Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika)
Utama, Deffa Ferdian Alif
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Pengelompokan Pemenang Tender dengan Metode K-Means Clustering (Kasus Layanan Pengadaan Secara Elektronik Bagian Pengadaan Barang/Jasa Kabupaten Semarang) Utama, Deffa Ferdian Alif; Purnomo, Hindriyanto Dwi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 8, No 1 (2024): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v8i1.765

Abstract

Electronic Procurement Services (LPSE) is a work unit formed specifically to serve the Goods/Services Procurement Work Unit (UKPBJ), responsible for carrying out the procurement process electronically. currently, the method of selecting providers has become e-regular tendering which is all done online, the evolution of electronic tendering systems has grown rapidly along with advances in information technology. This research uses the data of tender winners that have been done Data Mining before from LPSE Semarang Regency, from 2011 to 2022 with the population of completed tenders, which aims to group the data of tender winners to find out what procurements have been completed and the role of local entrepreneurs / companies. total of 2127, using only 238 random data samples referring to the method of Isaac and Michael. using the method of Machine Learning, namely the Unsupervised Learning method processed with the K-Means Clustering Algorithm, the results obtained are the Construction of Public Facilities in the form of types of Construction Work, such as roads, tourist attractions, facilities for villages and others both made new, upgrades and others. then comes from the Semarang Regency area by showing 8 out of 13 or two-thirds with a percentage of 62%. This information is useful as an overview, education, information, knowledge for all of us in the Semarang Regency area and all the people of Indonesia as well as helping the economic development of the region and all other regional areas to the National.
Pengelompokan Pemenang Tender dengan Metode K-Means Clustering (Kasus Layanan Pengadaan Secara Elektronik Bagian Pengadaan Barang/Jasa Kabupaten Semarang) Utama, Deffa Ferdian Alif; Purnomo, Hindriyanto Dwi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 8, No 1 (2024): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v8i1.765

Abstract

Electronic Procurement Services (LPSE) is a work unit formed specifically to serve the Goods/Services Procurement Work Unit (UKPBJ), responsible for carrying out the procurement process electronically. currently, the method of selecting providers has become e-regular tendering which is all done online, the evolution of electronic tendering systems has grown rapidly along with advances in information technology. This research uses the data of tender winners that have been done Data Mining before from LPSE Semarang Regency, from 2011 to 2022 with the population of completed tenders, which aims to group the data of tender winners to find out what procurements have been completed and the role of local entrepreneurs / companies. total of 2127, using only 238 random data samples referring to the method of Isaac and Michael. using the method of Machine Learning, namely the Unsupervised Learning method processed with the K-Means Clustering Algorithm, the results obtained are the Construction of Public Facilities in the form of types of Construction Work, such as roads, tourist attractions, facilities for villages and others both made new, upgrades and others. then comes from the Semarang Regency area by showing 8 out of 13 or two-thirds with a percentage of 62%. This information is useful as an overview, education, information, knowledge for all of us in the Semarang Regency area and all the people of Indonesia as well as helping the economic development of the region and all other regional areas to the National.
Co-Authors Hindriyanto Dwi Purnomo