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All Journal Jurnal Neutrino : jurnal fisika dan aplikasinya Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Informatika dan Teknik Elektro Terapan Jurnal Spektra JOIN (Jurnal Online Informatika) Jurnal Pilar Nusa Mandiri JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ Jurnal Informasi dan Komputer Communautaire: Journal of Community Service
Riza Ibnu Adam, Riza Ibnu
Departemen Fisika, FMIPA, Universitas Indonesia, Depok, 16424
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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EFEK MEDAN LISTRIK BINTANG NEUTRON Adam, Riza Ibnu; Sulaksono, Anto
Jurnal Spektra Vol 16, No 3 (2015): Spektra: Jurnal Fisika dan Aplikasinya
Publisher : Jurnal Spektra

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Abstract

AbstrakPada permukaan bintang neutron, perubahan kerapatan partikel yang signifikan dapat menghasilkan separasi muatan dalam bentuk lapisan dipol listrik. Pada penelitian ini dipelajari efek medan listrik akibat lapisan tersebut terhadap properti dari bintang neutron. Pada perhitungan kami gunakan dua model dengan asumsi berbeda, yakni: model dengan asumsi bahwa bintang neutron hanya tersusun atas p, n, e dan µ serta model dengan asumsi bintang neutron tersusun dari p, n, e, µ dan hiperon. Hasil yang diperoleh menunjukkan bahwa massa maksimum tidak sensitif terhadap medan istrik dipermukaan, tetapi radius bintang dengan massa kanonik 1,4 Mʘ cukup sensitif terhadap medan listrik. Bintang neutron dengan hiperon bersifar lebih soft dibandingkan bintang neutron tanpa hiperon. AbstractOn the surface of a neutron star, a significant particle density changes can produce charge separation in the form electric dipole layer. This research studied electric field effect from dipole layer on the properties of neutron star. We use two models with different assumptions: namely a model assumes the neutron star only composed of p, n, e and µ and a model which assumes the neutron star is composed of p, n, e, µ dan hyperon. The result showes that the maximum mass is not sensitive to the electric field on the surface, but the radius of star with canonical mass 1,4 Mʘ is quite sensitive to the electric field . The neutron star with hyperon is softer than without hyperon.Keywords: Neutron Star, Electric Field, TOV Equation, RMF Model, Gaussian Function.
VARIATIONAL MUTI-STEPS METHOD TO SOLVE DAMPED OSCILLATION EQUATION Adam, Riza Ibnu; Susilawati, Susilawati; Rizal, Adhi
Jurnal Neutrino Vol 10, No 1 (2017): October
Publisher : Department of Physics, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (214.908 KB) | DOI: 10.18860/neu.v10i1.4399

Abstract

This paper aims to identifying the numerical method accuracy of the analytical solution of the damped oscillation equation motion. Adams method of  4th order, Milne method and Adams-Simpson method are used to find numerical solutions. Value of y(1), y(2), y(3) obtained from The 4th order Runge-Kutta method. They used as initial value of multistep method. Then, the numerical solution result was compared with analytical solution. From the research result, it is found that 4th order Adams method has the best accuracy.
Sistem Kelas Virtual dan Pengelolaan Pembelajaran Berbasis 3-Dimensional Virtual World Rizal, Adhi; Adam, Riza Ibnu; Susilawati, Susilawati
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 4, No 2 (2018): Volume 4 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (832.175 KB) | DOI: 10.26418/jp.v4i2.27449

Abstract

Penelitian ini bertujuan untuk mengembangkan dan menerapkan sistem kelas virtual berbasis dunia virtual 3 dimensi (3D). Kelas virtual dikembangkan berdasarkan framework pengembangan aplikasi ADDIE dengan meintegrasikan LMS Moodle, singularity viewer, SLOODLE, dan multi-user 3D application server OpenSimulator. Objek-objek yang ada pada kelas di dunia nyata direpresentasikan oleh objek 3D. Peserta didik dapat berinteraksi dengan objek-objek yang ada dalam kelas virtual untuk melaksanakan kegiatan pembelajaran. Pengujian kelas virtual dilakukan dengan cara menerapkannya untuk digunakan secara langsung oleh peserta didik dalam kegiatan pembelajaran. Pengujian dilakukan berdasarkan dua kriteria, yaitu evaluasi hasil belajar peserta didik dan uji penerimaan pengguna menggunakan Technology Acceptance Model (TAM). Hasil evaluasi hasil belajar menunjukan bahwa penggunaan kelas virtual tidak berpengaruh terhadap hasil belajar. Walaupun demikian, hasil uji penerimaan pengguna menunjukan bahwa kelas virtual dapat memberikan kepuasan dan dapat diterima untuk digunakan oleh peserta didik dalam proses pembelajaran.
SKEMA PENYEMBUNYIAN DATA PADA GAMBAR BERBASIS INTERPOLASI KUBIK B-SPLINE MENGGUNAKAN METODE LEAST SIGNIFICANT BIT (LSB) garno, Garno; Adam, Riza Ibnu
Jurnal Edukasi dan Penelitian Informatika (JEPIN) Vol 5, No 3 (2019): Volume 5 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v5i3.37584

Abstract

Maraknya kasus pencurian data menyebabkan sistem keamanan pesan harus ditingkatkan. Salah satu cara untuk mengamankan pesan adalah dengan memasukkan pesan ke dalam gambar digital. Penelitian ini bertujuan untuk meningkatkan kualitas gambar digital dalam sistem keamanan pesan tersembunyi. Teknik yang digunakan untuk keamanan pesan adalah steganografi. Cover image akan dikonversi menjadi bit piksel dalam domain spasial. Cover image digunakan dalam bentuk gambar digital dengan format .jpg. Teknik meningkatkan kualitas dan kapasitas gambar digital dilakukan dengan menambahkan dan meningkatkan bit piksel menggunakan metode interpolasi Cubik B-Spline. Cover image yang telah di interpolasi, kemudian disisipi pesan menggunakan metode least significant bit (LSB) untuk memperoleh stegoimage. Pesan yang diselipkan berbentuk file .doc, .docx, .pdf, .xls, .rar, .iso dan .zip dengan ukuran berbeda-beda kapasitasnya. Teknik uji dibuat dengan bantuan perangkat lunak MATLAB versi 2017a. Penelitian melakukan uji dengan mengukur nilai kualitas penyamaran dari stegoimage menggunakan Peak Signal to Noise Ratio (PSNR) dengan rata-rata perolehan stegoimage terhadap Original image 29.06 dB dan stegoimage terhadap Image interpolation 64.34 dB dan uji mean squared error (MSE) dengan rata-rata perolehan 97.54 dB pada Image interpolation terhadap original image dan 97.55 dB pada stegoimage terhadap original image, 0.13 dB nilai MSE stegoimage terhadap Image interpolation. Hasil uji pada penelitian dengan proses interpolasi pada coverimage dengan Cubic B-Spline mempengaruhi terhadap nilai samar atau Nilai PSNR.
PELATIHAN PENGGUNAAN LABORATORIUM VIRTUAL UNTUK MENINGKATKAN KUALITAS PEMAHAMAN KONSEP FISIKA DI SMA NEGERI 6 KARAWANG Adam, Riza Ibnu; Rizal, Adhi; Susilawati, Susilawati
Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ Vol 8 No 1 (2021): Januari
Publisher : Lembaga Penelitian, Penerbitan dan Pengabdian Masyarakat (LP3M) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/ppkm.v8i1.1008

Abstract

Telah dilakukan pelatihan penggunaan laboratorium Phet. Di SMA Negeri 6 Karawang. Pelatihan bertujuan untuk membantu siswa dalam pemahaman konsep fisika. Simulasi Phet yang ditampilkan adalah gerak pendulum, rangkaian listrik DC, gerak proyektil dan hamburan rustherford .Kemudian, model TAM digunakan untuk mengetahui resapon peserta terhadap hasil simulasi penggunaan PhET. Dari hasil kuisioner diketahui bahwa tingkat actual use atas pembelajaran fisika meningkat dari 37 menjadi 80.
IMPLEMENTASI DEEP LEARNING DALAM MENGIDENTIFIKASI KERETAKAN BAN savina, savina; Adam, Riza Ibnu; Rozikin, Chaerur
Jurnal informasi dan komputer Vol 12 No 01 (2024): Jurnal Informasi dan Komputer yang terbit pada tahun 2024 pada bulan 4 (April)
Publisher : LPPM Institut Teknologi Bisnis Dan Bahasa Dian Cipta Cendikia

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Abstract

Tires are a crucial component of vehicles that play an important role. The functions of tires include reducing vibrations from road irregularities, protecting the wheels from wearing out quickly, and providing ease of movement while driving. Due to their vital nature, it is important to maintain the condition of tires to ensure passenger safety and comfort. Excessive tire usage can lead to damage such as cracks. Cracks in tires can occur due to poor weather conditions and road conditions. Cracks in tires refer to a condition where the tire loses its flexibility and traction capabilities while driving. In fact, research data shows that 80% of traffic accidents on highways occur due to indications of tire damage. Prompt handling and regular checks are required to address and optimize tire damage. The methods used to check tire conditions previously were done manually and relied on human labor. These methods are considered ineffective in identifying tire cracks. In this study, a Deep Learning model using the Transfer Learning ShuffleNet approach was developed to automatically classify tire images in identifying tire cracks. The main objective of this research is to determine the best method in identifying tire cracks and measure the performance of the developed model. In the development of this model, testing was conducted using 10 different scenarios on the created model to find the best method for achieving optimal testing accuracy. The best results obtained were an accuracy of 78% using the ADAM optimizer and 75% using the RMSprop optimizer. Therefore, it can be concluded that the Transfer Learning ShuffleNet method is efficient and capable of accurately detecting tire cracks. This research also successfully determined the best parameters such as the number of epochs, dropout layers, and optimizer in model creation to achieve optimal results. Through the adoption of Transfer Learning ShuffleNet, this research contributes to the development of tire damage detection technology aimed at improving safety and driving comfort.
APPLICATION OF BACKPROPAGATION NEURAL NETWORK ALGORITHM FOR CIHERANG RICE IMAGE IDENTIFICATION Aprilia, Dita; Jaman, Jajam Haerul; Adam, Riza Ibnu
Jurnal Pilar Nusa Mandiri Vol 16 No 2 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v16i2.1500

Abstract

Rice is a food source for carbohydrates that are most consumed in Indonesia, because of this the production is higher compared to other food crops. There are several superior rice varieties planted by the farmers, one of them is Ciherang. This type is widely planted by farmers because has high selling as economic value and can be used as premium rice. The existence of several types of rice that had a high sales value makes some person was deceitfulness by mix the rice with premium quality with bad quality. Many people do not know the problem of distinguishing types of rice from one to another that has the same shape. Classification techniques using the backpropagation neural network algorithm and image processing are used to identify one of the most preferred types of rice, Ciherang. The network architecture model on the backpropagation algorithm is very influential on the value of accuracy. In determining the best network’s architectures, 4 times attempted where network architecture with 5 nodes in the input layer, 8 nodes in the hidden layer, and 1 node in output layer produce the highest accuracy of 82,66%.
Pendampingan Pembuatan dan Pengelolaan Sistem Informasi Desa dan Covid-19 Adam, Riza Ibnu; Voutama, Apriade; Suci, Farradina Choria; Efelina, Vita; Ramadhan Sumantri, Muhammad Jodi
Communautaire: Journal of Community Service Vol. 2 No. 1 (2023)
Publisher : Al-Qalam Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (676.862 KB) | DOI: 10.61987/communautaire.v2i1.25

Abstract

Pasirjengkol Village is a village that is domiciled in Majalaya District, Karawang Regency. So far, they have experienced difficulties with information systems in the form of websites related to the Covid-19 pandemic, so they have never created or managed information systems for the public. The problems encountered are due to the limited ability of village government officials and employees in creating and managing information systems, as well as limited operational support facilities and infrastructure including computers. There are community service activities through mentoring activities, creation and management of a Covid-19 information system that is capable of assisting the routine operations of the Covid-19 task force in Pasirjengkol Village and compiling a guidebook for using the website-based Covid-19 information system in Pasirjengkol Village.
Implementation of Identity Loss Function on Face Recognition of Low-Resolution Faces With Light CNN Architecture Mufid, Tsaqif Mu'tashim; Adam, Riza Ibnu; Jaman, Jajam Khaeru; Garno, Garno; Maulana, Iqbal
Journal of Applied Informatics and Computing Vol. 8 No. 1 (2024): July 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i1.6274

Abstract

Face recognition in low-resolution images has seen significant advancements over the past few decades. Although extensive research has been conducted to improve accuracy in these conditions, one of the main challenges remains the difficulty in identifying unique facial features in low-resolution images, leading to high error rates in identification. The use of Deep Convolutional Neural Networks (DCNN) for low-resolution face recognition is still limited. However, employing super-resolution models like REAL-ESRGAN can enhance recognition accuracy in low-resolution images. This study utilizes the Light CNN architecture and applies the margin-based identity loss function AdaFace on low-resolution datasets. The model is trained using the Casia-WebFace dataset and evaluated using the LFW and TinyFace test datasets. Based on the evaluation results on the LFW test data, the best model is Light CNN9-AdaFace, achieving the highest accuracy of 97.78% at 128x128 resolution. For images with the lowest resolution of 16x16, an accuracy of 83.37% was achieved using super-resolution techniques. On the TinyFace test data, the use of super-resolution resulted in performance metrics with a Rank-1 accuracy of 47.26%, Rank-5 accuracy of 55.25%, Rank-10 accuracy of 58.61%, and Rank-20 accuracy of 61.90% using the Light CNN9-AdaFace architecture.
Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naive Bayes Ramadhan, Bintang Zulfikar; Adam, Riza Ibnu; Maulana, Iqbal
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4725

Abstract

The rapid development of E-commerce has given rise to many marketplaces in Indonesia such as Tokopedia, Shopee, Lazada. Tokopedia, Shopee and Lazada applications are applications that help sellers and buyers to make sales and purchase transactions for goods and services. Until now, of the three major E-Commerce applications, around 100 million users have downloaded the three E-Commerce applications. With the launch of some of these applications, it has caused a lot of opinions and criticisms from the public. Based on this, a sentiment analysis of the Naive Bayes algorithm was carried out to find out how the sentiment of users compares to the E-Commerce application on the Google Play Store. This research uses the Knowledge Discovery in Database (KDD) method which consists of 5 stages, namely data selection, preprocessing, transformation, data mining, and evaluation. The data used is a review of 500 E-Commerce applications per each application. At the data mining stage, it is carried out with 3 scenarios data sharing is 80:20, 70:30 and 60:40. The best results were obtained in scenario 1 (80:20) on the Shopee application using the Naive Bayes algorithm which resulted in an accuracy of 92%, precision of 92.13%, recall of 98.8% and f1-score of 95.35%.
Co-Authors Anto Sulaksono Apriade Voutama Aprilia, Dita Arnisa Stefanie Budi Arif Dermawan Dwijaksara, Ni Luh Bella Efelina, Vita Fikri, Raihan Garno, G. garno, Garno Ibrahim Ibrahim Ikhsal, Muhammad Fachry Iqbal Maulana Irawan, Agung Susilo Yuda Jaman, Jajam Haerul Lela Nurpulaela Masyita, Nurani Mufid, Tsaqif Mu'tashim Putri, Divasetya Pratama Ramadani, Daffa Tama Ramadhan Sumantri, Muhammad Jodi Ramadhan, Bintang Zulfikar Reni Rahmadewi, Reni Rizal, Adhi Rizal, Adhi Rizal, Adhi Rozikin, Chaerur Santoso, Dian Budhi savina, savina Sitanggang, Altolyto Suci, Farradina Choria Susilawati, Susilawati Umaidah, Yuyun