Data Flow Data Sources

Goods movement is an important aspect of the transportation system. Freight flow, complemented with the much-researched passenger movement, provides a way for understanding the complete vehicle flow scenario on the highways. Commodity movement prediction has not received much attention because of the lack of sufficient and easily accessible data sources. Most data sources give aggregated commodity movements and, because of the heterogeneity of freight, accurate predictions of truck flows have not been possible. A methodology for calculating the truck flows on the various highways in Massachusetts from interstate commodity flow data is presented. Freight tons originating and ending in Massachusetts have been converted to truck numbers by using a quantitative procedure and distributed to different areas in the state by using employment as an economic indicator variable. The truck flow is assigned to the important highways and validated against existing survey counts. On comparison, a large percentage of the roads show the estimated truck counts are within a tolerable error margin. The research also shows that statewide analyses need to be refined near urban areas because of a variety of complexities involved.

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Analisis Implementasi dan Pemodelan REA (Resource, Event, Agent) Sistem Akuntansi Pada UMKM Di Kabupaten Pasuruan

JAE (JURNAL AKUNTANSI DAN EKONOMI) ◽

10.29407/jae.v4i1.12759 ◽

2019 ◽

Vol 4 (1) ◽

pp. 87

Author(s):

Bagus Hari Sugiharto ◽

Ufi Rumefi

Keyword(s):

Data Flow ◽

Flow Diagram ◽

Flow Data ◽

Data Flow Diagram

Model REA (REA Model) adalah krangka kerja akuntansi alternatif untuk pemodelan sumber daya, peristiwa, dan pelaku (resource,event,agent-REA) perusahaan yang sangat penting, serta hubungan diantara mereka. Jika telah diadopsi, data akuntansi dan nonakuntansi mengenai fenomena ini dapat diidentifikasi, ditangkap, dan disimpan dalam basis data terpusat. Tempat penyimpanan ini, tampilan pengguna dapat dibentuk hingga memenuhi kebutuhan semua pengguna dalam perusahaan (James A. Hall, 2007). Dalam penelitian ini dilakukan analisa terhadap sistem pancatatan keuangan yang selama ini digunakan oleh pelaku UMKM di Kab. Pasuruan untuk menjalankan kegiatan proses bisnisnya. Untuk dapat melihat dengan sistematis dan terstruktur implementasi pencatatan keuangan yang dilakukan oleh pelaku UMKM, maka Model REA peneliti gunakan untuk menjadi nilai ukur dan bentuk hasil implementasi pencatatan keuangan yang terjadi pada pelaku UMKM di Kab. Pasuruan. Dalam proses penelitian, terdapat beberapa tahapan proses mulai wawancara langsung hingga penyusunan rancangan Dokumen Flow, Sistem Flow, Data Flow Diagram (DFD) hingga perancangan ERD (CDM) dan REA. Hasil dari penelitian ini akan mendapat formulasi bentuk sistem pencatatan keuangan yang memang sesuai dan mudah yang selama ini digunakan oleh pelaku UMKM di Kab. Pasuruan, dari formulasi tersebut juga dapat menjadi model dasar untuk digunakan merancang bangun sebuah Aplikasi Sistem Informasi Pencatatan Keuangan untuk mengembangkan menjadi aplikasi pencatatan keuangan ter-otomatisasi.

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Information technology. Cloud computing. Cloud services and devices: Data flow, data categories and data use

10.3403/30313039 ◽

2017 ◽

Keyword(s):

Information Technology ◽

Cloud Computing ◽

Data Flow ◽

Data Use ◽

Cloud Services ◽

Flow Data

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A New Approach in Measuring Local Migration and Population

Canadian Studies in Population ◽

10.25336/p6g324 ◽

2008 ◽

Vol 35 (1) ◽

pp. 27

Author(s):

Zongli Tang

Keyword(s):

Data Sources ◽

Decennial Census ◽

Population Estimates ◽

Flow Data ◽

Migration Flow ◽

New Approach ◽

New Model ◽

Relative Attractiveness

This paper presents a new model for measuring local migration and population and report results of a promising pilot application to Massachusetts. This model operationalizes Ravenstein’s classic “push-pull” paradigm, which posits that local migration is determined by the area’s relative attractiveness or a compound function of distinct factors that push migrants out of the area or pull them in. The attraction factors and changes are measured using varied data sources, including decennial census migration flow data and data on group quarters and school enrollments. This model yields timely population estimates with accuracy superior to the corresponding estimates based on the Census Bureau’s methodology. Such results warrant further applications to test and refine this promising approach.

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