47 research outputs found
Analisis Unjuk Kerja Aplikasi VoIP Call Android di Jaringan MANET [Performance Analysis of VoIP Call Application Android in MANET (Mobile Ad Hoc Network)]
No full textPenelitian ini bertujuan menganalisis kinerja aplikasi VoIP call android di jaringan MANET (mobile ad hoc network). Hasil pengujian menunjukan bahwa aplikasi VoIP call android dapat digunakan di jaringan MANET. Delay yang dihasilkan paling besar di pengujian indoor dengan jarak 11-15 meter yakni sebesar 0,014624811 seconds. Packet loss yang dihasilkan pada range 1%-2% sedangkan standar packet loss yang ditetapkan oleh CISCO untuk layanan aplikasi VoIP adalah < 5%. Jitter yang dihasilkan yakni antara 0,01-0,06 seconds sedangkan standar yang ditetapkan oleh CISCO adalah ≤ 30 ms atau 0,03 seconds. Throughput yang dihasilkan pada proses pengujian yakni antar 161 kbps-481 kbps. *****This study aims to analyze the performance of VOIP call android application in the MANET (mobile ad hoc network). The results showed that VoIP applications could be implemented in MANET network. The highest delay is produced in indoor testing with distance of 11-15 meters, which is equal to 0.014624811 seconds. Packet loss is generated in the range of 1% -2%, while packet loss standards set by Cisco for VoIP application services are <5%. The jitter is between 0.01 to 0.06 seconds, while the standard set by CISCO is ≤ 30 ms or 0.03 seconds. Throughput generated in the testing process is between 161 kbps-481 kbps.</p
APLIKASI MIND MAPPING UNTUK SISWA SEKOLAH DASAR DAN SEKOLAH MENENGAH LANJUTAN DENGAN MENGGUNAKAN METODE GRAF BERBASIS ANDROID
Get PDFABSTRACTThe purpose of this research is to create a mind mapping application displays course materials for elementary school students , junior high schools and high schools based on Android by using PhoneGap and jQuery Mobile framework . Mind mapping is a way of learning by noting that rely on creative image and relationship with each other by using pictures , words, numbers , logic and color became a unique record .Basically a mind map is a directed graph that has a central object and other objects , the mind map can be drawn on a graph with the words or topics as a point or a node and a link between two nodes is a side that has a direction with the assumption, that the has the meaning of section trending . Let G = ( V , E ) where V is the set of points A and B, can be written V = { A , B , C , D , E , F , G } and E is the set of sides that have direction Dangan e = { ( A , B ) , ( A , C ) , ( B , E ) , ( B , F ) , ( C , G ) } . G is a mind map , then A is the main topic or idea with B and C are part of A. E and F are part of B , and G is part of the C.Keywords : Andoid, Graph, JQuery Mobile, Mind Map, PhoneGap, Web application mobile
Convolutional Neural Network-Based Model for Indonesian Offensive Text Classification
Get PDFThis study presents a Convolutional Neural Network (CNN)-based model for classifying offensive and non-offensive Indonesian text using a dataset of 10,054 tweets collected from Twitter/X. The dataset was manually annotated into two classes and processed through a series of text-cleaning, tokenization, and padding steps before being used to train the model. Several training durations were tested to evaluate the effect of epoch variation on model performance. The results show that the model trained for 70 epochs achieved the best overall performance, with a testing accuracy of 86.73%, precision of 0.8793, recall of 0.8834, F1-score of 0.8814, and a ROC-AUC value of 92.08%. The confusion matrix analysis indicates strong classification capability for both classes, with the model performing slightly better in identifying offensive text due to distinctive lexical patterns. These findings demonstrate that the CNN architecture, supported by trainable word embeddings, is effective for Indonesian offensive-text classification. Future improvements may include integrating pretrained language models or expanding the dataset to enhance contextual understanding and robustness
KLASTERISASI MEDIA PEMBELAJARAN DARING DI ERA PANDEMI COVID-19 MENGGUNAKAN METODE AGGLOMERATIVE
Get PDFThis study aims to determine the use of learning media clusters from more effective and efficient in terms of user assessments, both students, and teachers in the midst of the Coronavirus Disease 2019 (Covid-19) pandemic. The method used in this research is the agglomerative algorithm method hierarchial clustering to classify online learning media according to user ratings. This method will calculate the grouping or clustering with several agglomerative methods, namely the single linkage method, average linkage, and complete the environment. Each of these methods can perform distance calculations Euclidean distance, which will later determine the appropriate online learning media cluster user ratings. The data used is user assessment data (students, students and teachers). The result of clusterization for learning media that is most widely used is google classroom which is included in the learning application cluster, while for the internet, users choose internet data quota and for learning devices users use smartphones more.Keywords : Agglomerative, Klasterisasi, Media Pembelajaran Daring
Implementation of Finite State Automata to Optimize the Waste Collection Process in the Greenify Application
Get PDFEfficient waste management is a major challenge in urban life. One promising solution is the use of Finite State Automata (FSA) to optimize the waste containment process within the Greenify application. This study aims to explore the application of FSA in designing the logical flow for waste management, which includes identifying waste types, collection locations, and pick-up schedules. The methodology employed is a theoretical approach that implements the FSA model to regulate statuses and transitions between different steps in the waste management process. The results demonstrate that FSA can improve operational efficiency, reduce management errors, and enhance the user experience. The application of FSA in Greenify facilitates a more structured and automated waste management system, while also improving the accuracy of scheduling and waste collection. This conclusion highlights the significant potential of FSA as a technological solution for environmentally friendly waste management, with the goal of optimizing the performance of the Greenify application and advancing urban waste management practices
IMPLEMENTASI DEEP LEARNING MENGGUNAKAN LONG SHORT-TERM MEMORY UNTUK PREDIKSI STABILITAS PONDASI TAHAN GEMPA
No full textPondasi merupakan elemen struktural yang sangat krusial dalam menjamin kestabilan bangunan terhadap beban gempa. Ketidakstabilan pada sistem pondasi dapat memicu keruntuhan total struktur meskipun elemen atas telah dirancang tahan gempa. Penelitian ini bertujuan untuk mengembangkan model prediksi stabilitas pondasi menggunakan pendekatan deep learning berbasis Long Short-Term Memory (LSTM) dengan memanfaatkan data gaya dan momen sambungan (joint reactions) hasil analisis struktur dari perangkat lunak SAP2000. Dataset terdiri atas tiga jenis bangunan berbeda, yakni pondasi utama, gedung service, dan gedung klinik teduh, yang masing-masing memuat komponen gaya (F1, F2, F3) dan momen (M1, M2, M3). Data diproses melalui tahapan normalisasi, penyusunan time series lima langkah ke belakang, dan pelatihan model menggunakan arsitektur LSTM dua lapis dengan dropout 0,2. Evaluasi dilakukan dengan skema validasi silang (Time Series Split) dan pengujian data unseen. Hasil penelitian menunjukkan bahwa model mampu melakukan prediksi dengan akurasi, presisi, recall, dan F1-score sebesar 1,0000. Grafik perbandingan training loss dan validation loss memperlihatkan konvergensi yang stabil tanpa indikasi overfitting. Sistem ini juga berhasil mengintegrasikan deteksi noise berbasis threshold error, memungkinkan klasifikasi anomali struktural secara otomatis. Kesimpulan dari penelitian ini menyatakan bahwa model LSTM sangat efektif dalam memprediksi respons pondasi terhadap gempa serta mendeteksi ketidaknormalan pola gaya dan momen
PENERAPAN STRING MATCHING PADA INFORMATION RETRIEVAL DARI EKSTRAKSI METADATA DAN ANALISIS AKURASI VIDEO YOUTUBE
No full textMeningkatnya jumlah konten di platform youtube shorts menghadirkan tantangan dalam menyaring informasi yang relevan serta menghindari konten yang mengandung kata-kata negatif. Penelitian ini mengembangkan sistem information retrieval dengan metode string matching untuk mencocokkan kata kunci yang dimasukkan pengguna dengan metadata video, seperti judul, hashtag, dan transkripsi audio. Sistem ini dirancang sebagai aplikasi berbasis web menggunakan PHP dan Python dengan framework Laravel serta PostgreSQL sebagai basis data. Pengujian dilakukan untuk mengevaluasi tingkat akurasi dan performa sistem. Hasil pengujian menunjukkan bahwa sistem mencapai akurasi hingga 82,5% saat menggunakan lebih dari 10 kata kunci, dengan 33 data valid. Pengujian performa juga menunjukkan bahwa MacBook Pro M1 memiliki efisiensi terbaik dibandingkan perangkat lainnya. Penerapan semantik dalam sistem memungkinkan peningkatan akurasi dengan mengurangi ambiguitas makna kata kunci
SURVEI DAN ANALISIS PENGGUNAAN INTERNET DI UNIVERSITAS JANABADRA
Get PDFThis research was conducted with the aim to find out the largest absorption of bandwidth used to access anything (eg social media, youtube and others) and to find out the factors that make internet connections at Janabadra University often not connected or slow connections. The method used in this study is to use the method of distributing questionnaires to all internet users at Janabadra University both employees, lecturers and students then the results of the questionnaire are processed and analyzed using regression analysis. Meanwhile, to determine the amount of bandwidth traffic using Quality of Service (QoS) analysis namely throughput, jitter and delay. To measure the QoS, the software is wireshark. Wireshark is used to record or view internet access distribution traffic that is used by users in Janabadra University. The results obtained that the highest bandwidth uptake is used for access to YouTube, online games and social media live streaming and it is evident from the analysis of internet usage traffic at Janabadra University that due to bandwidth is often used for unsuitable access, it produces a very small throughput with an average 2,092 kbps average. Keywords : Delay, Jitter, Throughput, Quality of Service
Towards a Common European Border Service? CEPS Working Document No. 331, June 2010
Get PDFWhat should be the future institutional configurations of the second generation of the EU’s Integrated Border Management strategy for the common external borders? The Stockholm Programme endorsed by the European Council on December 2009 and the European Commission’s action plan implementing it published in April 2010 have brought back to the EU policy agenda the feasibility of setting up a European system of border guards as a long-term policy vision. This Working Document examines the origins of this proposal and aims at thinking ahead by asserting that any future discussion and study in this context should be refocused by initially addressing two central questions: First, what kind of 'border guard' and what kinds of 'border controls' does the EU need in light of the current EU acquis on external border crossings and the Schengen Borders Code? Second, what would be the 'added value' of any new institutional arrangement at the current stage of European integration? Author Sergio Carrera, CEPS Research Fellow, argues that these questions could presage the establishment of a common European border service aimed at i) guaranteeing a uniform implementation and high-standard application of EU border law and the materialisation of a European approach to external border controls; ii) ensuring the respect of fundamental rights and guarantees in all external border control-related activities; iii) facilitating the (de)politicisation and accountability of external border controls; and iv) addressing issues of solidarity and mutual trust building across the external borders in an enlarged EU
