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All Journal Jurnal Eksplora Informatika Jurnal Teknik Informatika C.I.T. Medicom KETIK : Jurnal Informatika ADA Journal of Information System Research
Bu'ulolo, Efori
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Computer Science & IT

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Implementasi Algoritma Knuth-Morris-Pratt Pada E-Katalog Perpustakaan Marbun, Nasib; Rozy, Ahmad; Pasaribu, Sutrisno Arianto; Bu'ulolo, Efori; Purba, Bister; Hasibuan, Nisma Novita; Riansyah, Muhammad
KETIK : Jurnal Informatika Vol. 2 No. 02 (2024): November
Publisher : Faatuatua Media Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70404/ketik.v2i02.143

Abstract

E-katalog perpustakaan adalah salah satu aplikasi yang membantu pengguna untuk mencari koleksi buku atau informasi perpustakaan dengan lebih efisien melalui sistem berbasis elektronik. Salah satu tantangan dalam pengembangan e-katalog adalah meningkatkan kecepatan dan akurasi dalam pencarian data, khususnya dalam pencocokan string (teks) yang digunakan untuk mencari informasi katalog. Algoritma Knuth-Morris-Pratt (KMP) merupakan salah satu algoritma pencocokan string yang efisien untuk menyelesaikan masalah ini. Penelitian ini bertujuan untuk mengimplementasikan algoritma KMP dalam sistem e-katalog perpustakaan untuk meningkatkan performa pencarian data dan meminimalkan waktu respons. Hasil penelitian ini menyimpulkan bahwa Algoritma knuth morris pratt dapat membantu mempercepat pencocokan string, sehingga memperbaiki waktu respons dan efisiensi sistem pencarian data. Dengan demikian, penerapan algoritma ini dapat menjadi solusi yang baik dalam pengembangan e-katalog perpustakaan yang lebih cepat dan efisien.
Penentuan Mahasiswa Penerima Bantuan Uang Kuliah Tunggal dengan K-NN Syahputra, Rian; Bu'ulolo, Efori
Eksplora Informatika Vol 13 No 1 (2023): Jurnal Eksplora Informatika
Publisher : Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/eksplora.v13i1.797

Abstract

Pada proses penentuan mahasiswa yang layak memperoleh bantuan Uang Kuliah Tunggal (UKT) di Univeristas Budi Darma sering mengalami kesulitan karena kuota yang yang tersedia tidak sebanding dengan calon mahasiswa penerima dan kriteria data mahasiswa yang sama. Pada penelitian ini metode penelitian yang dilakukan dimulai dari studi literature, identifikasi masalah, pengumpulan data, normalisasi, penerapan algoritma, hasil penelitian dan publikasi. Algoritma yang digunakan yaitu algoritma K-NN, dimana data yang digunakan terdiri atas data training dan data testing. Dalam proses pencarian jarak terdekat maka menggunakan model Euclidean Distance. Sebelum dilakukan proses pencarian jarak terdekat maka data dinormalisisakan terlebih dahulu, tujuan agar ada keseimbangan antara kriteria yang digunakan sehingga memperoleh hasil yang lebih akurat dan optimal. Hasil dari penelitian ini adalah calon penerima bantuan UKT setelah diklasifikasi dengan algoritma K-NN dinyatakan tidak menerima.
Implementasi Metode TOPSIS Dalam Sistem Pendukung Keputusan Penilaian Kinerja Guru Honor Selvira, Rani; Tinambunan, Miko Putra Haposan; Bu'ulolo, Efori
ADA Journal of Information System Research Vol. 1 No. 2 (2024): February 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/adajisr.v1i2.39

Abstract

This research aims to implement the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method in the Decision Support System (SPK) for honorary teacher performance assessment. Problems in assessing the performance of honorary teachers are the main focus of this research. The aim is to create a more objective and structured SPK, which is able to provide a more accurate assessment of the performance of honorary teachers. In this research, honorary teacher performance data was collected from various sources, such as observation results, assessments from school principals, and evaluations from colleagues. The data is then processed using the TOPSIS method to give weight to each assessment criterion, which includes aspects of knowledge, teaching skills, discipline and the teacher's contribution to student progress. The research results show that the implementation of the TOPSIS method in the SPK for honorary teacher performance assessment has been successful. The developed SPK can provide more objective and consistent recommendations in assessing the performance of honorary teachers. This helps school principals and other authorities in making decisions regarding promotions, awards or training required by honorary teachers. By using the TOPSIS method, the performance assessment of honorary teachers becomes more structured and objective. This has the potential to increase transparency and accountability in the honorary teacher performance assessment process. The results of this research provide an important contribution to the development of a better performance assessment system for honorary teachers, which will ultimately have a positive impact on the quality of education at various levels. The results obtained were obtained by A1 with a value of 0.9038 as the highest value.
Determining Initial Centroid in K-Means using Global Average and Data Dimension Variance Bu'ulolo, Efori
Jurnal Teknik Informatika C.I.T Medicom Vol 17 No 5 (2025): November : Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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

Abstract

The selection of the right initial centroid greatly affects the quality of clustering results in the K-Means algorithm. This study proposes a new approach in determining the initial centroid by utilizing the global average and variance of data dimensions. The global average is used to represent the overall center position of the data, while the variance of dimensions provides information on the distribution of each feature. This method is tested using three-dimensional synthetic data (X, Y, Z) with 121 data, and compared with the random initialization approach. The results show that the global average and variance-based method produces more balanced clusters, lower Sum of Squared Error (SSE) values, and the highest Silhouette Score value (0.65), as well as faster convergence. Compared to two random initialization scenarios, this method is proven to be more stable in separating clusters based on the distribution of low, medium, and high values. This approach makes an important contribution to the development of a more consistent and effective K-Means initialization strategy, especially for low to medium-dimensional numerical datasets.
Co-Authors Hasibuan, Nisma Novita Nasib Marbun Pasaribu, Sutrisno Arianto Purba, Bister Rian Syahputra Riansyah, Muhammad Rozy, Ahmad Selvira, Rani Tinambunan, Miko Putra Haposan