5 Data Mining Models 256 1.6
Data Mining Methods 257 1.7 Data Mining Problems/Issues 260 1.8 Potential ...
