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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknik ITS Bulletin of Electrical Engineering and Informatics Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JITK (Jurnal Ilmu Pengetahuan dan Komputer) ILKOM Jurnal Ilmiah Journal of Computer Science and Informatics Engineering (J-Cosine) JURTEKSI Sewagati
Raras Tyasnurita
Institut Teknologi Sepuluh
Arts Humanities Computer Science & IT Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Pengenalan Sistem Aquaponik Cerdas untuk Memfasilitasi Kemampuan Mandiri pada Siswa Berkebutuhan Khusus di SLB Anggraeni, Wiwik; Risqiwati, Diah; Husniah, Lailatul; Sugiyanto; Aulia Sidharta, Hanugra; Budiyanta, Nova Eka; Djunaidy, Arif; Tyasnurita, Raras; Ali, Achmad Holil Noor; Divka, Princessa Sissy; Rahmanisa, Fathia
Sewagati Vol 8 No 2 (2024)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v8i2.967

Abstract

SLB ABCD Bakti Sosial merupakan sebuah sekolah luar biasa yang melayani siswa dengan kebutuhan khusus, terletak di Kecamatan Simo, Kabupaten Boyolali, Jawa Tengah.SLB tersebut memiliki 28 siswa SD, 18 siswa SMP, dan 17 siswa SMA, yang dibimbing oleh 11 guru. Berdasarkan diskusi dengan para guru, diketahui bahwa tempat tinggal siswa memiliki radius hingga 25 kilometer, karena jumlah SLB di Jawa Tengah yang belum sebanding dengan jumlah siswa. Metode pengajaran di SLB ini berbeda dengan sekolah umum, dengan kurikulum tahun 2013 yang mengalokasikan 40% pembelajaran pada materi teori dan 60\% pada keterampilan praktis. Untuk meningkatkan keterampilan siswa, Tim Pengabdian Masyarakat ITS mengusulkan penerapan sistem smart-aquaponic. Sistem ini tidak hanya menjadi alat latihan, tetapi juga sesuai dengan latar belakang pertanian masyarakat Boyolali, yang merupakan mata pencaharian utama di daerah tersebut. Materi video dan modul pendukung diperkenalkan untuk membantu para guru dalam membimbing siswa berkebutuhan khusus. Pengajaran ini bertujuan untuk meningkatkan keterampilan siswa dengan memperkenalkan integrasi budidaya ikan dan tanaman melalui otomatisasi sederhana. Otomatisasi ini meliputi pemberian pakan ikan secara terjadwal dan aliran air yang dapat disesuaikan berdasarkan kebutuhan tanaman. Dengan memperkenalkan smart-aquaponic di SLB ABCD Bakti Sosial, harapannya adalah guru dan siswa dapat mengembangkan keterampilan aquaponik dan menyesuaikannya dengan kebutuhan daerah sekitar.
Evaluation of Artificial Neural Network Model for Predicting Nitrogen Oxides (NOₓ) Concentration Arsyada, Muhammad Farrih Mahabbataka; Tyasnurita, Raras
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.4371

Abstract

Nitrogen Oxides (NOₓ) are air pollutants that require serious attention due to their potential negative impacts on human health, the environment, and the economy. This research is crucial to provide accurate predictive models of NOₓ concentration, which can serve as a foundation for decision-making and effective air pollution mitigation measures. The objective of this study is to evaluate several artificial neural network (ANN) models to determine the most effective model for accurately predicting NOₓ concentrations. One of the methods used for predicting air pollution data, such as NOₓ, is artificial neural networks (ANN). In this study, four ANN models were constructed and evaluated: Feed Forward Neural Network (FNN), Time Lagged Neural Network (TLNN), Seasonal Artificial Neural Network (SANN), and Long Short-Term Memory (LSTM). The models predict NOₓ concentration using data from the air quality dataset provided by the UCI Machine Learning Repository. Testing results indicate that the LSTM model performs best, achieving the lowest error value, characterized by 24 input nodes, three hidden nodes, one output node, and 300 training epochs. The RMSE values for LSTM, FNN, TLNN, and SANN are 57.3, 62.8, 64, and 89, respectively.
Text-Based Content Analysis on Social Media Using Topic Modelling to Support Digital Marketing Buana, Gandhi Surya; Tyasnurita, Raras; Puspita, Nindita Cahya; Vinarti, Retno Aulia; Mahananto, Faizal
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1636

Abstract

This study aims to create Social Media Analytics (SMA) tools to help Digital Marketers or Content Creators create content topics for creating text-based Instagram content and support digital marketing strategy. Since no SMA tools can provide topic discovery for text-based Instagram content, this research aims to make an SMA tool. The data requirements to make an SMA tool include content text, content caption text, likes, comments, upload time, and content category obtained through the Instascrapper. The method used in this study is the Topic Modelling method using the Latent Dirichlet Allocation (LDA) approach to find the most dominant topic in the content. Optical Character Recognition (OCR) performs an image transformation process to extract text from text-based Instagram content images. The results of SMA tool creation are tested on three expert users, which shows that 93% of test participants could use the SMA to find topic references, and 85% can still be used by users even though they find it difficult. Since the test result shows that SMA tools still need development, for further research, SMA tools can focus on developing the user experience to increase the value of user acceptance by paying attention to the ease of the SMA tools. Also, SMA tools can focus on target users such as Data Analysts, Business Intelligence Analysts, or others within a company to support decision-making for the marketing department.
Co-Authors Achmad Holil Noor Ali Adhi Yoga Muris Pamungkas Ahmad Muklason Algracevian Andrea Gibran Syahrial Amira Herwindyani Hutasuhut Andhika Prasandy Rachman Arif Djunaidy Arif Wibisono Arsyada, Muhammad Farrih Mahabbataka Aulia Sidharta, Hanugra Buana, Gandhi Surya Diah Risqiwati Divka, Princessa Sissy Erma Suryani Etria Sepwardhani Purba Faizal Mahananto Febriyora Surya Pratiwi Gabriella Icasia Hanifan Muhayat Ika Nurkasanah Jessica Patricia Halim Lailatul Husniah M. Yusuf Sulaiman Muhamad Rayhan Brameswara Muhammad Reza Pahlawan Nova Eka Budiyanta Pamungkas, Adhi Yoga Muris Puspita, Nindita Cahya Raffly Andico Devara Rahmanisa, Fathia Retno A. Vinarti Retno Aulia Vinarti Rifqi Rahmadrian Luthfiansyah Riksakomara, Edwin Rizka Wakhiddatus Sholikah Rully Agus Hendrawan Shafira Widya Hapsari Shinta Dewi SUGIYANTO Syifa Ilma Nabila Suwandi Wiwik Anggraeni