Teknik penyusunan dan contoh format Surat Perintah atau Surat Tugas. Contoh Telaah Staf Pns. Contoh Surat Telaahan Staf. Telaahan staf nota dinas, format.

Dari: Kepala Bagian.. April 2017 Perihal: Mohon bantuan SPPD,- 1. Pemerintah Kabupaten.. Pada APBK Tahun Anggaran 2017 melalui DPA SKPK Bagian.. Setdakab.., telah mengalokasikan anggaran untuk kegiatan pengadaan tanah antara lain sebagai berikut: - Ganti rugi tanah untuk perluasan... - Ganti rugi tanah perluasan lokasi...

- Pembebasan Lahan Lapangan... Guna percepatan pelaksanaan kegiatan pengadaan tanah dimaksud, perlu dilakukan peninjauan lokasi pembebasan tanah terhadap lokasi tanah yang akan dibebaskan. Berkenaan dengan maksud tersebut di atas, mohon bantuan SPPD ke lapangan selama 3 (tiga) hari terhitung mulai tanggal. April 2017, sedangkan biaya dibebankan melalui DPA Bagian..Setdakab..

Tahun Anggaran 2017 pada kegiatan pengadaan tanah, rekening Nomor: x.xx.x.xx.xx.xx.xx.x.x.x.xx.xx, kepada:.....

German Credit Data Set Arff Working Average ratng: 8,0/10 7448votes UCI Machine Learning Repository: Statlog (German Credit Data) Data Set Repository Web Statlog (German Credit Data) Data Set Download:, Abstract: This dataset classifies people described by a set of attributes as good or bad credit risks. Comes in two formats (one all numeric). Tekken 7 apk download weeblycom. Also comes with a cost matrix Data Set Characteristics: Multivariate Number of Instances: 1000 Area: Financial Attribute Characteristics: Categorical, Integer Number of Attributes: 20 Date Donated 1994-11-17 Associated Tasks: Classification Missing Values? N/A Number of Web Hits: 335771 Source: Professor Dr. Hans Hofmann Institut f'ur Statistik und 'Okonometrie Universit'at Hamburg FB Wirtschaftswissenschaften Von-Melle-Park 5 2000 Hamburg 13 Data Set Information: Two datasets are provided.

The original dataset, in the form provided by Prof. There may be several options for tools available for a data set. The German Credit Data contains data on 20 variables and the classification whether. Hofmann, contains categorical/symbolic attributes and is in the file 'german.data'.

For algorithms that need numerical attributes, Strathclyde University produced the file 'german.data-numeric'. This file has been edited and several indicator variables added to make it suitable for algorithms which cannot cope with categorical variables. Several attributes that are ordered categorical (such as attribute 17) have been coded as integer.

This was the form used by StatLog. This dataset requires use of a cost matrix (see below). 1 2 ---------------------------- 1 0 1 ----------------------- 2 5 0 (1 = Good, 2 = Bad) The rows represent the actual classification and the columns the predicted classification. It is worse to class a customer as good when they are bad (5), than it is to class a customer as bad when they are good (1).