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All Journal INOVTEK Polbeng - Seri Informatika Jurnal Sistem Informasi, Manajemen dan Teknologi Informasi LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics
Agus Susilo Nugroho
Universitas An Nuur
Computer Science & IT

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Klasterisasi Menggunakan Algoritma K-Means dan Elbow pada Opini Masyarakat Tentang Kebijakan Sekolah Luring Tahun 2022 Rahmawan Bagus Trianto; Agus Susilo Nugroho; Eko Supriyadi
Jurnal Inovtek Polbeng Seri Informatika Vol 8, No 1 (2023)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v8i1.2756

Abstract

The covid-19 pandemic that swept across the globe had adverse effects in many areas. One of the most affected areas is education in Indonesia. The online learning model became the only option at the time, which had a negative impact on the quality of education in Indonesia. As time went on, conditions are getting better, but there was still a threat of covid-19. In early 2022 governments began to adopt face-to-face or offline learning that attracted opinions on social media. The opinions that are widely written on social media need to be prepared because they could be input to the government. Clustering using the k-meansalgorithm with the elbow method as its optimizer in determining the best cluster number is one of the opinions processing options on social media for measuring and accounting. Data is treated with two approaches: with and without stemming. Applying the elbow method to the k-means algorithm produces a performance of the clustering model with a DBI value of 0.003 with 4 clusters, and a value of SSE 0.331, for data without stemming. On data with treatment using stemming, it has 3 cluster numbers with a value of DBI at 0.003 and SSE at 0426.
Implementasi Metode User-Centered Design Dalam Perancangan UI/UX Aplikasi Voting Kepengurusan Muhammadiyah Cabang Paguyangan Agus Susilo Nugroho; Arif Setia Sandi Ariyanto
Jurnal Sistem Informasi, Manajemen dan Teknologi Informasi Vol. 2 No. 1 (2024): Januari
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/jsimtek.v2i1.603

Abstract

Studi ini bertujuan untuk menguraikan implementasi metode User-Centered Design (UCD) dalam perancangan UI/UX aplikasi Voting Kepengurusan Muhammadiyah Cabang Paguyangan. UCD menjadi landasan untuk memahami secara mendalam kebutuhan, preferensi, dan perilaku pengguna dalam pengembangan aplikasi ini. Dengan kata lain, metode UCD ini membantu dalam perancangan sistem interaktif berdasarkan pengalaman pengguna. Studi ini menjelaskan tahapan-tahapan yang diambil dalam implementasi UCD, mulai dari pengumpulan informasi pengguna potensial hingga penggambaran persona dan perancangan prototipe berbasis hasil penelitian. Melalui pendekatan UCD, penelitian ini menghasilkan desain yang lebih adaptif terhadap kebutuhan pengguna, dengan fokus pada antarmuka yang mudah digunakan dan pengalaman pengguna yang memuaskan. Hasil evaluasi dan pengujian menunjukkan peningkatan signifikan dalam UI/UX aplikasi voting dalam penerapan UCD. Implementasi UCD dalam konteks aplikasi voting Kepengurusan Muhammadiyah Cabang Paguyangan memberikan manfaat dan memastikan aplikasi tersebut dapat diakses dan digunakan secara optimal. Pengguna dengan kelompok usia termuda lebih menguasi dan cepat beradaptasi dalam penggunaan aplikasi E-VoMU (E-Voting Muhammadiyah). Dibuktikan dengan nilai presentase pengujian yang dihasilkan, nilai kemampuan usia muda lebih tinggi jika dibandingkan dua kelompok usia lainnya.
Peringkasan Dokumen Teks Bilingual Sebagai Reduksi Fitur Untuk Klasifikasi Menggunakan Algoritma K-NN Rahmawan Bagus Trianto; Agus Susilo Nugroho
LogicLink Vol. 1 No. 1, June 2024
Publisher : UIN K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v1i1.7801

Abstract

Summarizing text is a step to extract the essence of a text document with no more than half. Summarizing text has an important role in extracting the core information from a document in a more concise form. Summarizing text documents can be used as feature reduction in classifying text documents because it can reduce features that are considered irrelevant. Text documents are summarized using the Term Frequency-Inverse Document Frequency (TF-IDF) method, then classified using the K-Nearest Neighbor (K-NN) algorithm. One of the disadvantages of the K-NN algorithm is that it is not optimal in classification if the k value is not appropriate, as well as the selection of an inappropriate distance calculation method. By testing various k values ​​and using the Euclidean Distance distance measurement method, you can increase the accuracy of text document classification. Text document summarization using the proposed TF-IDF method is proven to increase when classification is carried out with K-NN. From the research results, it was found that the classification accuracy at the compression rate increased by 50% with a k value of 6 to 8 of 95.33%. This shows that text document summarization as feature reduction has a positive role in the classification process using the K-NN algorithm.
Co-Authors Arif Setia Sandi A. Eko Supriyadi Rahmawan Bagus Trianto