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All Journal ComEngApp : Computer Engineering and Applications Journal Indexia : Informatics and Computational Intelligent Journal
Welly Purnomo
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Computer Science & IT Engineering

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Automated Continuous IoT-based Monitoring System for Vaname Shrimp Cultivation Management Dahnial Syauqy; Buce Trias Hanggara; Welly Purnomo; Widhy Hayuhardhika Nugraha Putra; Nyoman Wira Prasetya
Computer Engineering and Applications Journal Vol 11 No 2 (2022)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (708.857 KB) | DOI: 10.18495/comengapp.v11i2.402

Abstract

Shrimp cultivation in Indonesia has been increasing since the introduction of white leg shrimp or often known as vaname (Penaeus vannamei) from the South Pacific waters. The use of a cultivation model with a circular pond with a diameter of 10 meters has begun to attract shrimp farmers in the northern coastal areas of Java, including Tuban Regency. There are several water quality parameters that affects survival rate such as Dissolved Oxygen (DO), Temperature, and Total Dissolved Solids (TDS). Shrimp pond farmers in Tuban Regency have used digital measuring tools to monitor the environmental conditions. However, these measurements cannot be carried out continuously for 24 hours. This often causes delays in identifying problems that occur in ponds and eventually impacts on reducing biomass weight, resulting in not achieving harvest targets. In this study, a continuous monitoring system for water quality management was designed and implemented. The system consists of an IoT-based water quality monitoring device combined with a Shrimp Aquaculture Management Information System. Based on the system that has been built, it is found that the system has been able to acquire all sensor parameters and send them to the server. The results of calibration and prediction using linear regression show that the average data reading error is achieving 14% for DO sensors, and 1% each for temperature and TDS sensors. The aggregated data is presented in tabular and graphic formats so that daily monitoring and predictions can be carried out in ponds.
ANALISIS SENTIMEN PADA ULASAN APLIKASI MOBILE BANKING MENGGUNAKAN METODE NAÏVE BAYES DENGAN KAMUS INSET Alyaa Nadira; Nanang Yudi Setiawan; Welly Purnomo
INDEXIA Vol 5 No 01 (2023): INDEXIA : Informatics and Computational Intelligent Journal
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/indexia.v5i01.5138

Abstract

Perkembangan teknologi informasi dan komunikasi berpengaruh pada partisipasi dan interaksi pengguna dalam online platform, seperti contohnya adalah pemberian ulasan pada sebuah aplikasi di Google Play Store. Bagi perusahaan, ulasan dapat digunakan untuk mengetahui kebutuhan pengguna dan dapat digunakan juga sebagai bahan evaluasi untuk mengembangkan dan memperbaiki aplikasinya, namun terkadang dalam sebuah ulasan terdapat ketidaksesuaian antara isi ulasan dengan pemberian rating pada ulasan, yang berarti bahwa sentimen dari sebuah ulasan tidak dapat dilihat dari jumlah rating pada ulasan. Dalam sebuah ulasan juga dapat terjadi kesalahan penulisan baik disengaja ataupun tidak disengaja yang membuat ulasan tersebut susah untuk dibaca dan dimengerti. Pada penelitian ini dilakukan analisis sentimen dengan studi kasus aplikasi Victoria Mobile Banking untuk mengklasifikasikan ulasan aplikasi kedalam ulasan yang bersifat positif atau negatif serta dapat memberi visualisasi hasil analisis ulasan. Proses klasifikasi pada sistem menggunakan metode Naïve Bayes. Data latih yang digunakan adalah data ulasan yang telah diberi label secara otomatis menggunakan kamus InSet yang telah melalui penyesuaian kata dan bobot. Algoritma klasifikasi tersebut diuji menggunakan confusion matrix dan menghasilkan nilai precision 90,4%, recall 100%, f-measure 95%, dan akurasi 93,1%.
Co-Authors Alyaa Nadira Buce Trias Hanggara Dahnial Syauqy Nanang Yudi Setiawan Nyoman Wira Prasetya Widhy Hayuhardhika Nugraha Putra