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All Journal Techno.Com: Jurnal Teknologi Informasi CogITo Smart Journal
Rojakul, Rojakul
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Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering

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Analisis Sentimen Popularitas Capres dan Pilpres pada Media Sosial Twitter: Perbandingan Algoritma SVM, KNN, dan Naïve Bayes Rojakul, Rojakul; Sumardianto, Sumardianto; Wibowo, Arief
Techno.Com Vol. 23 No. 2 (2024): Mei 2024
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v23i2.10135

Abstract

Untuk memaham bagamana tokoh publk dpersepskan dan drespon oleh masyarakat d era meda sosial, analsis sentimen sangat berguna. Ini terutama berlaku karena popularitas tokoh publik meningkat di era meida sosial. Tujuan dari penelitian ini adalah untuk mengatasi masalah tersebut dan memberikan pemahaman yang bermanfaat tentang bagiamana masyarakat bertindak terhadap pemlhan presiden dan capres yang saat ini sangat diperdebatkan di medai sosial, serta bagiamana hal tu berdampak pada opn publk secara keseluruhan, khususnya d Twtter. Stud n bertujuan untuk mengkategorkan tweet emosonal ke dalam kategor postf atau negatf dengan menggunakan algortma pembagan terstruktur sepert Support Vector Machnes (SVM), Nave Bayes (NB), dan K-Nearest Neghbor. Hasl pengujan menunjukkan bahwa algortma NB memlk tngkat akuras 94,62% dan press 100%, mengalahkan SVM dan K-NN dalam menyelesakan kasus kepercayaan.
Implementation of SAW and AHP in Decision-Making Models for Credit Provision in Cooperatives Rojakul, Rojakul; Sumardianto, Sumardianto; Triyono, Gandung
CogITo Smart Journal Vol. 10 No. 2 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i2.662.418-432

Abstract

The research aims to overcome the difficulties in selecting the best members of the Al-Amin Independent Corporation, focusing on the challenges faced in determining the best members in the process of giving credit and payments on time. However, many members fail to meet their obligations or fail to pay their contributions smoothly, leading to credit freezes and decreased cooperative income. The cause of a member's failure to pay quotas has not been identified by the current candidate admission selection system. The methods used are Simple Additive Weighting (SAW) and Analytical Hierarchy Process (AHP) applied in the Decision Support System (DSS) model. The results of the research showed the effectiveness of the SAW method in identifying the best and optimal alternative with the highest value on V2 of 4. The AHP method has successfully determined the priority weight and the level of importance for member selection criteria including Activity (0.50), Savings (0.13), Guarantee (0.09), Loan (0.10), Disbursement (0.10), Time Period (0.07). The research provides insight to decision-makers in cooperatives makes important contributions, especially in the granting of credit, and affirms the importance of objective methods in the selection of members.
Co-Authors - Sumardianto Arief Wibowo Triyono, Gandung