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All Journal Jurnal Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Teknik ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science Majalah Ilmiah Matematika Komputer Jurnal Buana Informatika JUTI: Jurnal Ilmiah Teknologi Informasi International Journal of Advances in Intelligent Informatics Jurnal Teknobisnis INFORMAL: Informatics Journal Register: Jurnal Ilmiah Teknologi Sistem Informasi EMITTER International Journal of Engineering Technology Journal of ICSAR Math Didactic: Jurnal Pendidikan Matematika Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Eksplora Informatika SISFO International Journal of Supply Chain Management CCIT (Creative Communication and Innovative Technology) Journal jurnal teknik informatika dan sistem informasi Indonesian Journal of Electrical Engineering and Computer Science Makara Journal of Technology Sewagati
Buliali, Joko Lianto
Departemen Teknik Informatika, Institut Teknologi Sepuluh Nopember, Kampus ITS, Keputih, Sukolilo, Surabaya 60111
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Transportation

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Journal : IPTEK The Journal for Technology and Science

 1 
FRIEND RELATIONSHIP WEIGHTING FOR ACADEMIC PERFORMANCE PREDICTION ON UNIVERSITY DELEGATION AT FOLLOWING COMPETITION Bisono, Eva Firdayanti; Fahrudin, Tora; Buliali, Joko Lianto
IPTEK The Journal for Technology and Science Vol 30, No 2 (2019)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (625.196 KB) | DOI: 10.12962/j20882033.v30i2.5007

Abstract

Academic performance is an important key to student success or failure. Therefore, academic performance prediction become a popular research on education. In general, several researches used GPA to predicting academic performance. However, there are some aspect that also plays a role in student academic performance, like friend relationship. So, this paper will analyze the correlation between academic performance and friend relationship. Friendship will be seen from communication frequency between students when become University delegation. Each students friend will have weight to show their closeness. In this paper, proposed method gives friendship weight based on communication frequency proportion between student among all student in one faculty. Indeed, close friends have a higher weight than other friends. So, the friendship weight sorted into descending order to get the closest friend. Then, their GPA convert into academic label, i.e. cumlaude, excellent, very good, or drop out. Furthermore, label will be compared to obtaining validation of our hypotheses that friendship plays a role in academic performance achievement. We use scholar student delegation dataset in competition from year 2015 in 7 study programme with 160 scholar students. Experimental results showed that the proposed method can predict academic performance 43% from the total data sample.
Performance Study Of Uncertainty Based Feature Selection Method On Detection Of Chronic Kidney Disease With SVM Classification Qolby, Lailly Syifa'ul; Buliali, Joko Lianto; Saikhu, Ahmad
IPTEK The Journal for Technology and Science Vol 32, No 2 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i2.10483

Abstract

Chronic Kidney Disease (CKD) is a disorder that impairs kidney function. Early signs of CKD patients are very difficult until they lose 25% of their kidney function. Therefore, early detection and effective treatment are needed to reduce the mortality rate of CKD sufferers. In this study, the authors diagnose the CKD dataset using the Support Vector Machine (SVM) classification method to obtain accurate diagnostic results. The authors propose a comparison of the result on applying the feature selec- tion method to get the best feature candidates in improving the classification result. The testing process compares the Symmetrical Uncertainty (SU) and Multivariate Symmetrical Uncertainty (MSU) feature selection method and the SVM method as a classification method. Several experimental scenarios were carried out using the SU and MSU feature selection methods using the CKD dataset. From the results of the tests carried out, it shows that using the MSU feature selection method with 80%: 20% data split produces nine important features with an accuracy value of 0.9, sensi- tivity 0.84, specification 1.0, and when viewed on the ROC graph, the MSU method graph shows the true positive value is higher than the false positive value. So the classification using the MSU feature selection method is better than the SU feature selection method by 90% accuracy
Co-Authors A.A. Ketut Agung Cahyawan W Achmad Saidul Agri Kridanto, Agri Ahmad Saikhu Ahmad Saikhu Alvin Lazaro Andreas Handojo Andreast Wahyu Sugiyarta Andrew Andrew Andriyani Andriyani Andriyani Andriyani Andriyani Arya Yudhi Wijaya Arya Yudi Wijaya Bilqis Amaliah Bisono, Eva Firdayanti Cempaka A. Swastyastu Darlis Herumurti Diagnosa Fenomena Diana Purwitasari Dwi Sunaryono Erma Suryani Fadilah Fahrul Hardiansyah Fadilah Fahrul Hardiansyah, Fadilah Fahrul Fenky Sugiarto Frica Salim Wiharjo Ginardi, Raden Venantius Hari Giri Wiriapradja Hadi Siswidiastono Hartono Hartono Heru Tri Ahmanto Isye Arieshanti Mohammad Yazdi Pusadan Muhammad Faris Musthafa Muhammad Noor Muhammad Zuber Myrna ermawati Prayogo, Reza Prasetya Prayuda, Janandra Aji Qolby, Lailly Syifa'ul Ria Andriana Riyanarto Sarno Saprina Mamase Siti Maimunah Suhadi Lili Suhadi Lili Tora Fahrudin Tsabbit Aqdami Mukhtar, Tsabbit Aqdami Untoro, Meida Cahyo Victor Hariadi Wahyudi Agustiono Waskitho Wibisino Waskitho Wibisono Wulandari, Desi Yanuar Risah Prayogi Yudhi Purwananto Yudhiakto Pramudya Yuhana, Umi Laili Yuniarto, Muhammad Nur