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All Journal BERKALA SAINSTEK Sistemasi: Jurnal Sistem Informasi Jurnal Pilar Nusa Mandiri Journal of Informatics Development
Hizham, Fadhel Akhmad
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Electrical & Electronics Engineering Mathematics Physics

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Journal : Journal of Informatics Development

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Sentiment Analysis of Ijen Crater Reviews using Decision Tree Classification and Oversampling Optimization Hizham, Fadhel Akhmad; Asyari, Hasyim; Urrochman, Maysas Yafi
Journal of Informatics Development Vol. 3 No. 1 (2024): Oktober 2024
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/jid.v3i1.1399

Abstract

Sentiment analysis is a text mining technique that classifies content as positive, negative, or neutral polarity in each sentence or document. These lines or papers may be user reviews assessing the quality of a product or material supplied to them. The purpose of this study is to better understand the function of sentiment analysis in assessing evaluations of the Ijen Crater tourist destination based on Google Maps user comments. This study is conducted in four steps, beginning with data gathering in the form of Google Maps evaluations obtained by data scraping. Following data collection, text preparation includes case folding, tokenization, stopword elimination, and stemming. Following text preprocessing, the next stage is imbalaced data optimization, which involves modifying the minority class samples to be nearly equal to the majority class by randomly duplicating minority class samples. Then, each review is categorized according to sentiment using the Decision Tree (DT) method. Testing has done by comparing DT without optimization and DT with SMOTE-ENN and ADASYN optimization. The result shown DT with SMOTE-ENN optimization has the best accuracy improvement with 1.62%, from 96.94% to 98.56%.
Analysis and Visualization of Data on the Impacts of Covid-19 Globally and Locally Iqbal, Muhammad; Yudha, Julius Chaezar Bernard Buana; Umimah, Reza Nazilatul; Hizham, Fadhel Akhmad
Journal of Informatics Development Vol. 3 No. 2 (2025): April 2025
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/jid.v3i2.1513

Abstract

The COVID-19 pandemic has had a profound impact on multiple aspects of human life, including food supply, mental health, and healthcare service management. This study aims to examine these impacts by applying a combination of data analysis methods such as data preprocessing, exploratory data analysis (EDA), predictive algorithms, and data visualization. The datasets utilized include information related to mental health conditions, food security, and COVID-19-related health statistics. The findings indicate a significant increase in mental health issues, such as anxiety and depression, as well as disruptions in food supply chains that have adversely affected global food security. Moreover, data visualization has proven to be a valuable tool in supporting decision-making processes in healthcare management. However, most implementations remain limited in scope and are often confined to internal agency use. Therefore, this study recommends further development in integrating data sources, enhancing the application of predictive algorithms, and optimizing data visualization for more effective decision-making in managing global health crises.
Pengembangan Metode Information Retrieval dan Haversine Formula untuk Rekomendasi Penentuan Klinik di Kabupaten Jember Hizham, Fadhel Akhmad; Ginardi, Raden Venantius Hari
Journal of Informatics Development Vol. 1 No. 1 (2022): Oktober 2022
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/jid.v1i1.896

Abstract

Klinik merupakan fasilitas tempat orang berobat dan memperoleh advis medis serta tempat mahasiswa kedokteran melakukan pengamatan terhadap kasus penyakit yang diderita para pasien. Saat ini, hadirnya virus Corona (COVID-19) membuat banyak klinik menampung pasien yang terpapar virus tersebut. Dari kasus tersebut, rekomendasi penentuan klinik sangat diperlukan karena kondisi yang sangat darurat dan kasus positif yang bertambah setiap harinya. Pada penelitian ini, ditambahkan metode information retrieval, yaitu metode TF-IDF dan BM25 untuk menentukan rekomendasi klinik di Kabupaten Jember berdasarkan kata pencarian dari penggunanya dan diurutkan berdasarkan kemiripan (similarity) dari yang terbesar hingga yang terkecil. Sementara metode Haversine Formula digunakan untuk memilih klinik dengan jarak yang ditentukan oleh pengguna sebelumnya Penentuan rekomendasi klinik yang menggunakan metode gabungan information retrieval (similarity) + haversine dilakukan dengan formulasi rata-rata peringkat antara metode haversine dengan metode gabungan, dan formulasi normalisasi nilai similarity maupun nilai haversine. Hasilnya, ada 7 klinik yang menempati peringkat terbaik untuk metode gabungan dengan formulasi rata-rata peringkat, dan ada 47 klinik yang menempati peringkat terbaik untuk metode gabungan dengan formulasi normalisasi.
Co-Authors Asy'ari, Hasyim Choiri, Achmad Firman Firmansyah, Diksy Media Ginardi, R.V. Hari Hasyim Asyari Muhammad Iqbal Murni, Cahyasari Kartika Umimah, Reza Nazilatul Urrochman, Maysas Yafi Yanuar Nurdiansyah, Yanuar Yudha, Julius Chaezar Bernard Buana