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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Bulletin of Computer Science Research Indo-MathEdu Intellectuals Journal
Sutri, Ridwan
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Computer Science & IT Economics, Econometrics & Finance Education Mathematics Social Sciences

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Klasifikasi Buah Kelapa Muda, Kelapa Tua, dan Buah Naga Menggunakan Pendekatan Hybrid PCA-KNN Sutri, Ridwan; Ramadhanu, Agung
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 1 (2025): February 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i1.2581

Abstract

 Abstract: This study discusses the classification method of young coconuts, old coconuts, and dragon fruits using a hybrid Principal Component Analysis (PCA) and K-Nearest Neighbors (KNN) approach. This approach aims to improve the accuracy and efficiency of fruit classification based on visual and texture features. The research data were taken from fruit images processed using PCA for dimension reduction, followed by the KNN algorithm for classification. The test results showed that the combination of PCA and KNN was able to provide high accuracy, with an average accuracy value reaching 96%. Keyword: fruit classification, PCA, KNN, image processing.Abstrak: Penelitian ini membahas metode klasifikasi buah kelapa muda, kelapa tua, dan buah naga menggunakan pendekatan hybrid Principal Component Analysis (PCA) dan K-Nearest Neighbors (KNN). Pendekatan ini bertujuan untuk meningkatkan akurasi dan efisiensi dalam klasifikasi buah berdasarkan fitur visual dan tekstur. Data penelitian diambil dari citra buah yang diproses menggunakan PCA untuk reduksi dimensi, dilanjutkan dengan algoritma KNN untuk klasifikasi. Hasil pengujian menunjukkan bahwa kombinasi PCA dan KNN mampu memberikan akurasi tinggi, dengan nilai rata-rata akurasi mencapai 96%. Kata kunci: klasifikasi buah, PCA, KNN, pengolahan citra.
Pemanfaatan Teknologi Informasi Sebagai Media Inovatif Dalam Pendidikan Kewirausahaan di Era Digital: Kajian Systematic Literature Review Menggunakan Metode PRISMA Sutri, Ridwan; Veri, Jhon
Indo-MathEdu Intellectuals Journal Vol. 6 No. 4 (2025): Indo-MathEdu Intellectuals Journal
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/imeij.v6i4.3446

Abstract

Digital transformation has significantly influenced educational approaches, including entrepreneurship education. This study aims to examine the use of information technology as an innovative medium in entrepreneurship education in the digital era through a Systematic Literature Review (SLR) using the PRISMA method. A total of 100 articles were collected from various academic databases such as Google Scholar, ScienceDirect, and IEEE Xplore, and after screening, 70 relevant articles were selected for analysis. The results show that the integration of information technology—such as e-learning, Learning Management Systems (LMS) aims to identify commonly used data analysis techniques in a systematic literature review (SLR) approach based on the PRISMA method, business simulations, and social media—can enhance students’ learning motivation, creativity, and entrepreneurial skills. Technology also enables more flexible, interactive, and contextual learning. However, several challenges remain, including limited infrastructure and the readiness of educators to adopt technological tools effectively. This study concludes that the utilization of information technology is a crucial strategy for developing adaptive and future-oriented entrepreneurship education.
Prediksi Jumlah Kebutuhan Biji Kopi Berdasarkan Pola Konsumsi Konsumen dengan Algoritma Apriori Sutri, Ridwan; Hendrik, Billy; Sovia, Rini
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.757

Abstract

Coffee bean prediction is needed for optimal inventory management to maintain efficiency. This data grouping is taken from customer shopping consumption patterns. Based on the research aims to predict the amount of coffee bean needs based on consumer consumption patterns by applying the Apriori algorithm. Utilization of processed transaction data can provide what steps should be taken in the future. Based on this, this study aims to predict the amount of coffee bean needs based on consumer consumption patterns with the Apriori algorithm. The Apriori algorithm forms association rules based on a combination of data indicators used. These data indicators are sourced from Freehand Coffee. Based on the use of the Apriori algorithm in predicting coffee bean needs based on consumer consumption patterns, the results showed that the Apriori algorithm is able to provide product recommendations in the form of associative or consumer transaction patterns by collecting transaction data and then experimenting with existing data indicators. The contribution of this research can help Freehand Coffee to estimate coffee bean needs and optimize stock management, this research also helps in selecting drinks based on consumer consumption.
Co-Authors Hendrik, Billy Ramadhanu, Agung Sovia, Rini Veri, Jhon