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All Journal PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak
Luthfiyyah, Ibtihal Qomariyyah
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Computer Science & IT

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Pengelompokan Penyebaran Covid-19 Di Provinsi Jawa Barat Menggunakan Metode Clustering K-Medoids Luthfiyyah, Ibtihal Qomariyyah; Sari, Betha Nurina
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 2 (2024): September
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i2.10544

Abstract

Covid-19 merupakan suatu penyakit yang menjangkiti sistem pernapasan manusia dan memiliki kemampuan penularan yang sangat cepat. Provinsi Jawa Barat menjadi salah satu daerah yang terkena dampak pandemi Covid-19. Jumlah masyarakat terkonfirmasi virus Covid-19 di Jawa Barat yang masih bertambah hari demi hari. Oleh karena itu, diperlukan adanya pengelompokkan tingkat kerawanan penyebaran Covid-19 khususnya di Provinsi Jawa Barat menggunakan data dari website resmi pemerintah Provinsi Jawa Barat dengan menggunakan 5 atribut, yaitu nama_kab_kota, konfirmasi_total, konfirmasi_sembuh, konfirmasi_meninggal, dan konfirmasi_aktif. Penelitian ini bertujuan untuk mengidentifikasi pola penyebaran Covid-19 untuk mendukung pengambilan keputusan yang lebih efektif di tingkat regional. Metode penelitian melibatkan proses data mining yaitu pemahaman bisnis, pemahaman data, persiapan data, pemodelan, evaluasi, dan penyebaran berdasarkan metodologi CRISP-DM. Proses modeling menggunakan algoritma K-Medoids dengan 3 cluster sesuai dengan zona warna pemerintah. Hasil penelitian ini menunjukkan 3 cluster, yaitu cluster hijau merupakan jumlah kasus yang minimal dengan 16 Kabupaten/Kota. Cluster kuning merupakan mulai waspada akan jumlah kasus dengan 6 Kabupaten/Kota. Cluster merah merupakan kasus sudah sangat parah dengan 5 Kabupaten/Kota. Hasil pengujian Silhouette Coefficient yang menguji n_cluster = 2,3,4, dan 5 menunjukkan bahwa n_cluster=3 merupakan cluster yang terbaik dengan nilai sebesar 0.77.  
Pengelompokan Penyebaran Covid-19 di Provinsi Jawa Barat menggunakan Metode Clustering K-Medoids Luthfiyyah, Ibtihal Qomariyyah; Sari, Betha Nurina
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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

Abstract

Covid-19 is a disease that infects the human respiratory system and has a high-speed transmission ability. West Java Province is one of the areas affected by the Covid-19 pandemic. The number of people confirmed with the Covid-19 virus in West Java is still increasing daily. Therefore, it is necessary to group the level of vulnerability to the spread of Covid-19, especially in West Java Province, using data from the official website of the West Java Provincial Government using 5 attributes, namely district_city_name, total_confirmation, confirmed_recovered, confirmed_death, and confirmed_active. This study aims to identify the pattern of the spread of Covid-19 to support more effective decision-making at the regional level. The research method involves a data mining process, namely business understanding, data understanding, data preparation, modeling, evaluation, and deployment based on the CRISP-DM methodology. The modeling process uses the K-Medoids algorithm with 3 clusters according to the government's color zone. The results of this study show 3 clusters, namely the green cluster is the minimum number of cases with 16 districts/cities. The yellow cluster is starting to be alert to the number of cases with 6 districts/cities. The red cluster is a very severe case with 5 districts/cities. The results of the Silhouette Coefficient test that tested n_cluster = 2, 3, 4, and 5 showed that n_cluster = 3 is the best cluster with a value of 0.77.
Analisis Sentimen Mahasiswa Terhadap Kurikulum Literasi Digital di Universitas Singaperbangsa Karawang Menggunakan Naïve Bayes Luthfiyyah, Ibtihal Qomariyyah; Sari, Betha Nurina; Ridwan, Taufik
Jurnal PROCESSOR Vol 19 No 1 (2024): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2024.19.1.1669

Abstract

Implementation of the Digital Literacy Curriculum at University of Singaperbangsa Karawang (Unsika) as a concrete step considering the importance of digital literacy. Curriculum evaluation is an important step in ensuring the effectiveness of learning. Currently there is no mechanism from Unsika to encourage students to provide feedback on curriculum implementation. One way is by sentiment analysis, which requires sentiment analysis using the Naïve Bayes algorithm which contributes to providing feedback on curriculum evaluation. This sentiment analysis process uses the CRISP-DM (Cross Industry Standard Process for Data Mining) methodology. In an effort to obtain student perceptions, a survey was conducted using a questionnaire. The minimum number of respondents determined using the Slovin formula is 388. In this study the amount of data used was 591. There is an imbalance in the data, to overcome this an oversampling technique can be used using ADASYN (Adaptive Synthetic Sampling Approach). The data has been cleaned to produce 347 positive sentiments and 176 negative sentiments. The results of this research show the best model and word frequency in the form of visualization of words that play an important role in each sentiment category for use in curriculum evaluation. Of the eight model scenarios tested, the model trained with the Naïve Bayes algorithm using a division of 90% training data and 10% testing data with the application of ADASYN became the best model with an accuracy of 89%, precision 100%, recall 85%, and f1-score 92%.
Co-Authors Betha Nurina Sari Taufik Ridwan, Taufik