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All Journal Perfecting a Video Game with Game Metrics Jurnal EECCIS InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) Jurnal INFOTEL
Erni Yudaningtyas
Brawijaya University
Computer Science & IT Electrical & Electronics Engineering Engineering

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Nonlinearity compensation of low-frequency loudspeaker response using internal model controller Erni Yudaningtyas; Achsanul Khabib; Waru Djuriatno; Dionysius J. D. H. Santjojo; Adharul Muttaqin; Ponco Siwindarto; Zakiyah Amalia
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.11761

Abstract

This paper presents the nonlinearity compensation of low-frequency loudspeaker response. The loudspeaker is dedicated to measuring the response of Electret Condenser Microphone which operated in the arterial pulse region. The nonlinearity of loudspeaker has several problems which cause the nonlinearity behaviour consists of the back electromagnetic field, spring, mass of cone and inductance. Nonlinearity compensation is done using the Internal Model Controller with voltage feedback linearization. Several signal tests consist of step, impulse and sine wave signal are examined on different frequencies to validate the effectiveness of the design. The result showed that the Internal Mode Controller can achieve the high-speed response with a small error value.
Pengaruh Penggunaan Synonym Recognition dan Spelling Correction pada Hasil Aplikasi Penilaian Esai dengan Metode Longest Common Subsequence dan Cosine Similarity Mohammad Nur Cholis; Erni Yudaningtyas; Muhammad Aswin
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 3, No 2 (2019): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (295.081 KB) | DOI: 10.30743/infotekjar.v3i2.1061

Abstract

aplikasi penilaian esai adalah harus menilai kemiripan makna dari jawaban yan diketik oleh peserta ujian dengan kunci jawaban yang digunakan sebagai patokan kebenaran jawaban. Dimana jawaban esai adalah data bahasa alami manusia yang bisa memiliki sinonim kata dan ada kemungkinan kesalahan input yang disebabkan karena kesalahan pengetikan (kesalahan ejaan). Untuk itu perlu ada sebuah penelitian yang dapat mengukur seberapa berpengaruhnya penggunan synonim recognition dan spelling correction pada hasil aplikasi penilaian esai. Pada penelitian ini data yang digunakan untuk melakukan pengujian adalah data ujian pada mata pelajaran bahasa indonesia, seni budaya dan IPA dengan jumlah soal masing-masing ujian adalah 5 soal yang masing-masing ujian tersebut diikuti oleh 24 pelajar. Sehingga dari setiap ujian akan terdapat sebanyak 120 jawaban. Hasil pengujian menunjukkan bahwa penggunaan synonym recognition dan spelling correction pada hasil aplikasi penilaian esai dapat meningkatkan akurasi dan memperkecil nilai root mean square error (rmse).
Klasifikasi Citra Warna Daun Padi Menggunakan Metode Histogram of S-RGB dan Fuzzy Logic Berbasis Android Raimundus Sedo; Panca Mudjirahardjo; Erni Yudaningtyas
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 3, No 2 (2019): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (461.578 KB) | DOI: 10.30743/infotekjar.v3i2.1060

Abstract

 The level of greenish leaves of rice plants is one indicator to analyze the nutrient needs of the rice plant nitrogen required. In the process, one recommended way to determine nitrogen needs for the rice plant is the use Leaf Color Chart (LCC). Given the need for efficiency of time and energy, and to avoid the perception of the color differences are observed, it is important to do the development of a system to facilitate the farmers in determining the nitrogen requirements for rice.This research aims to develop an Android-based system to determine nitrogen needs for the rice crop through image processing concept. The method used is of s-RGB Histograms and Fuzzy Logic. Method of s-RGB Histogram function to extract the characteristic color of rice leaves, while Fuzzy Logic is used to classify images based on 4 levels of rice leaf color on the LCC also to determine the dose of nitrogen necessary for the needs of rice plants.Tests carried out using Samsung's smartphone brands with a capacity of 8 MP camera. The test results and evaluation system using the Confusion Matrix for Multiple Classes showed that the accuracy of the system provide the requested information is considered good enough, that is 88.19%. The success of the system to find the information back to the recall level of 88.25%. Degree of proximity between the predicted value of the system to the actual value of 88.75%, and the level of specificity obtained at 62.12%. While the system achieved computational time average of 10:14 seconds. Keywords- Histogram of s-RGB, Fuzzy Logic, Leaf Color Chart, Confusion Matrix for Multiple Classes
Identifikasi Takaran Pupuk Nitrogen Berdasarkan Tingkat Kehijauan Daun Tanaman Padi Menggunakan Metode Histogram of s-RGB dan Fuzzy Logic Raimundus Sedo; Panca Mudjirahardjo; Erni Yudaningtyas
Jurnal EECCIS Vol 13, No 1 (2019)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak – Analisis warna daun padi merupakan salah satu cara untuk mengidenfikasi kandungan unsur hara yang dibutuhkan sebagai dasar rekomendasi takaran pupuk untuk tanaman padi. Apabila kelebihan nitrogen, maka tanaman padi mudah terserang hama penyakit selain mencemari air tanah. Sebaliknya, jika kekurangan nitrogen, maka pertumbuhannya menjadi tidak normal. Tujuan penelitian ini adalah merancang sistem untuk mengidentifikasi takaran pupuk nitrogen berdasarkan tingkat kehijauan daun tanaman padi melalui konsep pengolahan citra menggunakan metode Histogram of s-RGB dan Fuzzy Logic berbasis android. Pada peneitian ini, Bagan Warna Daun (BWD) merupakan konsep dasar dalam proses pengembangan dan perancangan sistem ini. Sistem dirancang berdasarkan 4 skala warna sesuai level warna BWD agar dapat mengidentifikasi citra daun padi sebagai dasar rekomendasi takaran pupuk nitrogen.Berdasarkan hasil pengujian, diketahui bahwa rata-rata jarak terdekat (euclidean distance) nilai RGB citra daun padi yang dihasilkan sistem terhadap nilai RGB citra level warna BWD sebesar 14,28 pada smartphone 8 MP, sedangkan smartphone 5 MP sebesar 15,44. Hasil evaluasi Confusion Matrix for Multiple Classes menunjukkan bahwa ketepatan sistem memberikan informasi yang diminta pada smartphone 8 MP dinilai lebih baik, yaitu 93,03% dibanding pada smartphone 5 MP sebesar 87,18%. Keberhasilan sistem untuk menemukan informasi kembali pada smartphone 8 MP dinilai lebih unggul dengan tingkat recall sebesar 93,42%, dibanding sistem pada smartphone 5 MP sebesar 86,08%. Tingkat kedekatan antara nilai prediksi sistem dengan nilai aktual pada smartphone 8 MP sebesar 91,03%, sedangkan pada smartphone 5 MP mencapai 88,31%, namun keduanya memiliki specificity yang sama sebesar 66,67%. Kata Kunci— Histogram of s-RGB, Fuzzy Logic, Euclidean Distance, Confusion Matrix for Multiple Classes
Investigation of Human Emotion Pattern Based on EEG Signal Using Wavelet Families and Correlation Feature Selection Dwi Utari Surya; Ponco Siwindarto; Erni Yudaningtyas
JURNAL INFOTEL Vol 11 No 2 (2019): May 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i2.431

Abstract

Emotions is one of the advantages given by God to human beings compared to other living creatures. Emotions have an important role in human life. Many studies have been conducted to recognize human emotions using physiological measurements, one of which is Electroencephalograph (EEG). However, the previous researches have not discussed the types of wavelet families that have the best performance and canals that are optimal in the introduction of human emotions. In this paper, the power features of several types of wavelet families, namely Daubechies, symlets, and coiflets with the Correlation Feature Selection (CFS) method to select the best features of alpha, beta, gamma and theta frequencies. According to the results, coiflet is a method of the wavelet family that has the best accuracy value in emotional recognition. The use of the CFS feature selection can improve the accuracy of the results from 81% to 93%, and the five most dominant channels in the power features of alpha and gamma band on T8, T7, C5, CP5, and TP7. Hence, it can be concluded that the temporal of the left brain is more dominant in recognition of human emotions.
Co-Authors Achsanul Khabib Adharul Muttaqin Dionysius J. D. H. Santjojo Dwi Utari Surya Mohammad Nur Cholis Muhammad Aswin Panca Mudjirahardjo Ponco Siwindarto Raimundus Sedo Waru Djuriatno Zakiyah Amalia