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All Journal KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Sains dan Informatika Elsains : Jurnal Elektro Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Logic : Jurnal Rancang Bangun dan Teknologi Jurnal Pengabdian Kepada Masyarakat (Mediteg) Aisyah Journal of Informatics and Electrical Engineering Scientific Journal of Informatics Jurnal Teknimedia: Teknologi Informasi dan Multimedia Journal of Applied Computer Science and Technology (JACOST) Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Brilliance: Research of Artificial Intelligence Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) As-Sakinah : Jurnal Hukum Keluarga Islam Informatika Sains Teknologi
Veri Julianto
Politeknik Negeri Tanah Laut
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Mathematics Social Sciences Other

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Journal : Scientific Journal of Informatics

 1 
APLIKASI PEMILIHAN STRATEGI PROMOSI PENERIMAAN MAHASISWABARU POLITEKNIK NEGERI TANAH LAUT MENGGUNAKAN METODE K-MEANS CLUSTERING Veri Julianto; Jaka Permadi; Noviyanti
Jurnal Ilmiah Informatika Vol. 2 No. 1 (2017): Jurnal Imliah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v2i1.459

Abstract

Politeknik Negeri Tanah Laut in order to improve the new student admission, has adopted numerous type of promotion strategies. The strategies are among others high school visits, banner displays, brochure distribution, and promotions via social media. However, those strategies adopted by Politeknik Negeri Tanah Laut are admittedly costly. Application of Selecting Promotion Strategy Enrollment of New Students in the Politeknik Negeri Tanah Laut is an application used to help determine what kind of promotional strategy is likely to be more accurate and more planned as the guidance as well as the reference in order to increase the enrollment percentage of new students. The determination of such promotional media’s outcomes is supported by applying the method of K-Means Clustering to do the classification of promotional media data obtained from the result of students’ questionnaires. Obviously such thing becomes a solution to help determine the promotional strategy at Politeknik Negeri Tanah Laut.
Analisis dan Penerapan Metode Fuzzy AHP-TOPSIS dalam Penentuan Mitra Industri Sebagai Tempat Praktek Kerja Lapangan Veri Julianto; Hendrik Setyo Utomo; Herpendi Herpendi
Jurnal Ilmiah Informatika Vol. 5 No. 2 (2020): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v5i2.942

Abstract

Field Work Practices are part of achieving the expected competencies in the educational process. The suitability of students to companies that serve as street vendors is something that is important to note. The weakness of the previous field work practices system was that there were still many students who were inaccurate in choosing a company or institution as a place for street vendors. This study aims to help determine industry partners in accordance with the competency achievements of each department. The method to be used in this research is Fuzzy Analytical Hierarchy Process (FAHP) in the process of determining the weight priority of each criterion and the TOPSIS method in carrying out the ranking process. The criteria used are the suitability of the department with the company's core (C1), company credibility (C2), and company commitment (C3). corporate environment (C4), and the facilities provided (C5). Each of these criteria consists of several sub criteria. The weights of the criteria obtained through the FAHP are Furthermore, the process of ranking 37 companies using the TOPSIS method obtained the highest preference value, namely 0.8157.
Penerapan Bat Algorithm Dalam Penyelsaian Kasus Travelling Salesman Problem (TSP) Pada Internship Program Veri Julianto; Hendrik Setyo Utomo; Muhammad Rusyadi Arrahimi
Jurnal Ilmiah Informatika Vol. 6 No. 2 (2021): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v6i2.1485

Abstract

This optimization is an optimization case that organizes all possible and feasible solutions in discrete form. One form of combinatorial optimization that can be used as material in testing a method is the Traveling Salesman Problem (TSP). In this study, the bat algorithm will be used to find the optimum value in TSP. Utilization of the Metaheuristic Algorithm through the concept of the Bat Algorithm is able to provide optimal results in searching for the shortest distance in the case of TSP. Based on trials conducted using data on the location of student street vendors, the Bat Algortima is able to obtain the global minimum or the shortest distance when compared to the nearest neighbor method, Hungarian method, branch and bound method.
Prediction Of Student Graduation Using The K-Nearest Neighbor Method Case Study in Politeknik Negeri Tanah Laut Sari, Dwi Ratna; Julianto, Veri; Rhomadona, Herfia
Jurnal Ilmiah Informatika Vol. 8 No. 1 (2023): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v8i1.74-88

Abstract

Tanah Laut State Polytechnic as one of the universities in Indonesia has definitely paid attention to the quality of its students. One way is to predict student graduation. Graduation predictions can help study programs and academic supervisors review and pay special attention to students, especially students who are predicted to not graduate on time. Realizing one way to pay attention to the quality of students can be realized by creating a Student Graduation Prediction system using the Web-Based K-Nearest Neighbor (KNN) Method. The K-Nearest Neighbors method is an object classification method based on training data by finding the nearest neighbor value to determine the class of the new data. In the Student Graduation Prediction using the K-Nearest Neighbor Method, there is a section that can process training data, test data, the process of calculating student graduation predictions, and displaying the results obtained from the KNN calculation which has two classification classes, namely graduated and not passed. Based on the results of the study, it was found that KNN with different k values obtained different levels of accuracy, data testing with a value of k=1 obtained an accuracy rate of 83.33%, the value of k=2 obtained an accuracy rate of 79.17%, the value of k=3 to k= 8 obtained an accuracy rate of 95.83%, and the values of k=9 and k=10 obtained an accuracy rate of 91.67%. It can be concluded that the test with a value of k=3 to k=8 obtained the best or highest level of accuracy.
Co-Authors Ade Kurniawan Ade Kurniawan Adelia, Firda Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Arif Suprianto Arif Supriyanto Dewi Saadah Dhika Sinta Pratama Dwi Ratna Sari, Dwi Ratna Eka Wahyu Sholeha Fathurahmani Fathurahmani Fathurahmani, Fathurahmani Heldalina Hendrik Setyo Utomo herpendi, herpendi Jaka Permadi Jamil, Khafifah Karima Zam Zam Khairul Anwar Hafizd, Khairul Anwar Lastriani Lastriani Lastriani Lastriani Meldayanoor Meliana Mohammad Sofwat Aldi Muhammad Indra Darmawan Muhammad Muslih Amirudin Muhammad Noor Muhammad Rusyadi Arrahimi Mustofa, Jupri Norfifah Noviyanti Nur Maida Oktaviyani Oktaviyani Oktaviyani, Oktaviyani Oky Rahmanto Pratama, Dhika Sinta Rabini Sayyidati Rahman, Ramdani Rahmanto, Oky Ramdani Rahman Ramitha Ramitha Ramitha, Ramitha Rhomadona, Herfia Saadah, Dewi Sabella, Billy Wan Yuliyanti Wan Yuliyanti Wijayati, Titik Winda Aprianti Yundari, Yundari Yunita Prastyaningsih