CONTRACTOR SELECTION DECISION SUPPORT SYSTEM PROJECT ON AUCTION DINAS CIPTA KARYA KABUPATEN INDRAMAYU USING METHOD AHP (Analytic Hierarchy Process) Giana Department of Informatics, Faculty of Engineering and Computer Science University Computer Indonesia Jl. Dipati Ukur No. 112-116 Bandung E-mail :
[email protected]
ABSTRACT Dinas Cipta Karya in local government areas of Indramayu district has the authority to perform duties under Regulation (Perda) No. 1 of 2001 and the Regional Regulation No. 7 of 2001. One of the tasks undertaken Dinas Cipta Karya is building the infrastructure and public facilities and infrastructure of governance in local government areas of Indramayu district. Contractor selection process conducted DGCK Office takes a long time. Besides presenting information on the procurement of goods / services are still done conventionally, so that the missing information about the procurement of goods and services led to the participation of the contractors (participants partners) in the auction held by the Office of public works has become less and less proportionally, so it is necessary a decision support system. In the development process of decision support system for selecting the contractor on the auction Dinas Cipta Karya using data analysis techniques with methods of software development in a waterfall. For the system data stream method use structure method that is using DFD (Data Flow Diagram) in depicting functional model and ERD (Entity Relationship Diagram) to depict the standard data.Untuk model assessment criteria using AHP (Analytic Hierarchy Process) and MAUT (Multi Attribute Utility Theory) with pre-qualification and past- qualification. The results of this study inform the auction data, data ainwijiing, and bidders who pass the prequalification stage and post-stage. The test system consists of alpha testing where this test using black box testing method that focuses on functional requirements and software beta test is test of field by giving questionnaires to the users in the Technical Section of Survey and Planning Office Building Notices of Work with a question referring to the final destination. After alpha and beta testing, can be deduced that the functionality of the system is to produce the output as expected and the user can use it with ease. Keywords: Contractors, Auctions, Decision Support Systems, DFD, ERD, waterfall method, AHP, MAUT.
1. INTRODUCTION Identify the problem of how to build and implement the Decision Support System for Selection of Contractor for the Project on Auction Dinas Cipta Karya Kabupaten Indramayu Purpose and Objectives The purpose of this research is to Build Decision Support System for Selection of
Contractor for the Project on Auction Dinas Cipta Karya Kabupaten Indramayu. The purpose of this study include : 1. Analyze, design, implement and test the contractor selection decision support system at the Department of public works has Indramayu district, which features a rapid assessment of contractors and accurately by using the method of AHP and MAUT, and
2. 3.
access activities in a computerized auction conducted by connecting through the Internet. The use of electronic data storage media that systematically Provide alternative information for selecting the contractor's decision is in accordance with the fast, as well as provide information and interaction on auction at Dinas Cipta Karya.
2. MODEL ANALYSIS, DESIGN AND IMPLEMENTATION In the development process of decision support system for selecting the contractor on the auction Dinas Cipta Karya using data analysis techniques with methods of software development in a waterfall. For the system data stream method use structure method that is using Data Flow Diagrams (DFD) in depicting functional model and Entity Relationship Diagram (ERD) to illustrate data model.
information including a master list, the report data partners, project reports, auction information, ainwijiing information, prequalification information, postinformation, auction reports, reports ainwijiing, pre-qualification statements, reports pascakualiifikasi, pre-qualification approval, post-approval
2.2 Analysis System 1. Calculation AHP The calculation of the pre-qualification criteria and assessment standards pacakualifikasi using AHP (Analytic Hierarchy Process), for example case below: Problem of selecting the contractor conducted by the Office of Office of Cipta Karya Cipta Karya get into trouble choosing one of three contractors that meets the requirements. Public works has decided to create a hierarchy that can be seen figure 1 Pemenang Lelang
SIUJK
BPP
SK
APP
KPK
2.1 General Description of System The identification of this system are as follows users (Adminnistrator, Staff Admin, Leadership, and Partners) to log into the system, then the Administrator is available on page five of them cultivate process master data, see information on auction data, mengolaha standard assessment criteria, see the information list black, account. On master data will be no partner data processing, user data, pre-qualification criteria, criteria for post-, sub. On process of data there are four auction auction auction process that information, ainwijiing information, prequalification information, information on post-, and the Standard Assessment Calculation menu using AHP (Analytic Hierarchy Process), there are three such processes, the assessment criteria for prequalification, post-assessment and assessment criteria post-subcriteria. On this page the admin staff there are five processes, including information on master data, data processing auction, participants prequalification and post-assessment, info blacklist, account, on valuation calculation method used by participants include MAUT (Multi Attribute Utility Theory). On this page there are five process management
Kontraktor A
Kontraktor B
Kontraktor C
Figure 1 Structure of AHP Hierarchy Proof of Tax Payment (CPP), Certificate of Skills (SK), Contract Work Experience (KPK), Deed of Establishment and Changes (APP), SIUJK After preparation of the hierarchy is complete then the next step is to make comparisons between the elements by taking into account the influence of elements on the levels above comparison is done by a scale of 1 to 9. Can be seen in table 1 Table 1 Matrix comparison Krit
siujk
bpp
app
sk
kpk
siujk bpp
1 0.5
2 1
3 2
1 2
1 3
app sk kpk ∑
0.33 1 1 3.83
0.5 0.5 0.33 4.33
1 1 1 8
1 1 1 6
1 1 1 7
Values in Table 1 can be synthesized by adding up the numbers contained in each column, after that the numbers in each cell divided by the number on the relevant column. This process will produce a matrix that has been normal Table 2 Matrix comparison level 2 Krit
siujk
bpp
app
sk
kpk
∑
siujk bpp
0.26 0.13
0.46 0.23
0.38 0.25
0.17 0.33
0.14 0.43
1.41 1.37
app sk kpk
0.09 0.26 0.26
0.12 0.12 0.08
0.13 0.13 0.13
0.17 0.17 0.17
0.14 0.14 0.14
0.64 0.81 0.77
siujk bpp app sk kpk
0.18
5.43
0.91
0.17
5.31
0.42
0.08
5.39
0.54
0.10
5.43
0.52
0.10
5.37
λmaks value can be searched with the following calculation: λmaks
=
1
2
3
n
n
5.43 5.31 5.39
=
5.43 5.37
=
26.93
5
TPV = ∑ row / n Table 3 TPV Value Kriteria
0.96
5
= 5.33
Value of Consistency Index (CI) can be found by calculation as follows:
TPV
maks
CI=
0.18 0.17 0.08 0.10 0.10
n
=
n 1
5.33 5
= 0.08
5 1
Based on the Random Index (RI) for the number of element 5 is 1:12 then the value of consistency ratio (CI) is : CR =
The average value of each line indicates that the level of importance factor for each criterion is: 18%, 17%, 8%, 10%, and 10%. After completion of level 2 matrix is filled and calculated the weight of its priorities, the next step to make comparisons between the matrix element level 3 with respect to its association with the level. This process has the same steps as the process described previously. Consistency Calculation AHP Tabel 4 Normalisasi Matrik Krit
siujk
bpp
app
sk
kpk
∑
siujk
0.18
0.34
0.24
0.10
0.10
0.96
bpp
0.09
0.17
0.16
0.20
0.29
0.91
app sk kpk
0.06 0.18 0.18
0.09 0.09 0.06
0.08 0.08 0.08
0.10 0.10 0.10
0.10 0.10 0.10
0.42 0.54 0.51
Further on the value of each vector multiplication result is divided by the value of each cell in the priority vectors in order to obtain the results as follows:
CI IR
=
0.08
= 0.07
1.12
A value of 0.07 states that the ratio of the consistency of the results of comparative studies above have a constellation of 7%. This value causes the valuation is acceptable as it has been suggested by Saaty 2. Calculation MAUT Calculation of the total weight of the criteria to obtain a global priority globally is a global priority with a combination of AHP and MAUT methods can be done by following these steps: The first step determines an alternative to determine the value of Xij can be seen in table 5 Table 5 Classification Rating No
Kriteria
1
siujk a. Match b. Not Suitable bpp a. Match b. Not Suitable App a. Match
2
3
Classification Rating (Xij) 80 0 80 0 80
2.3 DFD(Data Flow Diagram)
80 0
Info user, password invalid Data login Data login Info rekanan
2.0 Registrasi penyedia jasa
Data rekanan
Info rekanan
Data join lelang prakualifikasi Data join lelang pascakualifikasi Persetujuan Prakualifikasi Persetujuan Pascakualifikasi
Info rekanan
Data login Login staff admin valid Login peserta valid
Data rekanan
Info join lelang prakualifikasi Info join lelang pascakualifikasi Info Prakualifikasi Info Pascakualifikasi
Data pengguna yang dirubah Info pengguna yang dirubah Data rekanan
Data kriteria prakulifikasi Info data kriteria prakualifikasi
Data kriteria pascakuailifikasi Info data kriteria Data subkriteria pascakualifikasi
Info rekanan Data rekanan
3.0 Pengolahan Data Master
Info Data subkriteria
0.18 0.17
11.2 0
bpp
Not Suitable
app
Match
80
0.08
11.2
sk
Match
80
0.10
11.2
Cocok 80 Vi = ∑ (xij * wij)
0.10
11.2 67.2
Data Daftar hitam
Info daftar hitam
Info lelang proyek Info daftar hitam
Data ainwijiing Data lelang proyek
Daftar hitam
Info nilai kriteria prakualifikasi
4.0 Penilaian AHP
Data nilai kriteria prakualifikasi Info nilai kriteria prakualifikasi Data nilai kriteria pascakualifikasi Info nilai kriteria pascakualifikasi Data nilai subkriteria pascakualifikasi Info nilai subkriteria pascakualifikasi
Info id_pengguna, password invalid
Data nilai lelang prakualifikasi
5.0 Lelang
Staff admin panitia
info Join lelang prakualfikai info nilai kriteria prakualfikasi Info Ainwijiing Info nilai pascakuualifikasi info join lelang pascakualifikasi
Info join lelang prakualifikasi
Join lelang prakualifkasi
Info nilai lelang pascakualifikasi
Info nilai lelang prakualifikasi
Nilai prakualifikasi
Info join lelang pascakualifikasi
Info lelang proyek Info join lelang prakualfikai Info nilai kriteria prakualfikasi Info ainwijiing Info Rekaanan Info nilai pascakuualifikasi Info join lelang pascakualifikasi
Info join lelang prakualifikasi
Figure 2 DFD Level 0
2.4 Menu Structure Design
MENU UTAMA
bpp 0.17
app 0.08
sk 0.10
kpk 0.10
PG
K A K B
80 80
80 80
80 80
80 80
0 0
67.2 67.2
K C
80
80
80
Keterangan : Krit = Criteria K = Contraktor PG = Global Priority TR = Not Recommended R = Recommended
80
80
Ket HOME
80.5
TR TR
DATA MASTER
DATA LELANG
STANDAR NILAI
Pengguna
Info Lelang Proyek
Penilaain Prakualifikasi
Daftar Rekanan
Info Ainwijiing
Penilaian Pascakualifiakasi
R Kriteria Prakualifikasi
Info Prakualifiaksi
Kriteria PAscakualifikasi
Info Pascakualifkasi
DAFTAR HITAM
Subkriteria Pascakualifikasi
Figure 3 Menu Structure
Join lelang pascakualifikasi
Info nilai lelang prakualifikasi
Data Lelang proyek Data Join lelang prakualfikai Data nilai kriteria prakualfikas Data Ainwijiing Data join lelang pascakualifikasi Data nilai kriteria pascakualfikasi
Tabel 7 Calculation of Final Score siujk 0.18
Nilai Pascakualifikasi
Data join lelang pascakualfikasi
LOGIN
Krit
Ainwijiing
Info ainwijiing
Info Proyek Info kriteria pascakualifikasi
Info nilai kriteria Data nilai pascakualifikasi kriteria pascakualifikasi
Data nilai lelang prakualifikasi
Jumlah
6.0 Pengolahan Laporan
Info lelang proyek
Lelang Proyek
Data join lelang prakualfikasi
Bobot (wj)
Info kriteria prakualifikasi
Pimpinan panitia
Info rekanan
Data Proyek
Info pengguna
Nilai Xij
Kriteria pascakualifikasi
Biodata Proyek
Data Pengguna
Data nilai kriteria prakualifikasi
Kriteria prakualifikasi
Info nilai subkriteria pascakualifikasi Data nilai subkriteria pascakualifikasi
subkriteria pascakualifikasi
Data Proyek
Info Proyek
Rekanan
Data join lelang prakualifikasi Data join lelang pascakualifikasi Info join lelang prakualifikasi Info join lelang pascakualifikasi
Login administrator valid Login Staff Admin Valid Login pimpinan panitia lelang
pengguna Data pengguna
Info useronline
useronline
Info pengguna
Data kriteria prakulifikasi Data bobot kriteria prakualifikasi Data kriteria pascakuailifikasi Data pengguna Data rekanan Data biodata proyek
Info kriteria prakulifikasi Info kriteria pascakuailifikasi Info pengguna Info rekanan Info biodata proyek Info daftar hitam Info ainwijiing
80 0
kpk
Info id_pengguna, password invalid
Data rekanan
Info id_pengguna, password invalid
Login rekanan
administrator
Info data rekanan
siujk
Penilaian Match
Data Rekanan
MY ACCOUNT
Ganti Password
Logout
Data nilai lelang prakualifikasi
Info Login
80 0
The second step provides an alternative value is shown in table 5 with the weight of the criteria shown in Table 3 by multiplying the value of each alternative and sum weighting criteria and the process can be seen in table 6 Tabel 6 V value calculation Kriteria
Kontraktor Info rekanan
Data login
Info Rekanan
1.0 Login
Data login
Info Login
5
0
Info join lelang pascakualifikasi
b. Not Suitable Sk a. Match b. Not Suitable kpk a. Match b. Not Suitable
4
2 3 4 5
2.5 Design Interface
Agree Simply Agree Less Agree Disagree
8 2 0 0
80 20 0 0
2. Do you agree this auction system can help you in the process of information flow auction? A. Strongly Agree D. Less Agree B. Agree E. Disagree C. Simply Agree No 1 2 3 4 5
Figure 4 Interface
2.6 Implementation Implementation phase is done after doing the analysis stage of design in the system. In the implementation process of making applications require identification of this word is the author of hardware equipment (hardware) and software (software) in completing this research. 1. Processor Dual Core 2.20GHZ 2. RAM 1 GB 3. VGA 256 MB 4. Monitor 15 “with resolution 1024 x 768 Specification of software (software) used to make the application identification of this word is: 1. Operating System Windows XP Profesional 2. MySQL as database 3. PhpMyadmin as interface 4. Macromedia Dreamweaver 8 code dan design interface 5. Mozilla Firefox,Operah, Google Chrome for web browser
3. RESULTS Results of identification of this research can be seen in the tables below: 1. Do you agree that the auction system is built easily learned and used? A. Strongly Agree D. Less Agree B. Agree E. Disagree C. Simply Agree No 1
Keterangan Strongly Agree
Responden 0
% 0
Keterangan Strongly Agree Agree Simply Agree Less Agree Disagree
Responden 7 2 1 0 0
% 80 20 10 0 0
3. Do you agree to the auction conducted on a system built with computer? A. Strongly Agree D. Less Agree B. Agree E. Disagree C. Simply Agree No 1 2 3 4 5
Keterangan Strongly Agree Agree Simply Agree Less Agree Disagree
Responden 0 6 4 0 0
% 0 60 40 0 0
4. Do you agree the process of submission of tender documents on this system using electronic media (the Internet) ? ( jaringan internet ) ? A. Strongly Agree D. Less Agree B. Agree E. Disagree C. Simply Agree No 1 2 3 4 5
Keterangan Strongly Agree Agree Simply Agree Less Agree Disagree
Responden
%
0 6 4 0 0
0 60 40 0 0
5. Do you agree that this system will be more easier for you in conducting the auction? A. Strongly Agree D. Less Agree B. Agree E. Disagree C. Simply Agree No 1 2 3
Keterangan Strongly Agree Agree Simply Agree
Responden
%
0 6 4
0 60 40
4 5
Less Agree Disagree
0 0
0 0
6. Does your partner agree on a system pendaftaraan process is done electronically (online)? A. Strongly Agree D. Less Agree B. Agree E. Disagree C. Simply Agree No 1 2 3 4 5
Keterangan Sangat Seuju Setuju Cukup Setuju Kurang Sertuju Tidak Setuju
Responden
%
0 6 4 0 0
0 60 40 0 0
7.2 Suggestions Based on the above conclusions, the suggestions are expected to be a decision support system development contractor selection at auction Dinas Cipta Karya Kabupaten Indaramayu 1. Adding data security facilities, such as Public Key Infrastructure registration facility (KPI). 2. Adding a news update function work 3. Add a client software for contractors. 4. Integrating employment data that will be auctioned with other agencies in the District Indramayu.
8. REFERENCES
7. CONCLUSIONS AND SUGGESTIONS
1.
7.1 Conclusion
2.
Based on the results of discussions during the research, it can be concluded that have been analyzed, designed, implemented and tested against the contractor selection decision support system project on auction Dinas Cipta Karya kabupaten Indramayu, including: 1. Contractor selection decision support system on the auction Dinas Cipta Karya kabupaten Indramayu contractor to perform the assessment process quickly and accurately by using the method of AHP and MAUT. 2. Contractor selection decision support system on the auction Dinas Cipta Karya kabupaten Indramayu has been computerized and can be accessed through the Internet network. 3. The use of storage media auction data requirements on the contractor selection decision support system on the auction Dinas Cipta Karya kabupaten Indramayu can be done electronically and systematically. 4. Contractor selection decision support system on the auction Dinas Cipta Karya kabupaten Indramayu to provide alternative information on contractor selection decisions quickly and accurately, and can provide information and interaction on auction on Dinas Cipta Karya kabupaten Indramayu
3.
4.
5.
6.
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