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Perbandingan Algoritma Conditional Random Field dan Hidden Markov Model pada Pos Tagging Bahasa Indonesia Singgih Briandoko; Atika Ratna Dewi; Muhammad Akbar Setiawan
Jurnal Teknologi Informasi, Ilmu Komputer dan Manajemen Vol 2 No 2 (2018): Teknikom Vol. 2 No. 2 Tahun 2018
Publisher : LPPM STMIK Widya Utama

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Abstract

Twitter is now an alternative source of real timeinformation for the public. Technological developmentscover all aspects of life, one of which is the field of language.Natural Language Processing (NLP) devices developed tosupport those needs are POS Tagger. This research use 10tweets and HMM algorithm get 62,7% accuracy level whileConditional Random Field algorithm get 71%. This showsthat CRF is better for performing POS tagging in Indonesianon Twitter. HMM and CRF can handle tagging of words thatare not in the corpus but the results are not very good.
TEMPERATURE CONTROL AND MONITORING SYSTEM (TCMS) BERBASIS INTERNET OF THINGS DENGAN SMARTPHONE ANDROID PADA AKUARIUM IKAN MOLLY BALON Setiawan, Muhammad Akbar; Andiko, Singgih Setia; Briandoko, Singgih; Kisworini, Rianti Yunita
Jurnal Teknologi Informasi, Ilmu Komputer dan Manajemen Vol 9 No 1 (2024): Vol 9 No 1 (2024): Teknikom Volume 9 Nomor 1 Tahun 2024
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) STMIK Widya Utama

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Abstract

Abstract— Approximately 363 types of freshwater ornamental fish bred in Indonesia and exported to European countries. Among the many types of freshwater ornamental fish, the focus will be on the Molly fish (Poecilia sphenops). Ornamental fish are well-known to the public as aquarium decorations. The Molly fish (Poecilia sphenops) is one of the ornamental fish with beautiful colors, belonging to the Poecilidae family originating from Mexico, Florida, and Virginia. The maximum size of this fish can reach 12-13 cm states that Molly fish (Poecilia sphenops) are widely cultivated because of their beautiful shape, color, omnivorous nature, and viviparous breeding. The Molly fish typically lives in water temperatures ranging from 15-27°C. They prefer a slightly alkaline pH, ranging from 7 to 8. This temperature and pH monitoring device was developed to address these challenges, making it easier for marble Molly fish farmers to control the temperature and pH levels in tarp ponds. The function of this device is to provide real-time temperature and pH data to the IoT application, which can be accessed by farmers. In addition to monitoring, the device also controls the temperature by sending commands to the heater to adjust to the optimal temperature for raising Molly fish.The performance of this device has been tested based on the Dimension of Quality for Goods, achieving a valid score of 82.26%. According to usability testing, the device achieved the highest performance in terms of usability and efficiency, with a score of 98.75%, indicating that the device is easy to use and efficient.