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All Journal Jurnal Sains dan Teknologi Jurnal Simetris Jurnal Buana Informatika Jurnal Teknologi Register: Jurnal Ilmiah Teknologi Sistem Informasi EMITTER International Journal of Engineering Technology JOIN (Jurnal Online Informatika) Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer INTEGER: Journal of Information Technology Informatika Pertanian Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control SINTECH (Science and Information Technology) Journal Prosiding Seminar Nasional Sains dan Teknologi Terapan Jurnal ULTIMATICS Journal of Information Technology and Computer Engineering Jurnal EDUTECH Undiksha JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Mnemonic Journal of Soft Computing Exploration Journal La Edusci JUSTIN (Jurnal Sistem dan Teknologi Informasi) JGHTT Indonesian Journal of Learning and Instructional Innovation
Febri Liantoni, Febri
Universitas Sebelas Maret
Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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Journal : Journal of Soft Computing Exploration

 1 
Prediction of PTIK students' study success in the first year using the c4.5 algorithm Astuti, Asri; Maryono, Dwi; Liantoni, Febri
Journal of Soft Computing Exploration Vol. 5 No. 1 (2024): March 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i1.237

Abstract

The purpose of this study is to determine the factors that influence the success of student studies in the first year through data mining research using the C4.5 algorithm. This research is a type of quantitative research. This research uses student data of a study program as much as 85 data which will be processed using the Weka application. The data obtained will then be processed using the C4.5 data mining method to produce a decision tree containing rules to predict the success of student studies in the first year. The best result using percentage-split 80% obtained an accuracy of 82.35% as well as the rules contained in the decision tree. The most important factor in determining the success of studies in first-year students is the selection of college entrance pathways. Other factors that become other determinants are education before college, intensity of communication with friends, class year, intensity of off-campus organizations, and plans to change study programs.
Comparative study of marker-based and markerless tracking in augmented reality under variable environmental conditions Sulistiyono, Mulia; Hasyim, Jaka Wardana; Bernadhed, Bernadhed; Liantoni, Febri; Sidauruk, Acihmah
Journal of Soft Computing Exploration Vol. 5 No. 4 (2024): December 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i4.503

Abstract

Augmented reality (AR) technology integrates virtual content into real environments using two main methods: marker-based and markerless tracking. Marker-based tracking relies on printed markers for object placement, while markerless uses environmental features for flexibility and accuracy. This research aims to evaluate the combined impact of environmental factors-distance, angle, and lighting-on these two methods. The Multimedia Development Life Cycle (MDLC) methodology was applied by testing 72 combinations of indicators: distance (5-120 cm), angle (30°, 45°, 90°), and light color (red, blue, green, yellow) using Xiaomi Note 8 and Google Pixel 4. Results show markerless tracking is superior in all conditions, achieving a 94.4% success rate on both devices. In contrast, marker-based tracking only achieved 72.2% (Xiaomi Note 8) and 77.8% (Google Pixel 4). Markerless tracking was optimally performed from 50 cm away and up close, while marker-based tracking degraded in performance at long distances and red lighting. Markerless tracking proved to be more reliable and consistent, suitable for dynamic and diverse environments, while marker-based methods remained relevant for short distances and controlled lighting. These findings provide guidance for AR developers in choosing a tracking methodology according to application needs.
Co-Authors Abin Suarsa Acihmah Sidauruk Agus Efendi Agus Santoso Ananda, Rizky Putu Anas, Rizky Chairul Andini, Ratih Friska Dwi Annisa, Fitri Nur Aris Budianto, Aris Astuti, Asri B.M.A.S. Anaconda Bangkara Bambang Yuwono Bataona, Daniel Silli Bernadhed, Bernadhed Chaizara, Rezza Fariszal Hisyam Chastine Fatichah Cucuk Wawan Budiyanto Dwi Maryono Hasyim, Jaka Wardana Hendro Nugroho, Hendro Hidayatulah Himawan Hidayatulloh, A. Nururrochman Luky Agus Hermanto, Luky Agus Majid, Desva Fitranda Maruf, Irma Rachmawati Maryanti Mulia Sulistiyono Myrtha, Risalina Nanik Suciati Nugroho, Hendro Nurcahya Pradana Taufik Prakisya Palupi, Dian Exsi Prabaswara, Muhammad Arden Prakisya , Nurcahya Pradana Taufik Prakisya, Nurcahya Pradana Taufik Pratama, Kalistus Haris Purnama, Bayu Rizkhy Candra Puspanda Hatta Putri, Nanditya Vianti Qurin, Milani Tanya Rahmawati, Weny M. Ramadhan, Firdaus Ditio Ramadhan, Raqael Fisabillah Rifki Indra Perwira Rosetya, Septiyawan Rosihan Ari Yuana, Rosihan Ari Rustanto, Diki Wahyudi Salsabila, Zahra Khalila Santoso, Agus Adi Saputro, Muhammad Naufal Adi Setiyani, Susanti Simanjuntak, Ondihon Siswoyo, Risya Ines Putri Sukmagautama, Coana Sukmaningrum, Agy Hafidzah Wahyudi, Yusuf Rois Weny Mistarika Rahmawati Yusfia Hafid Aristyagama