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JROCK (Journal Research on Computing Knowledge)
Published by Universitas Sembilanbelas November Kolaka
ISSN : -     EISSN : 30893038     DOI : -
Core Subject : Science,
Computer Science & IT
JROCK (Journal Research on Computing Knowledge) adalah jurnal ilmiah yang berfokus pada publikasi penelitian di bidang Teknologi Informasi, Sistem Komputer, dan Ilmu Komputasi. JROCK bertujuan untuk menyediakan platform bagi para peneliti, akademisi, dan praktisi untuk berbagi ide, inovasi, dan kontribusi terbaru di dunia teknologi dan komputasi. Jurnal ini menerima artikel dalam Bahasa Indonesia dan Bahasa Inggris, mencakup berbagai topik seperti Kecerdasan Buatan, Big Data, Rekayasa Perangkat Lunak, IoT, Keamanan Siber, dan Teknologi Baru yang lainnya. Semua artikel yang diterima akan melalui proses peer review untuk memastikan kualitas dan orisinalitas penelitian.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 13 Documents
 1   2 
Sistem Pendukung Keputusan Seleksi Peserta Pelatihan di UPTD BLKK Kolaka dengan Metode TOPSIS Hidayatullah, Muh. Ilham; Sunyanti, Sunyanti; Syaban, Kharis
Journal Research on Computing Knowledge Vol. 1 No. 2 (2025): Maret 2025
Publisher : Fakultas Teknologi Informasi

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Abstract

The participant selection process for training at UPTD BLKK Kolaka remains manual, resulting in inefficiency and potential subjectivity in decision-making. This paper formulates a Decision Support System (DSS) utilizing the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique to resolve this issue. This method is selected for its ability to yield optimal participant recommendations by evaluating proximity to both positive and negative ideal solutions. The system is constructed utilizing PHP and MySQL for the storage of participant data and computation outcomes. The research phases encompass needs analysis, system design, implementation, and testing using Black Box Testing. The outcomes of manual and system calculations demonstrate consistency in preference values, confirming that the TOPSIS method effectively identifies the most appropriate training participants. This approach accelerates the selection process, enhancing transparency and objectivity. The deployment of a TOPSIS-based Decision Support System is anticipated to enhance efficiency and precision in decision-making, guaranteeing that chosen participants fulfill the requisite requirements
Optimasi Prediksi Hasil Belajar Algoritma dengan Metode kNN Syahraeni Rahmadi; Jimsan; Muh. Hajar Akbar
Journal Research on Computing Knowledge Vol. 1 No. 2 (2025): Maret 2025
Publisher : Fakultas Teknologi Informasi

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Abstract

Penentuan performa akademik mahasiswa merupakan aspek penting dalam evaluasi pendidikan, terutama dalam mata kuliah Algoritma yang membutuhkan pemahaman logis dan analitis yang kuat. Penelitian ini menerapkan metode k-Nearest Neighbors (kNN) untuk mengklasifikasikan hasil belajar mahasiswa berdasarkan parameter akademik, seperti nilai tugas, nilai UTS, nilai UAS, jumlah latihan koding, dan tingkat kehadiran. Dataset yang digunakan terdiri dari 53 mahasiswa, dengan proses klasifikasi dilakukan melalui perhitungan Euclidean Distance untuk menentukan jarak antara data uji dan data latih. Hasil penelitian menunjukkan bahwa metode kNN dapat mengklasifikasikan mahasiswa dengan akurasi yang baik, di mana mahasiswa dengan tingkat latihan koding yang tinggi dan kehadiran yang konsisten cenderung memiliki performa akademik lebih baik. Dengan penerapan yang tepat, metode ini dapat digunakan sebagai alat bantu dalam analisis akademik serta membantu pendidik dalam mengidentifikasi mahasiswa yang membutuhkan bimbingan lebih lanjut.
Optimasi Pemilihan Destinasi Wisata Prioritas Menggunakan Metode ROC dan Weighted Product Mardianto; Muhallim, Muhlis
Journal Research on Computing Knowledge Vol. 1 No. 2 (2025): Maret 2025
Publisher : Fakultas Teknologi Informasi

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Abstract

The choice of suitable tourist locations is a key element in improving the competitiveness of regional tourism. Nonetheless, unstructured and subjective selection methodologies may result in inefficiencies in the planning and development of tourism regions. This research seeks to enhance the selection of priority tourism locations with a Decision Support System (DSS) employing the Weighted Product (WP) method and criteria weighting via the Rank Order Centroid (ROC). Five factors were employed in the assessment: destination distinctiveness, accessibility, supporting infrastructure, economic viability, and media prominence. Each alternative destination was evaluated on a scale of 1 to 5 and subsequently analyzed using the WP method to derive preference scores. The findings indicated that Destination A received the highest preference score of 0.232, so it is suggested as the principal site for development. This method is effective in aiding policymakers in formulating objective, systematic, and data-driven alternative choices

Page 2 of 2 | Total Record : 13

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