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All Journal Foristek Jurnal Teknologi dan Manajemen Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) ScientiCO : Computer Science and Informatics Journal BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Advance Sustainable Science, Engineering and Technology (ASSET) The Indonesian Journal of Computer Science
Rizka Ardiansyah
Program Studi S1 Sistem Informasi, Fakultas Teknik, Universitas Tadulako, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Nursing Public Health Social Sciences Veterinary Other

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Journal : The Indonesian Journal of Computer Science

 1 
Pemanfaatan TOPSIS (Technique For Order Preference By Similarity To Ideal Solutions) untuk Rekomendasi Objek Wisata di Provinsi Sulawesi Tengah Ulhak, Muhamad Zia; Pratama, Septiano Anggun; Ardiansyah, Rizka; Angreni, Dwi Shinta
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4404

Abstract

Tourism is one of the key sectors in driving economic growth in Central Sulawesi. To support the enhancement of tourism, this research developed a web-based decision support system using the TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) to provide tourism destination recommendations. The system assists users in selecting tourist destinations based on several relevant criteria, such as facilities, accessibility, cost, cleanliness, and safety. By applying the TOPSIS method, the system can rank tourism destinations by comparing the distances between positive and negative ideal solutions. This implementation is expected to help tourists make more informed and accurate decisions regarding the destinations they wish to visit and contribute positively to the development of tourism in Central Sulawesi.
Artikel Analisis Sentimen terhadap Resolusi Genjatan Senjata PBB 2023: Studi pada 10 Negara Penolak Resolusi Konflik Israel-Palestina Qofifa, Sitti Nurlaili; Ardiansyah, Rizka; Joefrie, Yuri Yudhaswana; Wirdayanti; Lapatta, Nouval Trezandy
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4405

Abstract

The Israeli-Palestinian conflict is the longest conflict that still has not found a bright spot. In December 2023 the UN again gave the latest resolution with the title “Armistice” this resolution received pros and cons from UN member states. The number of pro countries is 150 countries, contra as many as 10 countries and 23 countries abstain. This study aims to investigate whether the 10 countries that voted against the UN resolution represent the interests of their people or only represent the interests of their country. This research approach uses sentiment analysis on platform X with the Support Vector Machine method. Data was taken from March 2024 to the latest data, 137,447 data were obtained with 5 countries using non-English languages and 4 countries using English. Each data from these countries was successfully classified into positive and negative classes. The survey was conducted on 9 countries with an average positive sentiment of 34.82% and an average negative sentiment of 77.41%. The results of this research show that the decisions made by the 10 countries that rejected the resolution represent the voice of their people.
PERBANDINGAN AKURASI LINEAR REGRESSION DAN SUPPORT VECTOR REGRESSION DALAM PREDIKSI SUHU RATA-RATA Lesnusa, Gideon Namlea; Dwi Shinta Angreni; Ardiansyah, Rizka
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3944

Abstract

The weather in Indonesia varies significantly and is influenced by geographical location, topography, and regional climate. Weather patterns differ between the western and eastern parts of Indonesia. This study explores time series models to predict weather data in Palu City, a region that is complex due to various weather factors. The focus is on the unique weather patterns reflected by the geography and topography of Palu City. Evaluation was conducted on time series models, including Linear Regression and Support Vector Regression (SVR), to estimate weather conditions in Palu City. The evaluation results show that the SVR model has an RMSE of 0.6302, while linear regression has an RMSE of 0.6328. This research has the potential to improve early warning and decision-making regarding extreme weather
Co-Authors ., Rezki Afiah, Nurul Anggun Ain, Moch. Zukhruf Amriana Andi Hendra Anita Ahmad Kasim Anita, Ayu Deny Wiria Nugraha Dwi Shinta Angreni Dwi Wijaya, Kadek Agus Dwiwijaya, Kadek Agus Hafriadi, Fajar Dzulnufrie Hajra Rasmita Ngemba Indrajaya, Muhammad Aristo Iskandar Iskandar JULIAN WITJAKSONO Komang, Gusti Lamasitudju, Chairunnisa Lesnusa, Gideon Namlea Maroso, Akwan Mohamad Irfan, Mohamad Mohammad Yazdi Pusadan Muhammad Akbar Mutiara Sari Ngurah, Gusti Nouval Trezandy Lapatta Parenrengi, Andi Fathur Alamsyah A. Pratiwi, Inten Sakti Putra, Ryan Adi Qofifa, Sitti Nurlaili Rahim, Mohammad Arham Rahmah Laila Raivandy, I Made Randhy Rini Septiani Rinianty, Rinianty Rumampuk, Viola Gracella Ryfial Azhar, Ryfial Sahril Sahril Septiano Anggun Pratama Sondakh, Clivent Gerhard Syahrullah Syahrullah Syaiful Hendra Therry, Alvin Christian Davidson Ulhak, Muhamad Zia Wirdayanti Yazdi Pusadan, Mohammad Yudhaswana, Yuri Yulianti, Indira Yuri Yudhaswana Joefrie Yusuf Anshori