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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.
PELATIHAN PEMANFAATAN APLIKASI RUMAH BELAJAR UNTUK MEMBANTU PEMBELAJARAN PADA MASA PANDEMI BAGI GURU-GURU DI YAYASAN WALADUN SHOLEH Veri Julianto; Arif Supriyanto; Yunita Prastyaningsih; Wan Yuliyanti
Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Vol. 2 No. 2 (2022): Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat)
Publisher : Yayasan Lavandaia Dharma Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Learning that takes place at the Waladun Sholeh school is carried out online by utilizing several learning platforms, but there are some educators/teachers who are still lacking in literacy in the utilization and use of learning platforms, one of which is the Learning House portal. Therefore, it is necessary to train in the use of learning houses for learning during the pandemic for educators/teachers. Training on the use of learning houses for learning during the pandemic was carried out as a solution to the problem of lack of literacy in the use and utilization of learning portals. This training was wrapped in the form of community service and was held on December 17, 2021 at the Bill Gates Computer Laboratory, Department of Informatics, which was attended by 20 school teachers, Waladun Sholeh. The training provided is registration materials in the study house, uploading and downloading materials at the study house. As a result, 97.65% of participants stated that they were very satisfied with the training provided.
Rancang Bangun Sistem Informasi Audit Mutu Internal Norfifah; Veri Julianto Julianto; Yunita Prastyaningsih
Journal of Applied Computer Science and Technology Vol 4 No 2 (2023): Desember 2023
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jacost.v4i2.539

Abstract

Internal quality audits are conducted within the internal quality assurance system (SPMI) of higher education institutions to ensure compliance with SPMI standards and enhance a quality culture. Constraints in implementing internal quality audits include limitations in human resources, time, and costs, as well as the complexity of audit stages and documentation of audit findings. To address these challenges, a website-based information system has been designed using the waterfall method and the Unified Modeling Language (UML) approach, utilizing the PHP framework CodeIgniter and a MySQL database. The system aims to digitize and automate the implementation of internal quality audits to enhance effectiveness and efficiency. Additionally, it facilitates the management and storage of internal quality audit documents. For testing purposes, black-box testing is employed, consisting of 10 different test types. The testing results indicate a 90% success rate, while 10% of the data did not succeed due to the limitation of inputting text HTML.
Machine learning to Detect Palm Oil Diseases Based on Leaf Extraction Features and Principal Component Analysis (PCA) Arrahimi, Ahmad Rusadi; Julianto, Veri; Rahmanto, Oky
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 11, No 1 (2024)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v11i1.659

Abstract

Palm oil tree is one of the economically important crops that is the backbone of the Indonesian economy. However, palm oil production is often hampered by various diseases. The disease is difficult to detect in the early stages because infected trees often show no symptoms. Therefore, it is necessary to carry out identification and classification to determine whether this palm coconut plant is sick or infected with disease. In this study the disease was identified in palm coconut by identifying it through leaves by modifying the extraction process features using PCA and comparing it with no PCA for sick and healthy types. Subsequently, the classification will be done using SVM (Support Vector Machine) with various treatments such as variation of the features used and the amount of data to be processed in carrying out experiments or tests. The results obtained show that if the feature used for classifying a number of 4 or more then the accuracy value remains at 97%.
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

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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.
Perancangan Multicontrol Pada Lampu Berbasis Internet Of Think (IOT) Herpendi, Herpendi; Julianto, Veri; Hafizd, Khairul Anwar
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 8 No 2 (2018): September 2018
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (472.077 KB) | DOI: 10.33020/saintekom.v8i2.65

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Technological developments in the communication and information area can changes the lifestyle of the human become the digital lifestyle. Digitalization on the aspects of life can provide convenience for humans. Like the household appliances that can be controlled by a smartphone. In 2015 Nugraha build a light management system with android smartphone via bluetooth media. In addition, the lights are also can be controlled automatically by time and light (LDR). The disadvantages of this system are the lights that can not be used remotely and can not give notice to the home owner about the status “on or off” of the light. This research aims to design a multicontrol system to control the light with several media follows : bluetooth, voice, light (LDR), timer, website and SMS as notification of light status. System development method in this research using Waterfall method. The test results using bluetooth, light(LDR), voice, and timer provide a fast response with average less than 2 seconds.
Sistem Informasi Pendaftaran Nikah Kantor Urusan Agama berbasis Web Noor, Muhammad; Julianto, Veri
As-Sakinah : Jurnal Hukum Keluarga Islam Vol 2 No 2 (2024): As-Sakinah : Jurnal Hukum Keluarga Islam
Publisher : STAI Pelabuhan Ratu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51729/sakinah22707

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Kantor Urusan Agama (KUA) Bumi Makmur, Kabupaten Tanah Laut, merupakan salah satu instansi pemerintah yang memiliki peran penting dalam pelayanan administrasi pernikahan. Namun, pemanfaatan teknologi dalam proses pendaftaran di kantor ini masih kurang efisien. Sistem yang diterapkan saat ini mengharuskan masyarakat mendaftar secara manual dengan mendatangi kantor, mengisi formulir pendaftaran, serta melengkapi berkas persyaratan nikah. Penelitian ini bertujuan untuk menganalisis efisiensi proses pendaftaran nikah dan pengelolaan administrasi di Kantor Urusan Agama (KUA) Bumi Makmur, Kabupaten Tanah Laut, serta mengembangkan solusi berbasis teknologi untuk mengatasi kendala yang ada. Metode penelitian yang digunakan adalah pendekatan kualitatif dengan teknik pengumpulan data melalui observasi, wawancara, dan studi dokumentasi. Hasil penelitian menunjukkan bahwa sistem pendaftaran manual yang saat ini diterapkan memiliki berbagai kelemahan, seperti waktu layanan yang tidak efektif, risiko kehilangan atau kerusakan dokumen, serta pencatatan manual yang berpotensi menimbulkan kesalahan. Sebagai solusi, penelitian ini merekomendasikan implementasi sistem informasi digital yang dapat mendukung proses pendaftaran nikah secara daring dan pengelolaan laporan berbasis elektronik, sehingga meningkatkan efisiensi dan akurasi layanan administrasi di KUA.
Aplikasi Absensi dan Penjadwalan Berbasis Web di SMA Negeri 1 Pelaihari menggunakan framework Laravel Nur Maida; Veri Julianto
INFORMATIKA SAINS TEKNOLOGI Vol 2 No 2 (2024): Jurnal insit Vol 2 No 2 Tahun 2024
Publisher : Fakultas Sains Dan Teknologi Universitas Islam Asyafiiyah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34005/insit.v2i2.4110

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Pelaihari 1 Public High School, located in Pelaihari District, is one of the educational institutions that supports improving the quality of education. Providing information by students is carried out by collecting the necessary data, then the data is input using Microsoft Excel or Microsoft Word. Apart from that, paper is also used when making attendance. Any existing data is then shared back with teachers and students who need it via WhatsApp. This method is considered less effective due to limited program functions, easy file loss, difficulty in searching for data, and also in terms of time. Therefore, a Web-Based Attendance and Scheduling Application was developed at SMA Negeri 1 Pelaihari using the Laravel Framework. This application is expected to fulfill one of the Admin's tasks in managing data, so that Admins feel it is easier to share information with teachers and students. The features contained in this system include class data, student data, employee data, subject data, schedule data, User data, attendance data, reporting and journal data. This system was developed using a prototype development model, the Laravel framework, and was designed using the Unified Modeling Language (UML) and Entity Relationship Diagram (ERD) models. The programming language used is PHP and the database used is MySQL.
Evaluating Random Forest Algorithm: Detection of Palm Oil Leaf Disease Rahmanto, Oky; Julianto, Veri; Arrahimi, Ahmad Rusadi
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4798

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This research investigates the application of machine learning techniques for detecting diseases in oil palm leaves, utilizing a dataset of 1,119 images sourced from plantations in the Tanah Laut district. The dataset comprises 488 diseased and 631 healthy leaf samples, which were carefully cropped to isolate leaf areas and labeled with the assistance of domain experts. For feature extraction, both Lab and RGB color spaces were considered, alongside Haralick texture features, resulting in a total of eleven features per pixel. To reduce dimensionality and select relevant features, Principal Component Analysis (PCA) and Random Forest methods were applied. Support Vector Machine (SVM) was subsequently employed for the classification of leaf health status, and model performance was evaluated using accuracy, precision, recall, and F1 score metrics, all derived from a confusion matrix. The study finds that PCA and Random Forest significantly enhance model performance, improving the ability to distinguish between healthy and diseased leaves. These findings provide valuable insights for the development of automated disease detection systems in oil palm plantations, with potential applications in precision agriculture. Additionally, the results suggest pathways for further research into plant disease diagnostics, highlighting the role of advanced machine learning techniques in enhancing crop management and supporting sustainable agricultural practices.