and make decisions appropriately, and make appli-
cations that can analyze deeply on the subjects de-
sired. Researchers (Andri and Tujni, 2015) designed
a Data Warehouse as a library repository that was
implemented using Pentaho Kettle assistive software.
Research (Suprawoto et al., 2017) on integration of
morbidity data of puskesmas patients into the data
warehouse at the district health office in the Bantul,
emphasized on how to integrate outpatient morbidity
data from puskesmas in the Bantul district health of-
fice. Furthermore, the data is further processed to pro-
duce information according to the needs of leaders to
support decision making.
2 METHOD
2.1 Data Collection
The first step in this research is data collection. For
this purpose researchers conducted data collection by
taking data from the library information system (Si-
pusta) which was the object of research and conducted
a literature review to explore information related to
library data management systems and business pro-
cesses.
In this study, researchers used a top-down ap-
proach, this approach begins with defining organiza-
tional goals and policies and then analyzing informa-
tion needs and then down to transaction processing.
Before starting to create a data model for a data ware-
house, identified information and data requirements
specifications available in the Library. The data ob-
tained at this stage are operational data from the cir-
culation of books in the library. Furthermore, a deeper
analysis of the information needs of the leadership is
carried out. Furthermore, the data obtained will be
used as input to the system analysis process.
2.2 System Analysis
The data source used in this study came from a book
circulation database at library. The database taken
consists of book data, library members, loan transac-
tions and library book return transactions. The Data
Warehouse design methodology used in this study
uses the nine-step methodology. The process of in-
tegrating data is carried out with the concept of ETL
(Extracts, Transformation, Loading). Data that has
been integrated and stored in the same format is fur-
ther grouped into the form of dimension tables and
fact tables.
Pentaho Kettle software can be used as a device
to integrate data. Pentaho Kettle provides facilities
for ETL (Extraction, Transformation and Loading)
processes. The main elements of Pentaho Kettle are
Transformation and Job. Transformation is a set of in-
structions to change the input into the desired output.
Whereas Job is a collection of instructions for carry-
ing out transformation. There are three main com-
ponents in Pentaho Kettle namely, Spoon, Pan and
Kitchen. Spoon is the user interface for creating Job
and Transformation. Pan is a tool that functions to
read, change and write data, and Kitchen is a program
that executes jobs.
2.3 System Design
Before designing the system, an analysis of business
processes from the circulation of library collections
in library includes: 1) Member registration (students
and lecturers), 2) Procurement of library collections
(books, journals, magazines), 3) Borrowing books, 4)
Returning books, and 5) Free submission of student
libraries.
After knowing the business processes that occur
in the library, then do the grain selection process. The
selected grain will be used as a fact table in the Data
Warehouse. Based on the business processes that have
been defined, the resulting grains include: the number
of books, the number of members (number of students
and number of lecturers), and the number of books
borrowed.
Next identify and adjust the dimensions associated
with the fact table. From the results of the identifica-
tion of fact tables, 6 dimensions can be determined in
this design, namely: 1) Dimensions of members, 2)
Dimensions of books, 3) Dimensions of time, 4) Di-
mensions of categories, 5) Dimensions of publishers,
and 6) Dimensions of authors.
The next step is to choose a fact table based on
the selection of grains in the previous stage. The fact
table obtained from the analysis consists of borrowing
and returning library collections in book form. The
design of the fact table produced in this study is the
borrowing fact table and the book return fact table.
The loan fact table and the book return fact table can
be seen in Figure-1 and Figure-2.
2.4 Detailed Design Stage
2.4.1 Save Initial Calculations and Fact Tables
Aggregation in the loan fact table is total borrowing of
books based on time (days, weeks, months and years)
and aggregate factual returns of books are total returns
based on time (days, weeks, months and years).
CONRIST 2019 - International Conferences on Information System and Technology
60