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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Malikussaleh Journal of Mathematics Learning (MJML) Jurnal Pengabdian Masyarakat Nusantara
Eviyanti, Cut Yuniza
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Humanities Computer Science & IT Education Engineering Mathematics Social Sciences

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The Implementation of Group Investigation Learning Model Through Domino Mathematics Media on the Rank Number and Root Form Materials Eviyanti, Cut Yuniza; Rista, Lia; Hadijah, Siti; Andriani, A
Malikussaleh Journal of Mathematics Learning (MJML) Vol 4, No 1 (2021): May
Publisher : Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/mjml.v4i1.3118

Abstract

This study aims to find out the results of students' learning through the implementation of a group investigation learning model through mathematical domino media better than the implementation of a conventional learning model on the rank number and root form materials. The research was a quasi-experiment with the design of a randomized control group pretest-posttest. The population of this research is the entire class IX SMP Negeri 1 Lhokseumawe consisting of 9 classes. The research sample was determined by a randomized technique that made 2 classes namely experiment class (IXA) and control class (IXB). The results of the student posttest data test show that the data is distributed normally and homogeneously, so it can be analyzed with one-side t-test statistics at a significant α= 0.05. Based on the results of data processing against the posttest students obtained sig scores. (2-tailed) posttest data is 0.001 which means less than α= 0.05, this means H0 is rejected, so it can be concluded that the learning results of students taught by the group investigation learning model through domino mathematics media are better than conventional learning models on the rank number and root form materials in grade IX of SMP Negeri 1 Lhokseumawe.
PELATIHAN INSTALASI LISTRIK UNTUK MENINGKATKAN KETERAMPILAN DALAM UPAYA PENINGKATAN PENDAPATAN WIRAUSAHA BAGI PEMUDA PUTUS SEKOLAH DI DESA KRUENG SEUNONG Wahyuni, Sri; Febriansyah, Sutan; Nasruddin, Nasruddin; Eviyanti, Cut Yuniza; Rista, Lia
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 2 No. 1 (2022): Februari - Juli 2022
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v2i1.492

Abstract

The failure of formal education is not the end of everything. Young people who have failed in the formal education can still hone their skills and knowledge in non formal education through trainings to increase their capacity. STIE and STKIP Bumi Persada Lhokseumawe lecturers are designed and conducted electrical installation training to improve their abilities and skills in Krueng Seunong Village. The purpose of this activity is to enable young out of school to be able to independently install and repair electrical installations, thereby opening up entrepreneurshipl opportunities and at least having an income for themselves. This activity is carried out in three approaches, that is: briefing material, training and demonstration, and testing. The results obtained are the participants success in using and flowing electric current to the media which is marked by light up in each installed circuit.
Comparative Study of VGG16 and MobileNet Architectures for Rice Leaf Disease Classification Using CNN Ilham Sahputra; Ananda Faridatul Ulfa; Bella Amanda Putri; Cut Yuniza Eviyanti
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 1 (2025): Issues July 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i1.15458

Abstract

Rice is a primary commodity in Indonesia's agricultural sector, playing a vital role in national food security. However, rice productivity is frequently disrupted by leaf diseases such as Bacterial Leaf Blight, Brown Spot, Leaf Blast, and Narrow Brown Spot. This study aims to develop an automated rice leaf disease identification model using the Convolutional Neural Network (CNN) method with a transfer learning approach. Two CNN architectures, VGG16 and MobileNet, were trained using a dataset of 2,190 rice leaf images divided into five classes. The research process included data collection, preprocessing, model training, and performance evaluation using a confusion matrix. The results show that the VGG16 model achieved an accuracy of 98%, while MobileNet reached 95% accuracy. Thus, this method can serve as a modern solution for identifying rice plant diseases, supporting early detection efforts and enhancing agricultural productivity.
Co-Authors Ananda Faridatul Ulfa Andriani, A Bella Amanda Putri Febriansyah, Sutan Ilham Sahputra Nasruddin Nasruddin Rista, Lia Siti Hadijah Sri Wahyuni