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All Journal Counselium Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi)
Julianto, Bagas
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Social Sciences Transportation

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KEEFEKTIFAN SELF-AWARENESS TRAINING UNTUK MENINGKATKAN PENYESUAIAN DIRI PESERTA DIDIK Julianto, Bagas; Wagimin, Wagimin; Muslim, Mudaris
Consilium: Jurnal Program Studi Bimbingan dan Konseling Vol 4, No 1 (2016): Consilium: Jurnal Program Studi Bimbingan dan Konseling
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (519.894 KB)

Abstract

The purpose of this study was to determine the effectiveness of self-awareness training to improve the self-adjustment of student. This study was a quasi-experimental research (Quasi Experimental Design) to design Nonequivalent control group design that consist of the experimental group and the control group. The technique of collecting data using questionnaires. Data analysis using the Mann Whitney and Wilcoxon. The conclusion of this research was that self-awareness training was an effective way enhance the self-adjustment of student.
Implementasi Metode CNN Pada Aplikasi Android Untuk Deteksi Penyakit Pada Daun Padi Julianto, Bagas; Farida, Intan Nur; Dara, Made Ayu Dusea Widya
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 7 No. 2 (2023): PROSIDING SEMINAR NASIONAL INOVASI TEKNOLOGI TAHUN 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v7i2.3522

Abstract

Padi adalah komoditas pangan yang esensial didalam perekonomian indonesia, oleh karena itu ketersediaannya harus dipastikan untuk memenuhi kebutuhan pangan masyarakat, namun padi juga tidak luput dari serangan penyakit, adapun jenis penyakit daun padi yang diteliti: hawar daun, blast, bercak daun, hispa. Diperlukan sistem guna mengidentifikasi penyakit tersebut dengan menerapkan metode cnn, metode cnn digunakan untuk memprediksi penyakit yang menyerang daun padi dengan menggunakan 1200 citra dan rasio data training dan validate 90%:10% menerapkan parameter optimizer adam, learning rate 0,0001, jumlah epoch 100, batch size 32, dan tahapan pre-processing berupa normalisasi data dan augmentasi dan didapatkan hasil akurasi training sebesar 80% dan testing sebesar 87%.
Co-Authors Intan Nur Farida Made Ayu Dusea Widyadara - Universitas Nusantara Kediri, Made Ayu Dusea Widyadara Mudaris Muslim, Mudaris Wagimin Wagimin, Wagimin