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All Journal Jurnal Computech & Bisnis (e-Journal) Analitika : Jurnal Magister Psikologi UMA TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Jurnal Ilmu Ekonomi dan Sosial (JIES) eProceedings of Engineering Journal of Computer Engineering: Progress, Application and Technology Jurnal INFOTEL
Sri Astuti
Telkom University
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Nursing Public Health Social Sciences

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KLASIFIKASI DATA DELAY DENGAN LFID STRATEGI FORWARDING MENGGUNAKAN MACHINE LEARNING UNTUK MEMAKSIMALKAN KINERJA JARINGAN NDN (NAMED DATA NETWORK) Sri Astuti; Tody Ariefianto Wibowo; Ratna Mayasari; Ibnu Asror; Gregorius Pradana Satriawan
Jurnal Computech & Bisnis (e-Journal) Vol 14, No 2 (2020): Jurnal Computech & Bisnis
Publisher : STMIK Mardira Indonesia, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1218.166 KB) | DOI: 10.55281/jcb.v14i2.230

Abstract

Named Data Network (NDN) is the future internet network that data-centric and adaptive to consumer requirement. Routing and forwarding systems on the NDN networks are different from IP networks due to the use of cache at each node on the network. The implementation of the Loop Free Inport-Dependent (LFID) routing protocol on NDN networks aims to eliminate loops on the network by eliminating the preferred routes or inefficient next hops. Forwarding strategies that can be implemented are Best Route, Access, Random, and Multicast. Therefore, machine learning technology is needed with various classification methods that can be implemented in machine learning so the output gives the recommendations that can be used to maximize the performance of the NDN network. The final result of this study recommends that the forwarding strategies of Best Route and Access provide good delay values, which in the range of 150 ms to 300 ms. Random forwarding strategy with a payload size> = 3072 kbps still provides a good delay value to the network, which in the 150 to 300 ms range. All forwarding strategies of Best Route, Access, Random, and Multicast provide delay values with a very good category of delay values, which is below 150 ms if the type of interest (data) that requested to the network is a popular interest. Keywords: Named Data Network , Routing, Forwarding, Machine Learning.DOI : http://doi.org/10.5281/zenodo.4320264
Level Alexithymia Sebagai Mediator Motif Komunikasi dan Kepuasan Komunikasi Nurul Adiningtyas; Sri Wahyuning Astuti
Jurnal Ilmu Ekonomi dan Sosial (JIES) Vol 11, No 2 (2022): JULI 2022
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jies.v11i2.15803

Abstract

Masyarakat Indonesia masuk dalam kategori pengguna media sosial diatas rata-rata global yakni rata rata menggunakan selama 2 jam 24 menit. Tingginya penggunaan media sosial tentu membawa pengaruh terhadap penggunanya khususnya dalam cara mereka berkomunkasi. Ada perubahan komunikasi saat menggunakan media sosial, dari komunikasi tatap muka langsung menjadi melalui perantara. Kondisi ini menimbulkan perbedaan kepuasaan dalam komunikasi yang mereka lakukan. Penelitian melihat Hubungan antara kepuasan komunikasi dengan level alexithymia pengguna media sosial. Jenis penelitian yang digunakan dalam penelitian ini adalah kuantitatif korelasional. Sampel dalam penelitian ini adalah pengguna media sosial dengan teknik pengambilan dengan menggunakan random sampling dengan bantuan google form. Kepuasan Komunikasi diukur dengan menggunakan Skala Komunikasi dari Hecth dan Kepuasan relasional dari Norton. Sementara itu untuk Level alexithymia menggunakan diukur menggunakan Toronto Alexithymia Scale, (TAS-20) TAS-20 terdiri dari 20 item. Hasil penelitian menunjukkan ada hubungan yang positif antara kepuasan komunikasi dengan Level Alexithymia. Dengan demikian semakin tinggi Kepuasaan komunikasi maka semakin tinggi level Alexithymia.
Intensity of Tik Tok Use and Depression with Social comparison as a Mediator Variable sri wahyuning astuti
Analitika: Jurnal Magister Psikologi UMA Vol. 14 No. 2 (2022): ANALITIKA DESEMBER
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/analitika.v14i2.7363

Abstract

Tik Tok users until the end of 2021 managed to touch 2 billion worldwide. Being the second most populous country to use Tik Tok, a number of problems were reported. Starting from the very high frequency of use, to issues related to the mental health of its users. The study aims to find out the relationship between Tik Tok use and Depression and the social comparisons felt by its users. The type of research used in this study is correlational quantitative. There were 108 respondents in this study collected through Google forms. The measuring instrument used to see the intensity of social media use uses the intensity scale of using Tik Tok which consists of passion, attention, duration and frequency. Meanwhile, to measure Depression using Scala Beck and the level of social comparison using the IOWA scale. The results of the data analysis show that there is a significant relationship between the use of Tik Tok and Depression with social comparisons as a mediator
Pelatihan Menjadi Presenter Handal di SMK Telkom Bandung Sri Wahyuning Astuti; Martha Tri Lestari; Hadi Purnama
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 3 No. 1 (2023): Januari 2023 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/altifani.v3i1.351

Abstract

Berbicara di depan umum masih menjadi momok yang menakutkan bagi sebagain orang. Ketakutan berbicara di depan umum, pada umumnya terjadi karena ketidaksiapan materi. Padahal untuk dapat menjalin hubungan yang positif dengan lingkungan sekitar, dan membuat content media sosial mereka diperlukan kemampuan public speaking yang handal. Menjadi News Anchor, adalah satu dari sekian banyak ragam public speaking. Menjadi News Anchor adalah milik siapa saja dan ketrampilan menjadi News Anchor adalah bagian dari kurikulum merdeka belajar. Karena itulah, pengabdian masyarakat dengan masyarakat sasar SMK Telkom memberikan pelatihan menjadi news Anchor yang handal mulai dari membuat naskah berita hingga teknik announcing dan membawakan berita untuk khalayak. Pengabdian Masyarakat ini menyasar Siswa SMK Telkom jurusan Multimedia yang berjumlah 30 orang. Selain memberikan Materi tertulis, Siswa juga melakukan praktek langsung terkait teknik pembuatan naskah berita dan penyajian berita di televisi maupun media digital.
Simulasi Penerjemah SIBI (Sistem Isyarat Bahasa Indonesia) Menggunakan Tensorflow Dan Convolutional Neural Network (CNN) Muhammad Azka Imaddudin; Ida Wahidah Hamzah; Sri Astuti
eProceedings of Engineering Vol 9, No 6 (2022): Desember 2022
Publisher : eProceedings of Engineering

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

Abstract

Abstrak—Bahasa Isyarat biasanya digunakan oleh penyandang disabilitas tunarungu untuk berkomunikasi dengan orang lain. Permasalahan yang sering terjadi dalam komunikasi menggunakan bahasa isyarat adalah ketika orang belum mengerti berkomunikasi dengan penyandang disabilitas tunarungu. Penelitian ini membuat simulasi penerjemah SIBI (Sistem Isyarat Bahasa Indonesia) secara realtime dan non realtime. Dataset (kumpulan gambar bahasa isyarat) total 1200 gambar untuk 6 kelas huruf (A, B, C, D, E, dan F). Kemudian dataset dipisahkan untuk pelatihan 90% dan evaluasi 10%. Sebelum pelatihan dengan model, dataset dianotasikan perkelasnya. Model pelatihan yang digunakan yaitu SSD MobileNet V2. Dataset dilatih dengan 3 skema yaitu 10.000 step untuk skema 1. 20.000 step untuk skema 2. 30.000 step untuk skema 3. Setelah dilatih model akan dievaluasi untuk membangun model predeksi deteksi. Terakhir membuat program deteksi secara realtime dan non realtime. Dalam penelitian ini hasil yang dicapai bahwa simulasi berkerja dengan baik. Rata-rata tingkat klasifikasi realtime 91% dan tingkat klasifikasi non realtime 60%. Berdasarkan hasil pelatihan dan evaluasi untuk semua skema menghasilkan rata-rata learning rate 0,068 iteration/steps, rata-rata total loss 0,32 , rata-rata loss localization 0,067, rata-rata loss classification 0,13, mAP 0,75, dan mAR 0,78. Berdasarkan hasil tersebut sudah cukup baik dalam menerjemahkan Bahasa isyarat. Kata kunci — SIBI, Deteksi Objek, Tuna Rungu, Tensorflow, SSD MobileNet V2, CNN
Rancang Bangun Alat Penyiraman Otomatis Berbasis Internet Of Things Dengan Notifikasi Whatsapp M. Dwiki Fadhilah; Iman Hedi Santoso; Sri Astuti
eProceedings of Engineering Vol 8, No 6 (2021): Desember 2021
Publisher : eProceedings of Engineering

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Abstract

Abstrak Petani di Indonesia sangat mengandalkan air hujan untuk memenuhi kebutuhan air ditanaman. Kekurangan air mempengaruhi tumbuh kembang tanaman, sehingga keberhasilan panen sangat dipengaruhi oleh seberapa cukup tanaman mendapat asupan air dari tanah. Penyiraman otomatis tanaman berdasarkan kelembapan tanah dengan notifikasi Whatsapp dapat menerima notifikasi berupa pesan berbasis mikrokontroler adalah salah satu cara yang dapat digunakan untuk memantau tanaman tetap tercukupi kebutuhan air-nya. Sehingga pemilik tanaman hanya perlu memantau perkembangan tanaman tanpa harus terjun ke perkebunan. Sistem ini menggunakan ESP32 sebagai mikrokontroler dan menggunakan sensor Soil Moisture YL-69 dan sensor suhu DHT11 untuk mengukur kelembapan tanah maka hasil pengukuran kelembapan tanah yang diperoleh akan dikirim ke smartphone pemilik dalam bentuk notifikasi Whatsapp. Keypad untuk mengganti tingkat kelembapan yang diinginkan dan dapat menyesuaikan dengan semua tanaman. Ketika sensor mendeteksi tanah sedang kering, ESP32 akan memerintahkan Relay menghidupkan pompa air dan menyiram tanaman. Hasil pengujian sistem penyiraman otomatis dapat berfungsi dengan baik. Secara keseluruhan kinerja sistem penyiraman otomatis ini sesuai dengan rancangan yaitu berhasil mendapatkan informasi kelembapan tanah dari aplikasi Whatsapp. Dari pengujian dan analisis QoS didapatkan nilai QoS terbaik saat free hours dini hari dengan Delay terkecil sebesar 1,895 second, Throughput terbesar yaitu 2241,7667 bps, nilai packetloss terendah yaitu 0%. Kata Kunci : ESP32, Keypad, Whatsapp Abstract Farmers in Indonesia rely heavily on rainwater to meet their water needs. Lack of water affects the growth and development of plants, so that the success of the harvest is greatly influenced by how well the plants get enough water intake from the soil. Automatic watering of plants based on soil moisture with Whatsapp notifications can receive notifications in the form of microcontrollerbased messages is one way that can be used to monitor plants that their water needs are met. So that the plant owner only needs to monitor the development of the plant without having to go into the plantation. This system uses ESP32 as a microcontroller and uses a YL-69 Soil Moisture sensor and a DHT11 temperature sensor to measure soil moisture, the results of the soil moisture measurement obtained will be sent to the owner's smartphone in the form of a Whatsapp notification. Keypad to change the desired humidity level and can adapt to all plants. When the sensor detects that the soil is dry, the ESP32 will instruct the relay to turn on the water pump and water the plants. The test results of the automatic watering system can function properly. Overall, the performance of this automatic watering system is in accordance with the design, namely successfully obtaining soil moisture information from the Whatsapp application. From testing and QoS analysis, the best QoS value was obtained during free hours in the early hours of the morning with the smallest delay of 1.895 seconds, the largest throughput of 2241.7667 bps, and the lowest packetloss value of 0%. Keywords : ESP32, Keypad, Whatsapp
Analisis Perbandingan Algoritma Decision Tree, Random Forest, dan Naïve Bayes untuk Prediksi Banjir di Desa Dayeuhkolot Muhammad Bagas Arya Darmawan; Favian Dewanta; Sri Astuti
TELKA - Jurnal Telekomunikasi, Elektronika, Komputasi dan Kontrol Vol 9, No 1 (2023): TELKA
Publisher : Jurusan Teknik Elektro UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/telka.v9n1.52-61

Abstract

Bencana alam yang masih terjadi di kota–kota atau daerah di sepanjang bantaran sungai adalah bencana banjir. Bencana ini sering terjadi di Kabupaten Bandung, khususnya Desa Dayeuhkolot. Penyebab banjir umumnya karena volume air sungai meningkat dan intensitas curah hujan yang tinggi. Di Desa Dayeuhkolot, pencegahan banjir sulit dilakukan karena ketidakakuratan data dalam prediksi banjir yang diberikan oleh pemerintah daerah kepada masyarakat. Oleh karena itu, penelitian ini dilakukan untuk memprediksi banjir yang lebih akurat dengan performa dan akurasi yang lebih baik. Penelitian ini menggunakan dataset yang diperoleh dari Balai Besar Wilayah Sungai (BBWS) Citarum untuk wilayah Dayeuhkolot dengan parameter tinggi muka air sungai dan intensitas curah hujan dari tahun 2015 – 2018. Metode yang digunakan untuk mendeteksi terjadinya banjir yaitu dengan algoritma machine learning Decision Tree, Random Forest, dan Naïve Bayes. Hasil eksperimen menunjukkan bahwa metode dengan performa terbaik adalah Random Forest dibandingkan metode lain dengan rata–rata nilai akurasi, presisi, recall, dan f1-score masing-masing sebesar 99,05%, 97,91%, 99,18%, 98%, serta nilai waktu komputasi rata rata 0,2561 detik dari 3 kali pengujian yang dilakukan berdasarkan rasio pembagian data yang berbeda. A natural disaster still happening in the cities or districts along riverbanks is a flood disaster. This disaster frequently occurs in Bandung Regency, especially Dayeuhkolot Village. The cause of the flooding is generally due to increased river water volume and high rainfall intensity. At Dayeuhkolot Village, flood prevention is difficult because of the inaccurate data in flood predictions provided by the local government to the local community. Therefore, research was made to predict the flood with better performance and accuracy. This research uses a dataset from Balai Besar Wilayah Sungai (BBWS) Citarum for the Dayeuhkolot area with river water level and rainfall intensity parameters from 2015 – 2018. Machine learning algorithms with Decision Trees, Random Forests, and Naïve Bayes are used to detect flood disasters. From the experiment result, the method with the best performance is Random Forest, with the other methods with average values of accuracy, precision, recall, and f1-score are 99.05%, 97.98%, 99.18%, and 98%, respectively. The average value of computation time is 0.25616072 seconds from 3 times the tests were carried out based on different data partitions.
Training in academic information system usage at Ash Shidiq Integrated Islamic Junior High School Dawam Dwi Jatmiko Suwawi; Ibnu Asror; Yanuar Firdaus Arie Wibowo; Tora Fahrudin; Sri Astuti; Paramita Mayadewi; Alya Ghaitsa Rizky Pertiwi
Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Vol 8, No 3 (2023): August 2023
Publisher : University of Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/abdimas.v8i3.10516

Abstract

Ash-Shidiq Foundation recently established the Integrated Islamic Middle School (SMP IT). Currently, the school manages academic data manually, either on paper or through spreadsheet applications. Recognizing an opportunity, the Telkom University Software Engineering Expertise Group decided to provide community service by implementing a web-based academic information system for the school. This system is hosted on a server accessible via the Internet, enabling staff, teachers, and students to access it. It aims to simplify academic data reporting for school managers. The entire community service project, from initial observation to system installation, training, video documentation, and final report preparation, spanned approximately six months. Training sessions were conducted in a classroom setting for school principals, staff, and teachers. Feedback from this community service activity showed that 25% strongly agreed, 37.5% agreed, and 37.5% were neutral regarding the suitability of the training material to partners' needs. Regarding the presentation of material, 75% strongly agreed, 25% agreed, and 50% were neutral, with 37.5% in agreement and 12.5% in disagreement about the usefulness of the technology offered.
All-in-one computation vs computational-offloading approaches: a performance evaluation of object detection strategies on android mobile devices Muhammad Abdullah Rasyad; Favian Dewanta; Sri Astuti
JURNAL INFOTEL Vol 13 No 4 (2021): November 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i4.700

Abstract

Object detection gives a computer ability to classify objects in an image or video. However, high specified devices are needed to get a good performance. To enable devices with low specifications performs better, one way is offloading the computation process from a device with a low specification to another device with better specifications. This paper investigates the performance of object detection strategies on all-in-one Android mobile phone computation versus Android mobile phone computation with computational offloading on Nvidia Jetson Nano. The experiment carries out the video surveillance from the Android mobile phone with two scenarios, all-in-one object detection computation in a single Android device and decoupled object detection computation between an Android device and an Nvidia Jetson Nano. Android applications send video input for object detection using RTSP/RTMP streaming protocol and received by Nvidia Jetson Nano which acts as an RTSP/RTMP server. Then, the output of object detection is sent back to the Android device for being displayed to the user. The results show that the android device Huawei Y7 Pro with an average FPS performance of 1.82 and an average computing speed of 552 ms significantly improves when working with the Nvidia Jetson Nano, the average FPS becomes ten and the average computing speed becomes 95 ms. It means decoupling object detection computation between an Android device and an Nvidia Jetson Nano using the system provided in this paper successfully improves the detection speed performance.
Caching and Forwarding Mechanism for Smart Grid Communications Networks Arif Faturrachman; Fakhri Rahmatullah; Sayid Huseini Elfarizi; Ratna Mayasari; Ridha Muldina Negara; Sri Astuti; Kharisma Bani Adam; Arif Indra Irawan
CEPAT Journal of Computer Engineering: Progress, Application and Technology Vol 2 No 03 (2023): September 2023
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cepat.v2i03.6292

Abstract

A smart grid aims to integrate alternative and renewable energy sources. NDN has the advantage of being better than IP networks and can optimize the delivery of information. The concept of Named Data Networking (NDN) is designed for smart grid systems. This study aims to implement the NDN concept on a smart grid system and analyze forwarding and caching strategies. The implementation of the system strategy is supported using the NDN network topology, which is based on IEEE 39. The author evaluates network performance by paying attention to parameters such as delay and cache hit ratio. From the data the author obtained, it can be concluded that the best route-LRU and client control-LRU systems are better choices to be implemented in a smart grid communication system than the best route-FIFO and client control-FIFO systems. In other words, the LRU caching override method is superior to the FIFO caching override method. Meanwhile, the forwarding method does not show significant graphical results. This happens because the forwarding method that the authors use has the same route determination. Something that differentiates between the best route and client control is only the control of selecting the path. The best route is controlled by the producer, and client control is controlled by the consumer.
Co-Authors Alya Ghaitsa Rizky Pertiwi Arif Faturrachman Arif Indra Irawan Dawam Dwi Jatmiko Suwawi Fakhri Rahmatullah Favian Dewanta Gregorius Pradana Satriawan Hadi Purnama Ibnu Asror Ida Wahidah Hamzah Iman Hedi Santoso Kharisma Bani Adam M. Dwiki Fadhilah Martha Tri Lestari Muhammad Abdullah Rasyad Muhammad Azka Imaddudin Muhammad Bagas Arya Darmawan Nurul Adiningtyas Paramita Mayadewi Ratna Mayasari Ridha Muldina Negara Sayid Huseini Elfarizi Tody Ariefianto Wibowo Tora Fahrudin Yanuar Firdaus Arie Wibowo