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All Journal Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Jurnal Pengukuran Psikologi dan Pendidikan Indonesia (JP3I) Al-Jabar : Jurnal Pendidikan Matematika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL PENDIDIKAN TAMBUSAI Algoritme Jurnal Mahasiswa Teknik Informatika Informatics and Enginering Dedication Jurnal Sistem Cerdas dan Rekayasa Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Yohannes Yohannes
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Social Sciences Other

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Implementasi Algoritma K-Nearest Neighbor untuk Klasifikasi Cuaca Dandy, Dandy; Udjulawa, Daniel; Yohannes, Yohannes
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 4 No 1 (2023): Oktober 2023 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v4i1.4932

Abstract

Weather is a brief natural event concerning the atmospheric conditions that take place on Earth which are determined by pressure, wind speed, temperature, and air phenomena. This study classifies 3 weather classes, namely sunny, cloudy, and rainy using the K-Nearest Neighbor algorithm as a weather classification algorithm with K value parameters of 3, 5, 7, and 9. Weather dataset 96.453 data to be examined is data taken from the Kaggle website. The dataset is divided into training data and test data with a ratio of 80:20. The implementation of the K-Nearest Neighbor algorithm produces a confusion matrix and classification report where in the confusion matrix, the largest number of correctly predicted data is at the value K = 9, namely 13.132 correctly predicted data with the largest number of correctly predicted data in the cloudy class, namely 10.865 data. As for the classification report, the highest accuracy value for both the cloudy, rainy, and sunny weather classes is at K = 9, which is 68.073%, and the highest precision, recall, and f1-score values are found in the cloudy class at K = 9, respectively contributed 72.095%, 89.288%, and 79.775%.
Pelatihan Membangun Server DNS Lokal di SMK Negeri 1 Palembang Arman, Molavi; Yohannes, Yohannes; Al Rivan, Muhammad Ezar
FORDICATE Vol 2 No 1 (2022): November 2022
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v2i1.3393

Abstract

Pengabdian masyarakat yang dilakukan di SMK Negeri 1 Palembang yaitu berupa pelatihan untuk membangun Server DNS. Pelatihan ini diikuti oleh siswa SMK sehingga siswa memiliki keterampilan dan pengetahuan terkait dengan server DNS. Pelatihan ini diawali dengan melakukan instalasi sistem operasi Linux Debian. Pelatihan ini dilakukan dengan cara praktikum dan tanya jawab. Dari pelatihan ini didapatkan pengetahuan bagaimana melakukan instalasi Linux Debian kemudian dapat membangun Server DNS.
Transfer Learning dengan MobileNetV2 untuk Klasifikasi Motif Jumputan Palembang Sahpira, Mulia; Yohannes, Yohannes
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 6 No 1 (2025): Oktober 2025 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v6i1.10998

Abstract

Palembang jumputan fabric is one of Indonesia's cultural heritages that is unique in its motifs and manufacturing techniques. However, the lack of public understanding of the meaning of motifs and competition with other traditional fabrics are challenges in its preservation. This research aims to develop a classification model of Palembang jumputan fabric motifs using the Convolutional Neural Network method with MobileNetV2 architecture and transfer learning approach. The dataset used consists of 800 images of four types of motifs, namely Bintik Tujuh, Pola, Tabur, and Terong. The data is divided into 80% training, 10% validation, and 10% testing. The model was trained using four types of optimisers, namely AdamW, Adagrad, Nadam, and SGD, with training parameters of 100 epochs, batch size 32, and learning rate 0.001. The test results showed that AdamW gave the highest accuracy of 97%, followed by Nadam 96%, Adagrad 95%, and SGD 90%. The model recognised the motifs well, especially the Bintik Tujuh and Tabur motifs which achieved 100% accuracy. With these results, artificial intelligence can be utilised to support the preservation of Palembang jumputan fabrics through motif recognition technology.
Penyelundupan Pakaian Bekas Import Ditinjau dari Perspektif Hukum Ekonomi Annisa, Adde; Ariani, Nisha; Yohannes, Yohannes; Martin, Rizky; Jordan, Stevianus; Bumi, Harinu; Mustaqim, Mustaqim
Jurnal Pendidikan Tambusai Vol. 8 No. 1 (2024): April 2024
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v8i1.13312

Abstract

Penelitian ini membahas fenomena penyelundupan pakaian bekas impor di Indonesia dalam konteks hukum ekonomi. Meskipun pemerintah telah mengeluarkan peraturan yang melarang impor pakaian bekas, praktik penyelundupan tetap terjadi. Penelitian ini menganalisis dampak praktik ini pada perekonomian, dengan fokus pada kerugian pangsa pasar produk lokal, potensi penurunan kinerja industri tekstil, dan kerugian pendapatan negara karena impor ilegal. Melalui pendekatan hukum ekonomi dan normatif, penelitian ini mencermati regulasi perdagangan internasional yang berlaku, khususnya Undang-Undang Nomor 7 Tahun 2014 tentang Perdagangan. Upaya pemerintah untuk mengatasi permasalahan ini, melibatkan e-commerce dan socio-commerce untuk menghentikan penjualan pakaian bekas impor, memberikan sanksi hukuman kepada importir ilegal, dan memberikan dukungan kepada UMKM yang terkena dampak. Kesimpulannya, penelitian ini memberikan pemahaman mendalam terhadap tantangan hukum ekonomi dalam menghadapi fenomena penyelundupan pakaian bekas impor. Implikasi praktis dan konseptual dari praktik ini diuraikan, dengan harapan memberikan kontribusi pada pengembangan kebijakan yang lebih efektif dalam mengatasi penyelundupan pakaian bekas impor di Indonesia.
The Effect of Problem-Based Learning Model on Mathematical Critical Thinking Skills of Junior High School Students: A Meta-Analysis Study Yohannes, Yohannes; Juandi, Dadang; Tamur, Maximus
JP3I (Jurnal Pengukuran Psikologi dan Pendidikan Indonesia) Vol. 10 No. 2 (2021): JP3I
Publisher : FAKULTAS PSIKOLOGI UIN SYARIF HIDAYATULLAH JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jp3i.v10i2.17893

Abstract

Numerous similar studies have been conducted to evaluate the effect of problem-based learning models (PBL) on students' mathematical critical thinking skills. However, the findings from these studies are inconsistent. Highlighting this gap, this study comprehensively evaluates the effectiveness of implementing the PBL model on junior high school students’ critical thinking skills. This meta-analysis study was conducted by analyzing a sample of 15 journal papers that met the feasibility. Empirical data collection uses several journal search engines, and the instruments used are coding categories. Data analysis to obtain effect size value was performed with Comprehensive Meta-Analysis (CMA) software, and the estimation method used a random-effect model. Overall, the results showed that the effect size of PBL model implementation on mathematical critical thinking skills of junior high school students is 0.970, which means the PBL model's implementation had a high effect on students' critical thinking skills. Besides, the effect size of implementing the PBL model on junior high school students' critical thinking skills did not differ based on differences in class, year of study, and sample size. However, there were significant differences in effect sizes between study groups based on treatment duration. Thus, PBL will achieve a higher level of effectiveness, taking into account the treatment duration.
Co-Authors Ade Hendri Pandrean Annisa, Adde Ariani, Nisha Aryo Sasmita Azarya, Philips Denny Bumi, Harinu Dadang Juandi Dandy, Dandy Daniel Udjulawa Devella, Siska Dody, Muhammad Famerdi, Farhan Agung Febbiola Febbiola Feristyani, Indah Fransiska Kurniawati Gerry Jeven Timoti Hafiz Irsyad Hartati, Ery Indah Feristyani Johannes Petrus Jordan, Stevianus Karina Yolanda Leonardo Leonardo M Ezar Al Rivan Marcella, Dewi Martin, Rizky Meiriyama, Meiriyama Molavi Arman Muhammad Farid Athar Mustaqim Mustaqim, Mustaqim Novan Wijaya Nur Arifin, Nur Pandi Pandi Pandi Pandi, Pandi Pandrean, Ade Hendri Philips Denny Azarya Prabowo, Adrianus Prasthio, Rial Putra, Lipi Amanda RR. Ella Evrita Hestiandari Sahpira, Mulia Sari, Yulya Puspita Setiawan, Jerry Suparman Suparman Surya Dita Prasetya Tamur, Maximus William Hadisaputra Yoannita Yoannita Yoannita Yoannita, Yoannita Yulya Puspita Sari