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Journal : International Journal of Advances in Data and Information Systems

Application of K-Means Clustering Algorithm for Determination of Fire-Prone Areas Utilizing Hotspots in West Kalimantan Province Nabila Amalia Khairani; Edi Sutoyo
International Journal of Advances in Data and Information Systems Vol. 1 No. 1 (2020): April 2020 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v1i1.13

Abstract

Forest and land fires are disasters that often occur in Indonesia. In 2007, 2012 and 2015 forest fires that occurred in Sumatra and Kalimantan attracted global attention because they brought smog pollution to neighboring countries. One of the regions that has the highest fire hotspots is West Kalimantan Province. Forest and land fires have an impact on health, especially on the communities around the scene, as well as on the economic and social aspects. This must be overcome, one of them is by knowing the location of the area of ??fire and can analyze the causes of forest and land fires. With the impact caused by forest and land fires, the purpose of this study is to apply the clustering method using the k-means algorithm to be able to determine the hotspot prone areas in West Kalimantan Province. And evaluate the results of the cluster that has been obtained from the clustering method using the k-means algorithm. Data mining is a suitable method to be able to find out information on hotspot areas. The data mining method used is clustering because this method can process hotspot data into information that can inform areas prone to hotspots. This clustering uses k-means algorithm which is grouping data based on similar characteristics. The hotspots data obtained are grouped into 3 clusters with the results obtained for cluster 0 as many as 284 hotspots including hazardous areas, 215 hotspots including non-prone areas and 129 points that belong to very vulnerable areas. Then the clustering results were evaluated using the Davies-Bouldin Index (DBI) method with a value of 3.112 which indicates that the clustering results of 3 clusters were not optimal.
Aspect-Based Sentiment Analysis of Hotels in Bali on Tripadvisor Using BERT Algorithm Dimas Samodra Bimaputra; Edi Sutoyo
International Journal of Advances in Data and Information Systems Vol. 4 No. 1 (2023): April 2023 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1284

Abstract

The covid pandemic that began in 2020 has caused enormous losses worldwide, including in Indonesia. Human-to-human contact is the source of the transmission of the covid virus, so the government urges people to maintain cleanliness when interacting. Bali is a popular destination for foreign and domestic visitors in Indonesia. Hospitality businesses in Bali unquestionably face a high risk of covid transmission; consequently, changes in hotel business processes are unavoidable; the implementation of new business processes can have a negative effect on business performance. In order to maintain Bali's reputation as the most popular tourist destination in Indonesia, the government must evaluate the performance of several hotel services that have implemented new business processes. The Aspect-Based Sentiment Analysis (ABSA) methodology can be utilized for performance evaluation. One of the finest algorithms for analyzing text, Bidirectional Encoder Representations from Transformer (BERT), is required for sentiment analysis. The data consists of textual customer evaluations of hotels in Bali that have implemented a new protocol or Standard Operational Procedure (SOP), retrieved from the Tripadvisor website. In the form of a number of evaluations of various aspects of the hotel, the research results can assist the government in analyzing the performance of hotels in Bali based on predetermined criteria.
Co-Authors A. Rahmat Rosyadi Adinda Inez Sang Ahmad Ainul Yakin Ahmad Setiawan Ali Khoirul Hidayat Anggie Randy Pramuditha ANI SAFITRI Arifah Batubara, Qurratul Ain Aris Haryanto Armansyah Halomoan Tambunan Asep Rizki Aulia Putri, Meilani Barkah Akbar Budi Hartono Budi Hartono Chika Enggar Puspita Darmawan, Dwiki Dimas Samodra Bimaputra Dodih Dwi Yuliaji Edy Hartulistiyoso Fadil Mochamad Ramdan Fadlurrahman, M Asri Fakhrurroja, Hanif Fauzan Radifan Shidiq Fauzy, Restu Firmansyah, Yusup Fitriani Fitriani Fitriani Fitriyah, Atiqotun Frisca Febriyani Kurniawan Gigih Bayu Setyawan Gilang Erlangga Hablinur Al-Kindi Hablinur Alkindi Hafiza, Sifha Hasan Santosa Hasibuan, Musta'anul Husaini Hidayat, Ali Husaini Hasibuan, Musta'anul Iqbal Santosa Irfan Darmawan Iwan Tri Riyadi Yanto Kahfi Ahadian Mutaqin Khoiriah Widia Pawesti Mamat Rahmat Mamat Rahmat MAMAT RAHMAT Michael Yudhea Saragih Muhammad Iqbal Furqonul Hakim Muhammad Nanang Prayudyanto Muhammad Ridwan Nabila Amalia Khairani Nafis Qurrotul Aini Nurhayati, Immas Nuruddin Nashrullah Oktariani Nurul Pratiwi Oktoriansyah, Rinaldi Panji Romadon, Joe Pariatiara, Dicky Nur Pramono, Gatot Eka Pramono, Gatot Eka Prayuda, Ilham Vega Rachmadita Andreswari Rahmat Fauzi Rd. Rohmat Saedudin Revo Faris Saifuddin Roy Waluyo Rusydi Rusydi Ryan Darmawan Salundik Setya Permana Sutisna Setya Permana Sutisna Sigit Dwi Pramono Silo Mardadi Suganda, Cecep Sulha . SUMADI SUMADI Sunarya, Derivan Susila Wahyu Sutisna, Setya Syamsurizal, Adi Syed Humayon Shah Tegar, Muhammad Tika Hafzara Siregar Tika Hafzara Siregar Tika Hafzara Siregar Titing Suharti Turmudi Tutut Herawan Yoga Hermawan Yusuf Sopian Zaki, Abdul Zamil Anugrah