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Integrasi Teknologi Internet of Things dalam Pengembangan Sistem Pemantauan Kualitas Air dan Kesehatan Udang Air Tawar untuk Optimalisasi Produk Perikanan Ginardi, Raden Venantius Hari; Husni, Muchammad; Sholikah, Rizka Wakhidatus; Indrawanti, Annisaa Sri; Sabilla, Irzal Ahmad; Oktarina, Eka Sari; Rasmana, Susijanto Tri; Hariyawan, Mohammad Yanuar; Briantoro, Hendi; Wicaksono, M. Januar Eko; Mohammad, Iki Adfi Nur; Syafa, Ilhan Ahmad; Wicaksono, Rahmad Aji; Luqmanulhakim, Naufan Zaki; Kusuma, Zulfa Hafizh; Santosa, Hafis Akmaldi; Wijaya, Agas Ananta
Sewagati Vol 9 No 1 (2025)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v9i1.2487

Abstract

Pengelolaan kualitas air adalah salah satu komponen penting yang perlu diperhatikan dalam budidaya perikanan, terutama pada udang air tawar. Faktor kualitas air dapat mempengaruhi hasil produksi dan keberhasilan dari budidaya udang. Beberapa komponen dalam air yang perlu diperhatikan dalam budidaya udang antara lain suhu, oksigen terlarut, salinitas, dan PH dari air. Keempat komponen tersebut dapat memberikan gambaran terkait kondisi air dari budidaya udang apakah dalam kondisi baik atau dalam kondisi yang dapat mengganggu pertumbuhan udang. Pemantauan keempat komponen utama tersebut idealnya dilakukan setiap hari untuk dapat melakukan intervensi jika terjadi ketidak seimbangan kondisi air. Pada pengabdian masyarakat ini dibangun perangkat Internet of Things (IoT) untuk melakukan pemantauan kondisi air pada budidaya udang air tawar. Perangkat IoT memungkinkan dilakukan pemantauan kondisi air dari jauh dengan memanfaatkan aplikasi mobile. Hal tersebut dapat mempermudah petani udang untuk melakukan pemantauan tanpa harus datang langsung ke lokasi budidaya. Selain itu pelatihan pada mitra juga dilakukan untuk memberikan sosialisasi penggunaan alat dan implementasinya. Hasil luaran dari pengabdian masyarakat ini berupa prototype alat IoT untuk monitoring yang telah diimplementasikan pada pihak mitra, publikasi pada laman berita daring, HKI (Hak Kekayaan Intelektual) video abmas, dan jurnal pengabdian kepada masyarakat.
MULTI-DOCUMENT SUMMARIZATION USING A COMBINATION OF FEATURES BASED ON CENTROID AND KEYWORD Ranggianto, Narandha Arya; Purwitasari, Diana; Fatichah, Chastine; Sholikah, Rizka Wakhidatus
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 21, No. 2, July 2023
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v21i2.a1195

Abstract

Summarizing text in multi-documents requires choosing important sentences which are more complex than in one document because there is different information which results in contradictions and redundancy of information. The process of selecting important sentences can be done by scoring sentences that consider the main information. The combination of features is carried out for the process of scoring sentences so that sentences with high scores become candidates for summary. The centroid approach provides an advantage in obtaining key information. However, the centroid approach is still limited to information close to the center point. The addition of positional features provides increased information on the importance of a sentence, but positional features only focus on the main position. Therefore, researchers use the keyword feature as a research contribution that can provide additional information on important words in the form of N-grams in a document. In this study, the centroid, position, and keyword features were combined for a scoring process which can provide increased performance for multi-document news data and reviews. The test results show that the addition of keyword features produces the highest value for news data DUC2004 ROUGE-1 of 35.44, ROUGE-2 of 7.64, ROUGE-L of 37.02, and BERTScore of 84.22. While the Amazon review data was obtained with ROUGE-1 of 32.24, ROUGE-2 of 6.14, ROUGE-L of 34.77, and BERTScore of 85.75. The ROUGE and BERScore values outperform the other unsupervised models.
Abstractive and Extractive Approaches for Summarizing Multi-document Travel Reviews Ranggianto, Narandha Arya; Purwitasari, Diana; Fatichah, Chastine; Sholikah, Rizka Wakhidatus
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 6 (2023): December 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i6.5170

Abstract

Travel reviews offer insights into users' experiences at places they have visited, including hotels, restaurants, and tourist attractions. Reviews are a type of multidocument, where one place has several reviews from different users. Automatic summarization can help users get the main information in multi-document. Automatic summarization consists of abstractive and extractive approaches. The abstractive approach has the advantage of producing coherent and concise sentences, while the extractive approach has the advantage of producing an informative summary. However, there are weaknesses in the abstractive approach, which results in inaccurate and less information. On the other hand, the extractive approach produces longer sentences compared to the abstractive approach. Based on the characteristics of both approaches, we combine abstractive and extractive methods to produce a more concise and informative summary than can be achieved using either approach alone. To assess the effectiveness of abstractive and extractive, we use ROUGE based on lexical overlaps and BERTScore based on contextual embeddings which it be compared with a partial approach (abstractive only or extractive only). The experimental results demonstrate that the combination of abstractive and extractive approaches, namely BERT-EXT, leads to improved performance. The ROUGE-1 (unigram), ROUGE-2 (bigram), ROUGE-L (longest subsequence), and BERTScore values are 29.48%, 5.76%, 33.59%, and 54.38%, respectively. Combining abstractive and extractive approach yields higher performance than the partial approach.