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All Journal PROCEEDING IC-ITECHS 2014 Jurnal Sistem Komputer & Kecerdasan Buatan Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Digital Transformation Technology (Digitech) Amorti: Jurnal Studi Islam Interdisipliner Ahsana: Jurnal Penelitian dan Pengabdian kepada Masyarakat
saifulloh Saifulloh, saifulloh
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Nursing Public Health Social Sciences Other

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Journal : PROCEEDING IC-ITECHS 2014

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Application of FFT and KNN Methods for the Process of Identifying Sound Signals Yunitasari, Yessi; Saifulloh, Saifulloh; Harly, Daniswara Andhika Putra
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1599

Abstract

Everyone has a different kind of voice. Sound is a unique thing and has a certain range of frequencies and intensity of sound that can and cannot be heard by humans. we can detect important characteristics of the sound. The Fast Fourier Transform (FFT) algorithm is an algorithm for calculating Discrete Fourier Transform (DFT). Process of Identifying Sound Signals beginning with the sound data was preprocessed, feature extraction using FFT, classification using KNN and finding the nearest distance using the Euclidean distance method, an accuracy result of 79% of the tested data was obtained.
Mapping and Prediction Analysis of Rice Fertilizer Use in Paron District, Ngawi Regency using K-Means and Fuzzy Sugeno Methods Saifulloh, Saifulloh; Yunitasari, Yessi; Welasih, Rusti Dewi
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1600

Abstract

Clustering and prediction methods are effective tools in overcoming this problem. In this research, the K-Means method was used to map fertilizer needs based on regional characteristics, such as soil type, planting patterns and land productivity levels. This method is able to group regions that have similar characteristics, making it easier to determine optimal fertilizer allocation. Next, the Fuzzy Sugeno method is applied to predict fertilizer needs in the next planting season based on historical data and the results of the grouping that has been carried out. By combining these two methods, it is hoped that the results of this research can provide accurate recommendations for the effective and efficient use of fertilizer. Mapping and predictive analysis on the use of rice fertilizers in Paron District, Ngawi Regency in 12 villages were carried out by referring to the K-Means and Fuzzy Sugeno methods. Mapping with the K-Means Method is done by determining the centroid and clustering, while the prediction mapping using the Fuzzy Sugeno Method is done by determining the variables and fuzzy sets as well as the condition calculation rules. The results obtained are that 2 villages are in the category of low fertilizer use, 3 villages are in the category of medium fertilizer use and 7 villages are in the category of high fertilizer use. Based on the prediction calculation using the Fuzzy Sugeno Method, it was found that the level of error in the comparison of data was 5.36%, meaning that from 100% of the error rate difference, the truth value in calculating the prediction of the use of urea fertilizer using the fuzzy Sugeno method was 94.64%.
Co-Authors Aldida, Jovanza Denis Astuti, Anggun Yuli Bakir, Bakir Eka, Muhammad Rendy Harly, Daniswara Andhika Putra Hoiriyah, Hoiriyah Jamaludin, Muhammad Aizat Kartika, Betania Nita, Sekreningsih Pratiwi Susanti Razali, Mohamad Afiq bin Sulistyo, Dwimas Budi Welasih, Rusti Dewi Yessi Yunitasari