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Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika
Published by Universitas Yudharta Pasuruan
ISSN : 20863489     EISSN : 2549354X     DOI : -
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal Explore IT! merupakan publikasi ilmiah enam bulanan yang diterbitkan oleh Program Studi Teknik Informatika Universitas Yudharta Pasuruan. Isi artikel Jurnal EXPLORE IT meliputi bidang Artificial Intellegent, AR VR, Mobile programming, Pattern Recognition, Internet of Thinks (IoT), Remote Sensing, Fuzzy Logic, Computer Network and Architecture, Network Security, Embedded system, dan aplications.
Arjuna Subject : -
Articles 116 Documents
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OPTIMASI ALGORITMA C4.5 MENGGUNAKAN PARTICLE SWARM OPTIMIZATION (PSO) UNTUK KLASIFIKASI PENYEBAB PERCERAIAN Nafillah

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v11i1.1472

Abstract

The number of divorces that occur in Indonesia is increasing every year, from the data that is known that most divorce cases are carried out by couples under the age of 35 years, the cause also varies from domestic violence, economic factors, infidelity, incompatibility, etc. From the existing divorce data, it is necessary to extract information to predict what factors are causing the divorce. In this study will use the C4.5 algorithm as a classification and prediction method, which will be optimized using the PSO (Particle Swarm Optimization) algorithm to improve the performance of the C4.5 algorithm. From the data mining process, the classification is produced with an accuracy of 87.4%, the accuracy level is higher when compared to the previous research which is only 57.63%. Keywords: Divorce rate, divorce factor, C4.5 Algorithm, PSO Algorithm, Optimization.
IMPLEMENTASI SISTEM ABSENSI PEGAWAI MENGGUNAKAN MAC ADDRESS SMARTPHONE DENGAN SENSOR BLUETOOTH BERBASIS MIKROKONTROLLER ARDUINO Siti Nur Azizah

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v11i1.1473

Abstract

Along with the development of increasingly advanced technology and the use of hardware in a variety of work activities supported by various software, so that entrepreneurs of a company or agency use the technology as a tool attendance attendance that helps in the assessment and assessment of employee work. This research was conducted to design an attendance attendance system using microcontroller-based Bluetooth sensor that is easy, effective, efficient, and aimed to control and detect sensor, because it uses Bluetooth network as connectivity between hardware module which will produce attendance attendance system. In the Hardware Module originates from the Bluetooth mobile phone that will be connected to the Bluetooth HC-05 module, then Bluetooth Module HC-05 will send commands to detect sensors through Pin that is connected with Arduino Nano and processed into the PC. The result of this research is Bluetooth connection can be used as a tool of attendance by using hardware module connected to PC. Keywords: Bluetooth Mobile, Microcontroller, Bluetooth Sensor HC-05.
Aplikasi pengenalan huruf hijaiyah untuk anak usia dini berbasis android menggunakan augmented reality Alya Alwiyah; Muhammad Imron Rosadi

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v11i2.1653

Abstract

Smartphone kerap digunakan untuk mengendalikan aplikasi mobile sebagai sarana untuk mengakses dan mengolah informasi. Penggunaan smartphone banyak diminati mulai dari kalangan dewasa maupun anak-anak. Didalam smartphone terdapat ratusan aplikasi yang paling menarik yaitu game. Pada awalnya game ditunjukkan sebagai media penghilang kejenuhan saat belajar, namun fitur yang satu ini tidak jarang membuat anak jadi lupa waktu, sehingga menyebabkan anak-anak kelelahan dan malas untuk belajar. Bentuk kemajuan teknologi yang bisa dimanfaatkan dalam bidang pendidikan adalah Augmented Reality yaitu sebuah terobosan di dunia multimedia dan pengolahan citra digital yang sedang maju. Aplikasi tersebut digunakan untuk pengenalan huruf hijaiyah bagi anak dini berbasis android. Pembuatan aplikasi ini menggunakan software Unity 3D untuk marker huruf-huruf hijaiyah dan Vuforia. Pada impelementasi akan ada proses scanning untuk memunculkan efek 3D dari huruf-huruf hijaiyah tersebut. Tujuan dari penelitian ini menerapkan Augmented Reality pada smartphone untuk mengurangi bermain game dan menyeimbangkan minat belajar huruf hijaiyah sejak dini. Hasil penelitian yang dilakukan menunjukkan bahwa metode tersebut menghasilkan minat belajar terhadap anak-anak lebih baik.
APLIKASI PENGENALAN DINOSAURUS DENGAN ANIMASI 3D BERBASIS ANDROID MENGGUNAKAN AUGMENTED REALITY (AR) avysa nabila; Muhammad Imron Rosadi

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v11i2.1656

Abstract

Peningkatan di sekolahan pada umumnya proses pendidikan hampir sama, adanya pemberian materi menggunakan media-media seperti, papan tulis, buku-buku bergambar yang digunakan untuk lebih memperjelas materi kepada siswa. Aplikasi yang dikembangkan dan telah dipasang pada perangkat Android dengan menggunakan Vuforia sebagai dukungan teknologi Augmented Reality. Munculnya teknologi Augmented Reality sangat membantu prosesnya pendidikan pengenalan hewan terutama dengan adanya dukungan terhadap marker yang memadukan buku 2D sebagai marker untuk memunculkan objek 3D. Saat ini untuk belajar mengenai hewan Dinosaurus ketika belajar sejarah di sekolah setingkat SD dan SMP hanya dapat dipelajari dari buku sejarah saja, dimana terdapat gambar fosil Dinosaurus yang telah ditemukan di berbagai dunia. Dari pembahasan dapat disimpulkan bahwa perangkat Smartphone dan menggunkan Augmented Reality (AR), bisa dimanfaatkan sebagai media untuk mendapatkan informasi tentang jenis-jenis hewan dengan lebih mudah, efektif dan interaktif.
Segmentasi Region Of Interest (ROI) Garis Telapak Tangan Menggunakan Deteksi Tepi Sobel Khoilil Fitria; Lukman Hakim

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v11i1.1666

Abstract

The palm is one of the biometric characteristics that has been relatively recently investigated for identification and verification systems. The reason for using the palm geometry feature is, because the palm geometry is considered more resistant to external factors, such as weather, dry or wet palm conditions compared to using the characteristics of the palm lines that have difficult details and are susceptible to external factors. The problem that often arises in the self-recognition system is that it is easy to commit a crime against a person's identity if only by using something that is owned or something that is known to a system, using biometrics techniques is expected to minimize these frequent problems. Therefore, this study was made to implement the region of interest (ROI) segmentation method for palm line imagery using sobel edge detection, so that it can help for the initial process of identification and verification. the highest accuracy value on the right palm line image reached 87.01% and the lowest reached 86.46%, the highest accuracy value on the left palm line image reached 85.35% and the lowest reached 82.68%.
SEGMENTASI CITRA CT SCAN LUNG MENGGUNAKAN DETEKSI TEPI SOBEL DAN METODE DISTANCE REGULARIZED LEVEL SET EVOLUTION (DRLSE) ; Lilis Trisnawati; Lukman Hakim

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v10i1.1670

Abstract

The lung is one of the organs in the respiratory system that serves as a place to exchange oxygen with carbon dioxide in the blood. Disturbance the lung causes the patient difficult breathing, difficult to activity, lack of oxygen in fact if not quickly detected can cause death. To determine the symptoms of a patient's illness is generally carried out laboratory tests, where these tests are quite expensive and sometimes cause injuries and the result was sometimes long to be known x-ray images, this causes many people who indicated suffering from lung disease. The previous method capable of performing image segmentation ct scan lung difficult or not clarified to determination of edge detection and it still takes a long time for processing on ct scan lung image. Therefore, in this study to implement segmentation on ct scan lung image by using edge detection sobel and Distance Regularized Level Set Evolution Method to accelerate the segmentation of medical images. This method is capable of performing image segmentation ct scan lung with average an accuracy of 95.08% and average the Area Under the Curve (AUC) on relaive operating characteristic curve (ROC) amounted to 90.66%
PENERAPAN ALGORITMA NAÏVE BAYES UNTUK PREDIKSI PENERIMAAN SISWA BARU DI SMK AL-AMIEN WONOREJO ; Saful Rizal; Moch. Luthfi

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v10i1.1671

Abstract

One aspect of the first high school quality indicator is the level of acceptance of students in senior high schools or public vocational schools. Some junior high school students' data were analyzed to determine the level of acceptance of students in senior high schools or state vocational high schools. The process of analyzing student data using data mining techniques. The purpose of this research is to know the application of naïve bayes classification on the average value of report cards and the value of national examination on the acceptance level of students in high school or public vocational school using the result of classification model that formed. In this study the data used is the new student data force 2016 Vocational High School AL-AMIEN Wonorejo. Data mining process is assisted by WEKA software using naïve bayes classification and 10-fold cross validation. Furthermore the naïve bayes classification model is used to process prediction data. The results of the testing of the Naïve Bayes algorithm in predicting the acceptance of new students at the AL-AMIEN Wonorejo Vocational High School in 196 data of the students tested in this study, showed that the Naïve Bayes algorithm has an accuracy rate of 86.22%.
OPTIMASI METODE C4.5 MENGGUNAKAN ALGORITMA GENETIKA UNTUK KLASIFIKASI STUDI LANJUT SISWA MADRASAH ; A. Zulham F.H

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v10i1.1715

Abstract

Students (learners) are children or adolescents who get science education, guidance, and direction so as to get changes, developments in shaping a personality, as well as a structural education in the teaching process. In Permendikbud No. 5 of 2015 article 4 also explained the value of report cards must be 50% to 70% and the value of UN weighted between 30%. So in this research will do classification of advanced study of madrasah students by using algorithm C4.5 which has the highest level of accuracy, but in this research will be conducted optimization of assessment using genetic algorithm to mendaptkan better result. The process within the genetic algorithm is used to obtain an optimal solution of rapid value for complex problems in determining the value of subjects for five semesters. In experiments on the Decision Tree (C4.5) and Decision Tree algorithms coupled with optimizations using Genetic Algorithm (GA). From both tests it can be seen that Decision Tree (C4.5) research resulted Accuracy 79,43%, while Decision Tree (C4.5) with Genetic Algorithm (GA) as feature selection resulted Accuracy 81,43%.
PERBANDINGAN METODE k-NN DAN NEURAL NETWORK (Backpropagation) DALAM KLASIFIKASI GIZI ANAK ; Arif Faizin

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v10i1.1716

Abstract

In the Decree of the Minister of Health of the Republic of Indonesia No. 1995 / Menkes / SK / XII / 2010 dated December 30, 2010 and the World Health Organization- National Center for Health Statistics (NCHS-WHO), it is clear how standardization child nutrition is a very urgent matter. Because to know the nutritional intake of children that must be met when the condition of the child in a state of malnutrition or if the child nutrition. In this case, the child nutrition will affect brain development; adequate nutrition will be able to add to the absorption of the brain which will give the maximum intelligence, which corresponds to the opening 45 that is to educate intelligence UDD Nations children, which will be the focus point of this research. Methods to be used are two methods of data mining classification that Neural Network and K-Nearest Neighbor (K-NN), which will be sought method best of both methods, in seeking highest accuracy. Keynotes: Child Nutrition, Neural Networks and K-Nearest Neighbor (K-NN),
PREDIKSI STOK OBAT MENGGUNAKAN METODE RADIAL BASIS FUNCTION NETWORK STUDI KASUS GUDANG FARMASI KESEHATAN PUSKESMAS RACI Saiful Arif Saiful

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v10i1.1751

Abstract

Kesehatan merupakan hal yang penting dari setiap manusia untuk menjalankan aktifitas tanpa ada kendala suatu penyakit. Penykit merupakan suatu kondisi fisik dalam tubuh manusia yang tidak normal yang sangat menggangu pada penderita. Jenis penyakit yang sering ditakuti oleh setiap manusia yaitu penyakit kronis butuh adanya penanganan yang perlu di perhatikan. Obat merupakan suatu zat kimia yang penting untuk media perawatan. Pada bagian farmasi puskesmas raci sering terjadinya kekosongan stok obat dan membutukan waktu lama karena sistem yang digunakan masih menggunakan manual. Oleh karena itu, pada penelitian ini bertujuan untuk mengetahui hasil prediksi dari persedian stok obat dengan menggunakan metode Radial Basis Function Network. Radial Basis Function Network yaitu sebuah arsitektur dari jaringan syaraf tiruan yang terdiri dari input, hidden, dan output layer. Akan tetapi proses input ke hidden perlu digunakan algoritma K-Means. Penelitian ini untuk mengetahui nilai error RMSE dari presiksi stok obat metode Radial Basis Function Network. Hasil prediksi tingkat error yang didapat untuk obat ambroxol berjumlah 0,246, obat amoksisillin berjumlah 0,297, obat anti influenza berjumlah 0,319, obat asam mefenamat berjumlah 0,313, dan obat deksametason berjumlah 0,373. Kata Kunci : prediksi, stok obat, radial basis function network, rmse

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