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All Journal Jurnal Teknik Informatika (JUTIF) JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga) Blend Sains Jurnal Teknik MDP Student Conference Journal Of Artificial Intelligence And Software Engineering The Indonesian Journal of Computer Science
Belen Septian
Universitas Bangka Belitung
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Journal : The Indonesian Journal of Computer Science

 1 
Optimization of Corn Crop Nitrogen Percentage Using Genetic Algorithm Aidil Adrianda A; Septian, Belen; M. Fauzan Ridho
The Indonesian Journal of Computer Science Vol. 14 No. 4 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i4.4954

Abstract

Corn is one of the strategic commodities in food fulfillment in Indonesia. Despite being one of the strategic commodities for food security, corn production is still far from meeting total consumption. One of the main factors for increasing yield is the availability of nutrients, especially nitrogen. This research aims to determine the optimal nitrogen percentage to maximise corn production using genetic algorithm. Simulations were conducted using the genetic algorithm method with parameters such as population size, maximum number of generations, mutation rate, as well as Bayesian approach for the crossover method and a Gaussian distribution for mutation. The results showed that the more generations used, the better the accuracy of the curve approach to the actual data, with an optimal nitrogen value of 1.506% in the 500th generation and a production yield of 227,718 bu/ac or 15.325 ton/ha.
Noise Suppression of ECG Signal Using Optimized Digital Butterworth Bandpass Filter Septian, Belen
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4312

Abstract

ECG devices have been widely utilized by medical experts for cardiac health detection. It generates an analog signal that has intrinsic characteristics represented by PQRST waves. Each wave is useful for diagnostic purposes. However, ECG signal is prone to noise, particularly EMG noise. This noise occurs as a result of muscle contraction or sudden body movement of a subject. Several studies have been proposed to suppress the EMG noise on ECG. However, the complexity of an algorithm is a challenging task to be solved. Considering this problem, this research aims to suppress EMG noise using a low-complexity algorithm. To achieve this objective, a method of Butterworth bandpass filter DF-II has been proposed. The findings demonstrate that the proposed method improves SNR and signal power by 0.498dB and 0.006dBm/Hz respectively. It also demonstrates the capability to perform efficiently on a microcontroller unit.
Co-Authors Adrianda, Aidil Ahmad Fahri Ramadhani Aidil Adrianda A Ali Zainal Abidin Fardhan Arkan I. Gusti Lanang Dwitya Putra M. Fauzan Ridho Md Misbahuddin Misbahuddin, Md. Nanda Aulia Ilmatus Sakdiyah Ridho, M. Fauzan Ridho, Muhammad Fauzan Wahyu Nabila