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All Journal TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Computing and Informatics Research Bulletin of Information System Research
Dedy Hartama
STIKOM Tunas Bangsa, Pematang Siantar
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Penerapan K-Means Clustering Dalam Menentukan Banyaknya Desa/Kelurahan Menurut Keberadaan dan Jenis Industri Kecil dan Mikro (Desa) Fira Fania; Agus Perdana Windarto; Dedy Hartama
Bulletin of Information System Research Vol 1 No 1 (2022): Desember 2022
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Processing Industry is an economic activity that carries out activities to change a basic item mechanically, chemically, or by hand so that it becomes finished / semi-finished goods, and or goods of less value to goods of higher value, and which are closer to the end user. This study aims to model the grouping in determining the Number of Villages / Villages According to the Existence and Types of Small and Micro Industries (Villages). This research is a reference, especially for the government, so that the potential for employment in this industry group can continue to be developed and optimized. Government contributions can be realized through the creation of stable social, economic and political conditions and through the policy of determining the direction of business development of Micro and Small Industries. The data from this study were taken from a government statistical data provider website, BPS (Statistics Indonesia) www.bps.go .id. This research uses the K-Mens method and is tested with RapidMiner software to create 3 clusters, namely high, medium and low level clusters and see what the contents of the cluster are. From the research results obtained by high cluster data centroids namely ((2151.79), ( 1494.34), (1135.76), moderate clusters ((406.64), (525.06), (616,218), and low clusters ((455,361), (345,523), (1074.09), (176,434), (1410,34), (243,749), (295,151), (463,266), (5868,13), (9344.07), (170,925), (8818,85), (1031,65), (433,61), (5985,505), (1630,75), (367,928), (119,082), (560,907), (172,333), (545,342), (226,174), (776,643), (1880,857), (172,333), (545,342), (226,174), (776,643), (1880,853), (1880,853), (18,80,853), (1880,853), (1880,853), (1880,853), (1880,853), (1880,853) ), (1482.39), (115,573), (232,734), (187.04), (142,884), (455,674), (441,934) With this analysis expected to be input and information for the government of each region to pay more attention to regions micro / small industrial areas occupying low clushter (C1) positions in order to improve industrial quality in the region.
Analisis Pola Minat Siswa Lulusan SMU/SMK Untuk Melanjutkan Kuliah dengan Menggunakan Algoritma C4.5 Yuli Septya Ayunda; Dedy Hartama; Muhammad Ridwan Lubis; Indra Gunawan; Muhammad Rafai
TIN: Terapan Informatika Nusantara Vol 4 No 9 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i9.4880

Abstract

STIKOM Tunas Bangsa is one of the best private universities in the city of Pematangsiantar. With so many universities in the city of Pematangsiantar, it certainly creates competition in attracting prospective new students. In order to maintain the number of students each year, universities must know what factors are the main drivers for prospective students to continue their studies at STIKOM Tunas Bangsa. The aim of this research is to determine the main factors for high school/vocational school graduate students in continuing their studies at STIKOM Tunas Bangsa. Data was obtained from questionnaires which were then processed using data mining with the C4.5 algorithm and tested with Rapid Miner software. Based on the research results, it can be concluded that there are six (6) patterns produced in cases of interest in prospective students who will study at STIKOM Tunas Bangsa, where three (3) of these rules result in interest decisions and three (3) rules result in no interest decisions. One of the resulting rules is if Recommendation = Never, and Suitability of Department = Appropriate, then the result is Interest. Recommendations from local people are the main supporting factor for high school/vocational school graduate students to continue studying at STIKOM Tunas Bangsa Pematangsiantar.
Klasifikasi Peminatan Topik Keilmuan Dalam Penyelesaian Studi Menggunakan Algoritma Naive Bayes Waldi Setiawan; Dedy Hartama; Muhammad Ridwan Lubis; Ihsan Syajidan; Agus Perdana Windarto
Journal of Computing and Informatics Research Vol 3 No 2 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i2.1200

Abstract

Academic expertise is a subject of study taught at the university level to assist students in completing their thesis writing, thereby enabling them to successfully complete their graduate studies. The chosen academic specialization aligns with the vision and mission of each program and can have a positive impact on the university. Students' chosen fields of expertise in completing their studies may either align or not align with the program's vision and mission. The variables used in this research are GPA, MKRV1, MKRV2, and Academic Expertise. The aim of this research is to determine how many students select an academic topic that aligns with the program's vision and mission, particularly in this case, the Computer Science program, as they complete their studies. The Naïve Bayes algorithm is employed in this research, yielding an accuracy rate of 98.11%. This research can provide valuable insights for STIKOM Tunas Bangsa Pematang Siantar to understand the extent to which students from other programs choose academic expertise that aligns with the vision and mission of each program.
Co-Authors Agus Perdana Windarto Fira Fania Ihsan Syajidan Indra Gunawan Muhammad Rafai Muhammad Ridwan Lubis Waldi Setiawan Yuli Septya Ayunda