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All Journal MEKTEK Foristek Jurnal MEKANIKAL AKSIOMA Jurnal Pendidikan Matematika Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Informatika dan Teknik Elektro Terapan MEKTRIK International Journal of Artificial Intelligence Research JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sistem Cerdas JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal ScientiCO : Computer Science and Informatics Journal BERNAS: Jurnal Pengabdian Kepada Masyarakat Aksioma Advance Sustainable Science, Engineering and Technology (ASSET) The Indonesian Journal of Computer Science Riau Jurnal Teknik Informatika AKSIOMA
Yuri Yudhaswana Joefrie
Information Technology Department, Faculty Of Engineering, Universitas Tadulako, Jl. Soekarno Hatta No KM 9 Palu 94148, Central Sulawesi, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering 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 
Implementasi Sistem Informasi Bimbingan Konseling Pelanggaran Siswa Dengan Sistem Point Wahyu Setiawan; Septiano Anggun Pratama; Wirdayanti; Yuri Yudhaswana Joefrie
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3958

Abstract

Computer technology is currently advancing rapidly. Almost every sector of work relies on computer technology for data processing, including in the field of education, particularly in counseling services. Based on monitoring and direct interactions with teaching staff at SMK Negeri 3 Palu, it is revealed that there is currently no system available that can manage student violation incident data optimally. Instead, the process still relies on manual recording, where teachers record student violations and then submit them to the Counseling Unit (BK). Manual information management is vulnerable to the risk of data loss and information overlap. To address this situation, this research intends to develop a Web-Based Student Violation Counseling Information System with a Point System at SMK Negeri 3 Palu, focusing on improving efficiency and transparency in the point allocation process. In this study, the approach applied is the Waterfall model. With the adoption of this system, the identification of the most frequently occurring student violations becomes more detailed.
Penerapan Algoritma Dijkstra Untuk Menentukan Rute Terpendek Dalam Distribusi Darah Di Palang Merah Indonesia Kota Palu Berbasis Mobile Dival Maulana, Muhammad; Hendra, Andi; Yudhaswana, Yuri; Anshori, Yusuf; Ar. Lamasitudju, Chairunnisa
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4454

Abstract

Efficient blood distribution is crucial for the Indonesian Red Cross (PMI) to save lives. This research develops a mobile-based blood distribution system that utilizes Dijkstra's Algorithm to determine the shortest delivery routes. The system is specifically designed for PMI in Palu City, assisting drivers in finding optimal paths and monitoring blood stock availability in hospitals in real-time. A prototyping method was employed for development, while the Google Maps API enables accurate route visualization. Research results indicate that Dijkstra's Algorithm reduces blood distribution time by 15-20% compared to the previously used manual methods. Additionally, this system facilitates better management of blood stocks and increases distribution speed. Blackbox testing ensures that all features function according to specifications. This research contributes to enhancing blood distribution efficiency at PMI, with the hope of minimizing the risk of blood shortages. Future research is recommended to further develop the system on a larger scale to address more complex distribution challenges.
Analisis Sentimen Terhadap Presiden Terpilih Dimedia Sosial Twitter (X) Menggunakan Algoritma Support Vector Machine Ono, Jumaita; Anshori , Yusuf; Yudhaswana Joefrie , Yuri; Yazdi Pusadan, Mohammad; Syahrullah
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4388

Abstract

The current elected presidents of Indonesia are Prabowo and Gibran, with several work programs and visions and missions that are still being discussed on various social media, especially on Twitter. Based on the problems in this research, the Support Vector Machine method was applied with the dataset used amounting to 2000 data obtained from Twitter social media using scraping techniques, and divided into five scenarios, namely positive, very positive, neutral, negative and very negative. Data were tested from 100 datasets, 500 datasets, 1000 datasets, 1500 datasets, and 2000 datasets. The accuracy results obtained from 100 data were 0.40% accuracy, 0.08% precision, and 0.20% recall. The second test used 500 data with an accuracy of 0.67%, precision of 0.33% and recall of 0.24%. The third test used 1000 data with an accuracy of 0.73%, precision of 0.52% and recall of 0.29%. The fourth test used 1500 data with an accuracy of 0.74%, precision of 0.41% and recall of 0.29%. The fifth test with the highest level of accuracy uses 2000 data, with an accuracy of 0.75%, precision of 0.47%, and recall of 0.30%
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
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.
Co-Authors Abdul Mahatir Najar Alda Nur Pradinda Amalia, Liza Amriana Amriana Andi Hendra Andipa Batara Putra Anita Ahmad Kasim Arsita, Tiara Juli Deny Wiria Nugraha Dival Maulana, Muhammad Dodu, Erwin Dwi Shinta Angreni Dwimanhendra, Muhammad Rifaldi Hajra Rasmita Ngemba Hanama, Ikhsan Wahyudin Hasanuddin Hasanuddin Ihwan, Abib Raifmuaffah Indrajaya, Muhammad Aristo Isminarti, Isminarti Junus Widjaja Lamadjido, Moh. Raihan Dirga Putra Lamasitudju, Chairunnisa Liza Amalia Meidji, Farah Nabila Mohammad Yazdi Pusadan Muh Alif Alghifari Muhammad Yazdi Muhammad Yazdi Nadyanti, Nadyanti Ngurah, Gusti Ningsih, Alief Surya Nouval Trezandy Lapatta Ono, Jumaita Parenrengi, Andi Fathur Alamsyah A. Pradinda, Alda Nur Pratiwi, Inten Sakti Prihastomo, Enggar Dwi Protus Peter Kalatiku Protus Pieter Kalatiku Putra, Ryan Adi Qofifa, Sitti Nurlaili Rahmah Laila Rini Septiani Rizka Ardiansyah Rumampuk, Viola Gracella Ryfial Azhar Sahril Sahril Septiano Anggun Pratama Sondakh, Clivent Gerhard Syahrullah Syahrullah Syahrullah Syaiful Hendra Therry, Alvin Christian Davidson Wahyu Setiawan Widyati, Made Ayu Sri Wirdayanti Wisanti, Widya Yusuf Anshori Yusuf Anshori Zulkifli Zulkifli