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. Darniati
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A Transformative Approach to Innovative Learning Media at State Elementary School 095224 Taratak Nagodang Darniati, Darniati; Hasibuan, Asnita
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.v8i1.13688

Abstract

Upaya pengembangan masyarakat berbasis pelatihan guru SD Negeri 095224 TARATAK NAGODANG dalam penciptaan media pembelajaran baru telah membuahkan hasil yang revolusioner. Melalui sistem yang mapan yang melibatkan penilaian kebutuhan, pelatihan interaktif, dan dukungan berkelanjutan, para pendidik telah meningkatkan keterampilan mereka secara signifikan. Dampak manfaatnya terlihat jelas dalam peningkatan integrasi teknologi, peningkatan keterlibatan siswa, dan pembentukan komunitas belajar kolaboratif. Keberhasilan proyek ini berlanjut melampaui sesi pelatihan langsung, dengan langkah-langkah dukungan pasca-pelatihan yang menjamin keberlanjutan upaya tersebut. Suasana kolaboratif di antara para pendidik mendukung pertukaran pengetahuan yang berkelanjutan, berkontribusi pada budaya pertumbuhan yang berkelanjutan. Proyek ini tidak hanya meningkatkan praktik pengajaran tetapi juga menggarisbawahi peran penting pendidik dalam menghasilkan pengalaman pendidikan yang dinamis dan menarik. Sebagai sumber inspirasi bagi proyek pengembangan masyarakat di masa depan, proyek ini menggambarkan potensi transformatif dari investasi pengembangan profesional bagi para pendidik. Pembelajaran yang diperoleh dan perbaikan positif yang terlihat dalam lanskap pendidikan di SD Negeri 095224 TARATAK NAGODANG menetapkan landasan bagi pertumbuhan dan keunggulan berkelanjutan, dengan menekankan peran penting guru dalam menciptakan masa depan pendidikan.
ANALISIS KINERJA WEBSITE PT.BRINGIN GIGANTARA MENGGUNAKAN SEMRUSH TOOL METODE ANALYSIS Bunganan , Rey Richard; Muhsal, Muhammad Ilham; Darniati, Darniati; Haruna, Suardi B.
Jurnal Review Pendidikan dan Pengajaran Vol. 7 No. 3 (2024): Vol. 7 No. 3 (2024): Volume 7 No 3 Tahun 2024 (Special Issue)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jrpp.v7i3.32047

Abstract

Website PT.BRINGIN GIGANTARA adalah website yang digunakan untuk keperluan nasabah dalam hal membutuhkan pengelolaan keuangan, jasa service, dan pengisian uang mesin ATM BRI. Dalam website ini terdapat media dan informasi untuk mengetahui profil,kontak,kegiatan,dan tentang perusahaan ini. Untuk menganalisis suatu website yang dilakukan adalah mengetahui kinerjanya,menampilkan informasi yang valid,menampilkan status keamanan websitenya,dan mengetahui jumlah byte data yang keluar pada saat diakses. karena itu kami akan analisis website ini dengan menggunakan alat atau tools, kami pakai SEMRUSH tool dan google transparency report untuk mengetahui status keamanan website ini, SEMRUSH tool ini alat analisis website otomatis dan mengetahui hasil dari analisis berupa score kinerja untuk website, mendeteksi jumlah-jumlah error atau masalah,dan memberikan saran atau Solusi perbaikan untuk website. Dari hasil analisis dengan menggunakan SEMRUSH tool diperoleh nilai rata-rata kinerjanya lumayan bagus sebesar 96% status Kesehatan website adalah 73% angka ini berada dilevel sedang berarti ada bug terdeteksi dan perlu diperbaiki agar kinerjanya bisa optimal 100%.
The Effect Of Burning Time On The Amount Of Bacteria Staphylococcus Aureus Contamination Of Grilled Meatballs Sold In Darusssalam, Banda Aceh Novita, Andi; Ismail, Ismail; Khoirunnisa, Fathonah; Ferasyi, Teuku Reza; Darniati, Darniati; Zainuddin, Zainuddin
The International Journal of Tropical Veterinary and Biomedical Research Vol 8, No 2 (2023): Vol. 8 (2) November 2023
Publisher : The Faculty of Veterinary Medicine of Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21157/ijtvbr.v8i2.34328

Abstract

This study aims to determine the effect of heating time in the combustion process on Staphylococcus aureus contamination in grilled meatballs. A total of 9 samples of meatballs obtained from 3 sellers of grilled meatballs were divided into 3 treatments, namely burning at temperatures ranging from 56C-59C for 1 minute, 3 minutes, and 5 minutes, with 3 repetitions. Determination of the number of microbes was carried out using the Total Plate Count (TPC) method. The research data were analyzed using a two-way ANOVA analysis of variance followed by Duncan's test. The results showed that the duration of burning affected the amount of Staphylococcus aureus contamination in grilled meatballs. The best combustion was shown at 5 minutes, with a microbial count of 3.6 101 CUF/g. The results of the analysis of variance (ANOVA) showed that there was a significant difference (P0.05) in the average value of Staphylococcus aureus microbial contamination in grilled meatballs given treatment. Based on the calculation results, it can be concluded that 5 minutes of burning time is the most effective for decontaminating the amount of Staphylococcus aureus microbial contamination in grilled meatballs.
klasifikasi tanaman herbal lokal berdasarkan citra daun dengan menggunakan algoritma resnet152v2 ., arneta; Darniati; Chyquitha Danuputri
Ainet : Jurnal Informatika Vol. 7 No. 2 (2025): September (2025)
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/gstka990

Abstract

Abstrak Penelitian ini bertujuan untuk mengklasifikasikan tanaman herbal lokal berdasarkan citra daun dengan memanfaatkan algoritma Convolutional Neural Network (CNN) menggunakan arsitektur ResNet152V2. Identifikasi tanaman herbal secara manual masih menjadi tantangan bagi masyarakat karena banyak jenis tanaman memiliki kemiripan morfologi daun, sehingga berpotensi menimbulkan kesalahan dalam pemanfaatannya sebagai bahan obat tradisional. Oleh karena itu, penerapan teknologi pengolahan citra digital berbasis deep learning menjadi solusi yang relevan untuk meningkatkan akurasi identifikasi tanaman herbal. Dataset yang digunakan dalam penelitian ini terdiri dari 4.400 citra daun yang dikumpulkan secara langsung di lingkungan alami, mencakup 11 kelas yang terdiri atas tanaman herbal, non-herbal, dan kelas tidak teridentifikasi. Dataset melalui tahap pra-pemrosesan yang meliputi padding, resizing, normalisasi, serta augmentasi data untuk meningkatkan variasi dan kualitas data. Model ResNet152V2 dilatih menggunakan optimizer Adam dengan learning rate sebesar 0,0001 dan fungsi loss Categorical Crossentropy, serta menerapkan callback EarlyStopping untuk mencegah overfitting.Hasil evaluasi menunjukkan bahwa model mampu mencapai akurasi validasi sebesar 99,77% dan akurasi pengujian sebesar 99,11%. Nilai precision, recall, dan F1-score pada hampir seluruh kelas berada di atas 0,95, yang menandakan performa klasifikasi yang sangat baik. Dengan demikian, penelitian ini membuktikan bahwa ResNet152V2 efektif digunakan dalam sistem identifikasi tanaman herbal berbasis citra daun dan berpotensi dikembangkan lebih lanjut sebagai sistem pendukung pelestarian tanaman obat lokal.
PERBANDINGAN CNN DAN YOLO PADA SISTEM PENGENALAN WAJAH BERBASIS PRESENSI Nurfadillah; Ida; Darniati; Yusliana Bakti, Rizki; Wahyuni, Titin; Faisal, Muhammad
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i1.532

Abstract

Face recognition based on image data has been widely applied in automated attendance systems; however, it still faces challenges related to accuracy and efficiency under varying lighting conditions and facial pose variations. This study aims to compare the performance of Convolutional Neural Network (CNN) and You Only Look Once (YOLO) methods for face detection and recognition in a deep learning–based attendance system. The dataset consists of facial images collected from students in a limited campus environment with several variations in viewpoint and illumination. The research stages include image preprocessing, training of CNN and YOLO models, and performance evaluation using accuracy, precision, recall, and computation time metrics. The experimental results indicate that YOLO outperforms CNN in terms of detection speed and performance stability, while CNN demonstrates competitive classification performance on limited datasets. This study provides empirical insights into the characteristics of both methods in attendance system scenarios and can serve as a reference for selecting appropriate models for real-world implementation. The main limitations of this study are the dataset size and the restricted data acquisition scope.
KLASIFIKASI TANAMAN OBAT TRADISIONAL BERBASIS CITRA BUAH DAN DAUN Kusumawardani, Nurul; Danuputri, Chyquitha; Darniati; Faisal, Muhammad; A.M Hayat, Muhyiddin; S. Kuba, Muhammad Syafaat; Anggreani, Desi
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i1.534

Abstract

Indonesia is a megabiodiversity country with extensive use of traditional medicinal plants; however, plant identification in natural environments remains largely manual and error-prone. Recent advances in deep learning, particularly Vision Transformer (ViT), provide a promising solution by effectively capturing global spatial features for image classification. This study applies a ViT-Base/16 model to automatically classify fruit and leaf images of Indonesian medicinal plants. The dataset comprises 1,000 field-collected images from Galung Village, West Sulawesi, covering 20 classes (10 medicinal and 10 non-medicinal plants). The model was fine-tuned using the AdamW optimizer with a learning rate of 2×10⁻⁵ and trained for 30 epochs with cosine annealing. The proposed approach achieved high performance, with 99.33% accuracy, 99.41% precision, 99.33% recall, and a 99.33% F1-score, while binary classification between medicinal and non-medicinal plants reached 100% accuracy. The system was deployed as a Flask-based web application, demonstrating reliable functionality and practical response times. Overall, the results confirm the effectiveness of Vision Transformer for medicinal plant classification under natural conditions and highlight its potential to support digital documentation, education, and the preservation of local ethnobotanical knowledge.
Strategi Pemasaran Dengan Metode Potongan Harga Dalam Meningkatkan Minat Belanja Rezky, Annisyah; Satriani, Satriani; Wanini, Wanini; Diva, Farah; Darniati, Darniati; Arifuddin, Arifuddin
Jurnal Ilmiah Multidisiplin Amsir Vol. 2 No. 1 (2023): Desember
Publisher : AhInstitute of Research and Community Service (LP2M) Institute of Social Sciences and Business Andi Sapada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62861/jimat.v2i1.935

Abstract

This study aims to determine the marketing strategy of the Alfamidi Ahmad Yani Store in implementing discount or discount methods to increase consumer shopping interest in fulfilling their wants and needs. The technique used is qualitative by conducting direct research in the field to observe the phenomena at Alfamidi Ahmad Yani to maximize the data obtained in marketing products that are given discounts and overcome problems or obstacles that arise during the research. Using this discount method positively impacts gaining profit in-store revenue and can retain consumers. With this method, shops can also prevent losses due to non-sales of a product; for this reason, Alfamidi Ahmad Yani needs to maintain this strategy and develop price discounts for each product.
Co-Authors . Darmawi . Darmawi . Darmawi . Fakhrurrazi . Muthmainnah . Syafruddin ., arneta Abdil lah Imron Nasution Abdul Harris Abdul Wahid Abdullah Hamzah Agusni Yahya Agustin Indrawati AK, M Daud Akbar, Muh Andi Novita Andi Novita Arifuddin Arifuddin Arman Sayuti Ayuti, Siti Rani Azhari Azhari Azmansyah Azmansyah Baharuddin, Suardi Hi Bakti, Rizki Yusliana Balqis Alrasyid Suyoto Basri Gani Bunganan , Rey Richard Chyquitha Danuputri Cut Nila Thasmi Cut Soraya Danuputri, Chyquitha Dara Hayati Rapi Darmawi Darmawi Desi Anggreani Diva, Farah Dwi Rosa Selfiana Erina Erina Erina Erina Erina Erina Erina Erina Erina Erina Erina Erina Erina Erina Erina Erina Fadlah, Iga fadli amri Fahkrurrazi Fahkrurrazi Faisal Jamin Faisal Jamin Faisal Jamin Faisal Jamin Fakhrurrazi Fakhrurrazi Fakhrurrazi Fakhrurrazi Florentina Magdalena Girsang Ginta Riady Ginta Riady Hamdani Budiman Haruna, Suardi B. Hasibuan, Asnita Herrialfian, Herrialfian Iccha Elvioleta Ida Ida Mulyadi, Ida Isa, M Ismail Ismail Khoirunnisa, Fathonah Kholifah, Ida Kusumawardani, Nurul Latifa Suryandari LIA PERMATA SARI M Daud AK M Nur Salim M. Nur Salim Mahdi Abrar Mahdi Abrar Mahdi Abrar Maryulia Dewi Maryulia Dewi Maryulia Dewi Mirna Safrani Fauzi Muhammad Amin muhammad aroza Muhammad Faisal Muhammad Faisal Muhammad Hambal Muhammad Syafaat S. Kuba Muhsal, Muhammad Ilham Muhyiddin A.M Hayat Musdalifa Thamrin Muttaqien Bakri Muttaqien Muttaqien Nazaruddin Nazaruddin nisma hayani Nugraha, Ronaldi Fajar Nur Ramadhan, Nur Nurahmad Nurfadillah NURLIANA NURLIANA Nuzul Asmilia Olivia salsa dilla putri Pratiwi, Zahwa Amelia Rahmadhini, Vivi Rahmadia Fitri Rastina Rastina Razali Daud Resti Reimena Rezi Maghfira Rezky, Annisyah Rima Rizky Amiruddin Rinidar Rinidar Risal riza maulita Robbi Ghani Roslizawaty Roslizawaty Safika S, Safika Samsuria, Samsuria Sarea, Muh Syahrul Sari, Wahyu Eka Satriani Satriani Silvia P.N Keliat Surachmi Setiyaningsih T. Armansyah T. Armanyah TR Teuku R. Ferasyi Teuku Reza Ferasyi Titin Wahyuni Tongku N Siregar Ummu Balqis wahyu eka sari Wanini, Wanini Windian Tajuk Masmah Bengi Yudha Fahrimal Zainuddin, Zainuddin Zakiah Heryawati Manaf Zakiyah Heryawati Manaf Zinatul Hayati Zuhrawati NA