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All Journal Jurnal Teknologi dan Manajemen Informatika SMATIKA KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal Ilmiah KOMPUTASI JURNAL MEDIA INFORMATIKA BUDIDARMA INTECOMS: Journal of Information Technology and Computer Science IJISTECH (International Journal Of Information System & Technology) JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jurnal Mantik Jurnal Teknologi Informasi dan Multimedia Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Teknik Informatika C.I.T. Medicom JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Teknologi Informatika dan Komputer IJISTECH KLIK: Kajian Ilmiah Informatika dan Komputer JUSTIN (Jurnal Sistem dan Teknologi Informasi)
Agus Iskandar
Universitas Nasional
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences

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Journal : Building of Informatics, Technology and Science

 1 
Sistem Pendukung Keputusan Kelayakan Penerima Bantuan Dana KIP Kuliah Menggunakan Metode ROC-EDAS Agus Iskandar
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2265

Abstract

Education is one of the keys in achieving the ideals of the nation's children, there are often economic or financial constraints for the Indonesian people who are unable to be able to attend higher education stages, this makes the ideals of the nation's generation to be smart and have the potential to build the nation. being more advanced becomes hampered, this phenomenon makes the government take action in making an assistance program in the form of a card called the smart Indonesia card or (KIP), the provision of scholarship funds in the smart Indonesia card program of course has terms and conditions that can be met to get the right and disbursement of funds, the number of students who want to get KIP (Smart Indonesia Cards) aid funds makes the manager really have to manage the eligibility of recipients of KIP (Smart Indonesia Cards) funds, a procedure that often happens fraudulently and requires a process of calculating the eligibility of receiving aid. ana KIP (Smart Indonesia Card) which is still less accurate makes the manager of the selection of aid recipients have to take into account the eligibility of the beneficiary very well so that the beneficiary is really the right person. A decision support system is used to obtain more precise and accurate results based on the calculation of a hybrid method which is a combination method so that the results obtained are of higher quality, the method used is the ROC-EDAS hybrid method. The results obtained in using this method are found an alternative named isty with the highest score of 0.207622 who became a student who deserved to receive tuition assistance KIP funds
Analisa Perbandingan Complate Linkage AHC dan K-Medoids Dalam Pengelompokkan Data Kemiskinan di Indonesia Rifqi Habibi Sachrrial; Agus Iskandar
Building of Informatics, Technology and Science (BITS) Vol 5 No 2 (2023): September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i2.4310

Abstract

The poverty rate in Indonesia has increased from 9.54 percent in March 2022 to 9.57 percent in September 2022 due to inflation and low wages and people's incomes. To overcome this problem, steps such as providing social assistance, creating decent jobs, and increasing wage standards are needed to increase people's purchasing power and reduce poverty in the future. The government needs to pay special attention to provinces with high poverty rates through special programs and efforts to increase income and the economy in these areas. Data Mining is a solution in solving this problem by utilizing the clustering method which is known as the clustering method. The clustering method used in this study is the AHC method and the K-Medoids method. In order to determine the provinces with the highest number of poor people, the AHC and K-Medoids clustering methods will be applied separately so that the final results of each will be analyzed. The results of the analysis show the formation of three clusters with different cluster locations. The application of the AHC method resulted in cluster 2 with the largest number of provinces, namely 22 provinces, followed by cluster 0 with 9 provinces, and cluster 1 with only 3 provinces. While the application of the K-Medoids method resulted in cluster 1 with the largest number of provinces, namely 22 provinces, followed by cluster 0 with 9 provinces, and cluster 2 with only 3 provinces. Although the location of the clusters is different between the two methods, the number of provinces in the cluster is the same so that a cluster with a total of 3 provinces is declared the province with the largest number of poor people.
Co-Authors Aditya lutfi Irawan Aei Dhelwis Okdhianthy Putri Agung Triayudi Aldi Ardiansyah Amelia H Ikhlas Arie Gunawan Arya Dimas Setiadi Avicienna Adhi Narendro Purnomo badriawan sukma Bagas Prayoga Bimo Anggoro Seno Binsar Pamungkas Batu Bara Dandi Putra Denissa A. Putri Dhea Andarweni Eka Permana Putra Eldy Dwi Sentosa Fahmi Apriliansyah Fauziah Fauziah Firdo Andri Saputra Galih Rakasiwi Ghifari Yusuf Abdillah Haidar Ali Heru Saputro Iskandar Fitri Iskandar Fitri Iskandar Fitri Iskandar Fitri Iwan Wahyudin M. Iwan Wahyuddin M. Iwan Wahyudin M. Mustaqim Mauludani Muhammad Mochammad Arya Darmawan Moh. Iwan Wahyuddin Muhammad Naufal Rifqi Muhammad Rizky Hamdan Naufal Rifqi Niam Shofi Oky Triadi Sampurno Olipa Sarta Matilda Purba Puji Ariyanto Raihan Abdi Negoro Rian Rasyidhi Richard Ronaldo Marbun Rifqi Habibi Sachrrial Rifqi Habibi Sachrrial Rosyidah Rahmah Septi Andryana Shandy Nurjaman Sri Intan Maharani Ucuk Darusalam Vendy Blessing Gulo Yoga Septian Nugraha