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All Journal Jurnal Agroteknos International Journal of Engineering, Science and Information Technology Jurnal Malikussaleh Mengabdi
NELI SUSANTI, NELI
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ANALISIS VARIABILITAS KULTIVAR JAGUNG PULUT (Zea mays Ceritina Kulesh) LOKAL SULAWESI TENGGARA SAFUAN, LA ODE; BOER, DIRVAMENA; WIJAYANTO, TEGUH; SUSANTI, NELI
Jurnal Agroteknos Vol 4, No 2 (2014)
Publisher : Jurnal Agroteknos

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (851.771 KB)

Abstract

The experiment was conducted in the Rahandouna village, Poasia, Kendari Southeast Sulawesi, from August to November 2013.  The purpose of this study was to determine the estimate of heritability between characters of thirteen local waxy corn cultivars of Southeast Sulawesi. This study was prepared using a randomized block design (RBD), with 3 replicates. Total waxy corn cultivars studied was 13 species, so that there were 39 plots. Each plot consisted of a single cultivar. Observed variables were plant height (cm), stem diameter (cm), leaf area (cm2), number of leaves (strands), ear length (cm), cob diameter (cm), number of rows per ear, weight of 100 seeds (g), ear weight. The results of this study showed that there was narrow variability on all local waxy corn characters observed. Keywords: Local waxy corn, characters, cultivars, Southeast Sulawesi, variability
Peningkatan Literasi Digital Guru untuk Membangun Materi Ajar Dalam Menghadapi Program Kelas Digital pada MIN 4 Kota Lhokseumawe Bustami, Bustami; Fikry, Muhammad; Ismail, Ismail; Yani, Muhammad; Maharani, Silfa; Susanti, Neli; Iskandar, Fahra Azzahra
Jurnal Malikussaleh Mengabdi Vol 3, No 1 (2024): Jurnal Malikussaleh Mengabdi, April 2024
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v2i2.13878

Abstract

Madrasah Ibtidaiyah Negeri (MIN) 4 di Kota Lhokseumawe menghadapi tantangan signifikan dalam mengadaptasi Program Kelas Digital dalam konteks pembelajaran. Dalam upaya mendukung dan memperkuat inisiatif ini, pengabdian masyarakat telah dilakukan untuk meningkatkan literasi digital para guru. Pengabdian ini bertujuan untuk mengimplementasikan serangkaian pelatihan literasi digital yang disesuaikan dengan kebutuhan guru. Melalui pendekatan kolaboratif, komunitas akademik, praktisi industri teknologi, dan pemerintah lokal terlibat dalam menyusun program pelatihan yang holistik. Metode pelaksanaan terdiri dari workshop, lokakarya, dan sesi pelatihan interaktif yang fokus pada pemahaman teknologi pendidikan, pemanfaatan aplikasi pembelajaran online, dan strategi pengembangan materi ajar yang responsif terhadap kebutuhan Program Kelas Digital. Hasilnya menunjukkan peningkatan yang signifikan dalam pemahaman dan keterampilan teknologi guru-guru MIN 4. Diharapkan bahwa upaya pengabdian masyarakat ini tidak hanya akan meningkatkan kualitas pembelajaran, tetapi juga memperkuat kapasitas guru dalam memanfaatkan teknologi untuk menghasilkan materi ajar yang inovatif dan relevan dengan kebutuhan siswa di era digital ini.
Expert System for Diagnosing Dengue Fever with Comparison of Naïve Bayes and Dempster Shafer Methods Susanti, Neli; Nurdin, Nurdin; Afrillia, Yesy
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.691

Abstract

An expert system for diagnosing dengue fever (DF) using a comparison of the Naive Bayes and Dempster Shafer methods aims to provide a solution to assist medical personnel in diagnosing this disease. Dengue fever is a disease caused by the dengue virus infection through the bite of Aedes mosquitoes. It has symptoms similar to other diseases and requires rapid and accurate diagnosis. The Naive Bayes and Dempster Shafer methods were chosen because both have different approaches to handling uncertainty and imprecise information. The Naive Bayes method is a probability-based classification that assumes independence between features. Meanwhile, Dempster Shafer is an approach to handling uncertainty. Therefore, comparing Naive Bayes and Dempster Shafer allows for classification with structured and fairly straightforward data, offering accuracy and flexibility in dealing with uncertainty. Applying this expert system with these methods can help in the faster and more accurate diagnosis of DF and provide better recommendations in situations where the available data is incomplete or ambiguous. From the test data calculations, the two methods show that the Naive Bayes method has a higher percentage value of 93%, while Dempster Shafer has 86%.
Co-Authors Bustami Bustami DIRVAMENA BOER, DIRVAMENA Iskandar, Fahra Azzahra Ismail Ismail La Ode Safuan Maharani, Silfa Muhammad Fikry Muhammad Yani, Muhammad Nurdin Nurdin Teguh Wijayanto Yesy Afrillia