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All Journal Aisyah Journal of Informatics and Electrical Engineering Jurnal Aisyah : Jurnal Ilmu Kesehatan Jurnal Al-Kifayah: Ilmu Tarbiyah dan Keguruan
Ningsiah
Universitas Aisyah Pringsewu
Chemistry Computer Science & IT Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Nursing Public Health Veterinary Other

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PENERAPAN SMART FARMING UNTUK BUDIDAYA CABAI DALAM GREENHOUSE Hafsah Mukaromah; Anas Ikhsanudin; Febri Arianto; Ningsiah; Sri Lestari
Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E) Vol. 5 No. 2 (2023): Aisyah Journal Of Informatics and Electrical Engineering
Publisher : Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30604/jti.v5i2.227

Abstract

Budidaya tanaman cabai saat ini menjadi salah satu budidaya favorit dan sangat diminati oleh petani. Permintaan yang besar dan secara terus menerus menjadikan harga cabai masih menempati urutan teratas produk pertanian hortikultura yang sering mengalami fluktuasi harga. Terdapat beberapa jenis cabai yang dibudidayakan di Indonesia diantaranya cabai rawit, cabai merah keriting, dan cabai besar. Penelitian ini dilaksanakan melalui 2 (dua) tahapan agar diperoleh hasil yang baik. Adapun 2 (dua) tahapan tersebut yaitu Sistem Smart Greenhouse dan Sistem Fertigasi. Berdasarkan pengamatan kami, sistem fertigasi telah berfungsi dengan baik dan tanaman mendapatkan nutrisi dan air yang cukup. Berdasarkan pengukuran yang kami lakukan dengan menggunakan pressure gauge pada setiap ujung barisan tanaman, didapatkan informasi bahwa pada setiap ujung baris tanaman mempunyai tekana air yang sama besar, sehingga dapat dipastikan setiap tanaman mendapat nutrisi dan air dengan volume yang sama. Berdasarkan penelitian kami, dengan menggunakan sistem fertigasi yang terintegrasi dapat meningkatkan kualitas pertumbuhan dan perkembangan tanaman. Sistem fertigasi yang telah diimplementasikan juga semakin memudahkan petani dalam mengontrol sistem penyiraman dan pemberian nutrisi tanaman karena sdh dilengkapi dengan modul IOT berupa Haiwell IOT cloud HMI yang dapat dikontrol secara remote baik menggunakan jaringan Wifi maupun internet.
Penerapan Model Pemilihan Kartu (Card Short) Dalam Pembelajaran Fiqih Untuk Meningkatkan Keaktifan Dan Prestasi Belajar Siswa Siswa Kelas V C MIN 2 Indragiri Hulu Ningsiah, Ningsiah
Jurnal Al-Kifayah: Ilmu Tarbiyah dan Keguruan Vol. 1 No. 2 (2022): Jurnal Al-Kifayah: Ilmu Tarbiyah dan Keguruan
Publisher : Sekolah Tinggi Agama Islam (STAI) Al- Kifayah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (637.279 KB) | DOI: 10.53398/ja.v1i2.198

Abstract

This study aims to increase student achievement in class V C MIN 2 INHU in the subject of Jurisprudence through a card sort model, and this research uses CAR research methods or class action research (classroom action research). with the learning model type sorting cards (card sort) managed to improve student achievement. In cycle 1 students of class V C obtained an average score of 71.72 with the lowest score being 60 and the highest score being 95. There were also 17 students who had not yet reached the KKM with a classical completeness score of only 41%. In cycle II the average score was 79.82, the lowest score was 70 and the highest score was 100. Meanwhile, there were only 4 students who had not reached the KKM with classical completeness of 88%. succeeded in increasing the activity and achievement of student learning. This can be seen in the development of each cycle that is held. Namely in cycle 1 only 41% and increased in cycle II 86%. Based on the average value per cycle which is in the very good category
COMPARATIVE ANALYSIS OF LUNG DISEASES FROM CHEST X-RAY IMAGES USING CONVOLUTIONAL NEURAL NETWORK AND SUPPORT VECTOR MACHINE Ningsiah, Ningsiah; Irianto, Suhendro Yusuf
Jurnal Aisyah : Jurnal Ilmu Kesehatan Vol 9, No 1 (2024): March 2024
Publisher : Universitas Aisyah Pringsewu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30604/jika.v9i1.2736

Abstract

The lungs are an important human organ in the human body, especially in the respiratory system. Another function of the lungs is to maintain stable body temperature, protect the body from dangerous substances, the nose is the sense of smell, but sometimes the lungs will experience conditions where they do not function normally. Chest x-ray images are the most well-known clinical method for the diagnosis of lung diseases. However, diagnosing lung diseases from chest x-ray images is a challenging task even for radiologists. This research proposes a system that can be used for comparative analysis of lung disease by applying the Convolutional Neural Network and Support Vector Machine methods. CNN is a method in the field of object recognition that has special layers, namely convolution layers and pooling layers which enable a good feature learning process. SVM is a comparative analysis method that relies on results from statistical learning theory to guarantee generalization performance. In this research there are 2 main processes, namely preprocessing and comparative analysis. There are 3 classes of disease for comparative analysis, namely Covid-19 disease, Tuberculosis disease, Pneumonia disease, and Normal disease. In this study, a comparison was also carried out between the classification carried out by CNN and SVM. The research data uses a chest X-ray image dataset. This research produces the best algorithm that is implemented to classify lung diseases from chest x-ray images.
Co-Authors Anas Ikhsanudin Febri Arianto Mukaromah, Hafsah Sri Lestari Y. Suhendro