Proxies Jurnal Informatika最新文献

{"title":"ANALISIS LATENSI PADA APLIKASI VIRTUAL REALITY UNTUK ANAK DENGAN AUTISM SYNDROME DISORDER","authors":"Muhammad Rafly, Meredita Susanty","doi":"10.31294/inf.v9i1.11778","DOIUrl":"https://doi.org/10.31294/inf.v9i1.11778","url":null,"abstract":"Virtual Reality (VR) is a branch of interactive media that constantly evolves. VR is a technology that allows users to interact with the environment in a virtual world simulated by a computer. VR makes users feel like they are in the environment. In developing VR, we must have knowledge of sensing and tracking, stereoscopic display, multimodal interactions and recognition (example: metaphors and threedimensional menus, sound, and motion), computer graphics, physics simulation and others. With these technologies, VR can manipulate the user’s brain as if they were in a different world. Because it requires a high level of visual graphics to provide a realistic experience, one of the main challenges in developing VR gaming applications is high latency. High latency results in a decreased quality of the user experience, as there is a time delay between the user’s action and the application’s response. Latency in VR use can even lead to a headache. This study aims to develop a low-latency VR application with a case study of a game application for children with Autism Spectrum Disorder (ASD) while maintaining good visual graphic quality. This study measured the value of latency per visual quality component and application performance quality using a profiler from Unity. The test results show that decreasing the value of each visual component, such as anti-aliasing, shadow resolution, cascades, and soft shadow, will reduce latency. Among these visual components, anti-aliasing contributes the most to latency. This study obtained the optimum combination of these visual components to obtain low latency and good visual graphics.","PeriodicalId":32029,"journal":{"name":"Proxies Jurnal Informatika","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82699199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Perbandingan Algoritma C4.5 dan Naïve Bayes Dalam Memprediksi Penyakit Cerebrovascular","authors":"Kelvin Leonardi Kohsasih, Zakarias Situmorang","doi":"10.31294/inf.v9i1.11931","DOIUrl":"https://doi.org/10.31294/inf.v9i1.11931","url":null,"abstract":"","PeriodicalId":32029,"journal":{"name":"Proxies Jurnal Informatika","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73699316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementasi Metode Hybrid AHP-SAW-TOPSIS Untuk Pemilihan Taman TOGA","authors":"Galih Setiadi, Wiwien Hadikurniawati","doi":"10.31294/inf.v9i1.11901","DOIUrl":"https://doi.org/10.31294/inf.v9i1.11901","url":null,"abstract":"digunakan di dalam penelitian ini menggunakan metode hybrid Analytical Hierarchy Process (AHP), Simple Additive Weighting (SAW), dan Technique for order performance of similarity to idea solution (TOPSIS). Metode AHP dimanfaatkan dalam penentuan nilai bobot parameter, metode SAW dimanfaatkan dalam perhitungan matriks normalisasi serta metode TOPSIS dimanfaatkan dalam proses perankingan untuk mendapatkan hasil akhir. Setelah melakukan proses pemilihan dari beberapa alternatif menggunakan 8 kriteria yang sebelumnya sudah ditentukan, metode hybrid AHP-SAW-TOPSIS yang digunakan di dalam penelitian ini mendapatkan kesimpulan bahwa taman TOGA RT1 dari RW4 memiliki posisi peringkat yang paling tinggi dengan jumlah nilai 0,586. Kelurahan Tambangan Semarang bisa menggunakan Decision Making ini dengan mudah melalui perangkat mobile android. Abstract TOGA park competition is a step taken by the Tambangan Semarang urban village to encourage people to take advantage of nature again. TOGA is a nutritious plant that is managed by the family and planted in the yard. In practice, the TOGA park selection process still uses the manual method. Improper decision-making will result in the chosen TOGA park not being in accordance with the actual reality. Problems in decision-making have made researchers develop Multi-Attribute Decision Making (MADM) research. MADM is used to help the urban village of Tambangan Semarang determine the best TOGA park based on predetermined criteria. Based on the results of interviews with interviewees who made the selection, the criteria used in selecting the best TOGA garden include diversity, neatness, plant identity, product innovation, garden size, number of plants, environmental cleanliness, and documentation. The MADM used in this study uses the hybrid method of Analytical Hierarchy Process (AHP)), Simple Additive Weighting (SAW), and Technique for order performance of similarity to ideal solution (TOPSIS). AHP method is used in determining the parameter weight values, the SAW method is used in calculating the normalization matrix and the TOPSIS method is used in the ranking process to get the final result. After conducting the selection process from several alternatives using 8 previously determined criteria, the AHP-SAW-TOPSIS hybrid method used in this study concluded that TOGA park RT1 from RW4 has the highest-ranking position with a total score of 0.586. Tambangan Semarang urban village can use this Decision Making easily through an android mobile device.","PeriodicalId":32029,"journal":{"name":"Proxies Jurnal Informatika","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86396447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Peningkatan Kualitas Layanan Warga Kelurahan Duri Kepa dengan Aplikasi LINGKOE","authors":"Francka Sakti Lee, M. F. Isputrawan","doi":"10.31294/inf.v9i1.11538","DOIUrl":"https://doi.org/10.31294/inf.v9i1.11538","url":null,"abstract":"","PeriodicalId":32029,"journal":{"name":"Proxies Jurnal Informatika","volume":"16 2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76499693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimasi Pearson Correlation untuk Sistem Rekomendasi menggunakan Algoritma Firefly","authors":"Melany Mustika Dewi","doi":"10.31294/inf.v9i1.10209","DOIUrl":"https://doi.org/10.31294/inf.v9i1.10209","url":null,"abstract":"","PeriodicalId":32029,"journal":{"name":"Proxies Jurnal Informatika","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79252182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisa Hasil Perbandingan Poly Kernel Dan Normalisasi Poly Kernel Pada Support Vector Machine Sebagai Metode Klasifikasi Citra Tanda Tangan","authors":"C. Widiawati, Suliswaningsih Suliswaningsih","doi":"10.31294/inf.v9i1.11288","DOIUrl":"https://doi.org/10.31294/inf.v9i1.11288","url":null,"abstract":"Signature is one of the important characteristics that can be used in verification of several documents, one of which is an academic document. Signature verification in the academic environment is important, especially in ensuring the authenticity of the lecturers or teaching staff signatures. Not a few students who choose to falsify the signature of a lecturer or teaching staff in order to facilitate their academic process, this is an important issue especially if the student is actually not eligible and does not meet the criteria to get a signature or endorsement from the lecturer concerned. A technique or method is needed that can help the process of verifying the signatures of lecturers and teaching staff in an academic environment. One technique that might be used is to use image processing techniques. In this study a classification will be made between the genuine and forgery signature images as a verification process of the authenticity of the lecturer signatures obtained by students. The data used is the signature image of a lecturer at Amikom Purwokerto University who was a examiner at the Practical Task Seminar. The method proposed in the classification process uses the Support Vector Machine (SVM) algorithm with two different kernels. Both kernels consist of poly kernel and normalized poly kernel, the selection of the two kernels is used to compare which results are more optimal. The results of this study are SVM by using poly kernel normalization to be able to give better results when compared to using poly kernel only. The results obtained using poly kernel normalization are an accuracy level of 79.43% and a specificity level of 100%.","PeriodicalId":32029,"journal":{"name":"Proxies Jurnal Informatika","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89591731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tata Kelola Teknologi Informasi Pada JNE Cabang Bekasi Menggunakan Framework Cobit 4.1","authors":"Andi Saryoko, Agus Junaidi, Sopiyan Dalis, Samudi Samudi, R. Aryanti, Haryani Haryani","doi":"10.31294/inf.v9i1.11708","DOIUrl":"https://doi.org/10.31294/inf.v9i1.11708","url":null,"abstract":"","PeriodicalId":32029,"journal":{"name":"Proxies Jurnal Informatika","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81608854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perbandingan Fungsi Optimasi Neural Network Dalam Klasifikasi Kelayakan Calon Suami","authors":"Melisa Handayani, Maisarah Riandini, Zakarias Zakarias","doi":"10.31294/inf.v9i1.12318","DOIUrl":"https://doi.org/10.31294/inf.v9i1.12318","url":null,"abstract":"adalah dengan menggunakan machine learning, khususnya menggunakan metode neural network . Penelitian ini bertujuan untuk menganalisa hasil klasifikasi kelayakan calon suami menggunakan metode neural network , dengan variasi kombinasi fungsi Rectified Linear Unit dan fungsi optimasi seperti Limited Memory Broyden–Fletcher–Goldfarb–Shanno Bound Constraint, Stochastic Gradient Descent dan Adative Moment Estimation . Hasil dari penelitian ini adalah bahwa kombinasi fungsi aktivasi Rectified Linear Unit dan fungsi optimasi Adaptive Moment Estimation merupakan yang Abstract The selection of a prospective husband is an important thing to consider to form a happy family. One way to help assess the suitability of a prospective husband is to use machine learning, especially using the neural network method. This study aims to analyze the results of the feasibility classification of prospective husbands using the neural network method, with variations in the combination of the Rectified Linear Unit function and optimization functions such as Limited Memory Broyden–Fletcher– Goldfarb–Shanno Bound Constraint, Stochastic Gradient Descent, and Adaptive Moment Estimation. The results of this study are that the combination of the Rectified Linear Unit activation function and the Adaptive Moment Estimation optimization function is the best, while the combination of the Rectified Linear Unit activation function and the Stochastic Gradient Descent optimization function is the worst, in terms of accuracy, precision and recall values respectively..","PeriodicalId":32029,"journal":{"name":"Proxies Jurnal Informatika","volume":"129 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89819973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sistem Penunjang Keputusan Dalam Penerimaan PraKerja Dengan Menggunakan Metode Analytic Hierarchy Process","authors":"Rini Oktaviani, N. Purwanti, Weni Anita, Cepi Cahyadi","doi":"10.31294/inf.v9i1.11032","DOIUrl":"https://doi.org/10.31294/inf.v9i1.11032","url":null,"abstract":"pemerintah masih sering keliru dalam menentukan calon penerima Kartu Pra Kerja, oleh karena itu dalam penelitian ini penulis menggunakan metode Analytical Hierarchy Process. Karena penilaian dengan menggunakan Analytical Hierarchy Process memberikan nilai yang baik yang dapat dijadikan Korban Analytical Abstract In the time of this pandemic, the country's economy experienced a substantial decline, the public was also exposed to the impact of the declining economy of Indonesia. In helping the economy of the community the government issued a policy to provide assistance in the form of Card Pre-Employment as one of the form of the program for workers affected by the Termination of Employment (PHK), the workers are laid off, as well as provide the potential and opportunity to the job seekers and students who have recently graduated from school to develop creativity and provides a soft skills in accordance with their interests through training online. Unfortunately, the government is still often mistaken in determining the prospective recipient of Card Pre-Employment, therefore in this study the authors use the method of Analytical Hierarchy Process. Because the assessment using Analytical Hierarchy Process is able to provide a good value that can be used as an alternative in the determination of the decision, namely on the Victim's Termination of Employment (PHK) with a value of 41%, so it can be concluded that the assessment of the Analytical Hierarchy Process is quite good.","PeriodicalId":32029,"journal":{"name":"Proxies Jurnal Informatika","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84603667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impelementasi Deep Learning untuk Optimasi Slump Menggunakan Convolutional Neural Network Pada PT. Handaru Wijaya Mulya","authors":"Hedi Pandowo, Dian Kusumaningrum, Vaisal Amir","doi":"10.31294/inf.v9i1.11713","DOIUrl":"https://doi.org/10.31294/inf.v9i1.11713","url":null,"abstract":"","PeriodicalId":32029,"journal":{"name":"Proxies Jurnal Informatika","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80506183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}