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All Journal SANGKEP: Jurnal Kajian Sosial Keagamaan Jusikom: Jurnal Sistem Informasi Ilmu Komputer Health Research Journal of Indonesia Jurnalistrendi: Jurnal Linguistik, Sastra dan Pendidikan
Hartini, Dina
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Decision Sciences, Operations Research & Management Dentistry Education Health Professions Languange, Linguistic, Communication & Media Medicine & Pharmacology Nursing Public Health Social Sciences

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Comparison of K-Nearest Neighbors and Convolutional Neural Network Algorithms in Potato Leaf Disease Classification Nurmayanti, Trisya; Hartini, Dina; Rohana, Tatang; Lestari, Santi Arum Puspita; Wahiddin, Deden
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 1 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i1.5337

Abstract

tatang.rohana@ubpkarawang.ac.id3, santi.arum@ubpkarawang.ac.id4, deden.wahiddin@ubpkarawang.ac.id5ABSTRACTPotato production in Central Java was recorded to have decreased by 10.77% by the Central Statistics Agency (BPS), from 278,717 tons in 2022 to 248,700 tons in 2023. This decline is due to the fact that potatoes are susceptible to diseases such as late blight and dry spot (early blight) which can significantly reduce yields. This study aims to evaluate the performance of Convolutional Neural Network (CNN) with VGG16 architecture and K-Nearest Neighbors (KNN) to find the best method for potato late blight classification. The dataset used consists of 1500 potato leaf images divided into training, validation, and testing. This research uses pre- processing including resizing, rescaling, and data augmentation. The results show that CNN with the VGG16 model is superior in classifying potato leaf diseases compared to KNN with the MobileNetV2 model. CNN produced an accuracy of 96% while KNN with the MobileNetV2 model obtained an accuracy of 93%. These results can be used as a powerful tool in supporting potato leaf disease identification. This model makes a significant contribution to the development of disease identification techniques through digital image processing.Keywords: Potato Leaf Disease, Convolutional Neural Network, VGG16, K-Nearest
ASSEMBLING THE ISLAMIC MOSAIC OF THE SASAK TRIBE THROUGH TRADITIONAL CLOTHING Hartini, Dina; Hidayati, Baiq Rosida; Rahmayani, Dwina; Nahdiah, Fadhilatul; Hariadi, Eka Putra; Saharudin, Saharudin
SANGKéP: Jurnal Kajian Sosial Keagamaan Vol. 7 No. 1 (2024): Promoting Peace and Cultural Integration in Indonesia
Publisher : UIN Mataram dan Asosiasi Sosiologi Agama Indonesia (ASAGI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20414/sangkep.v7i1.9159

Abstract

The traditional clothing of the Sasak tribe is clothing that the people of Lombok usually wear at various events such as weddings, traditional ceremonies, or welcoming guests. Men's traditional clothing is called pegon, while women's traditional clothing is called lambung. When wearing traditional Sasak clothing, there are also several accessories such as keris, slewoq, dodot, and sapuq for men and pangkak, tongkak, and bendang/slewoq for women. The traditional clothing used by the Sasak tribe in daily life cannot be separated from religion, especially Islam which is the religion of the majority of the people of the island of Lombok. The aim of this research is to find out what Islamic meanings are contained in the traditional clothing of the Sasak tribe. This research is a type of qualitative descriptive research conducted in the Central Lombok area, specifically in Bebuak Village, Kopang District. The data collection techniques used in this research were direct observation and interviews. The research results show that there are many Islamic meanings contained in the traditional clothing of the Sasak-Lombok tribe, such as monotheism, purity, gentleness, tranquility, and so on. Thus, the traditional clothing of the Sasak-Lombok tribe not only has an aesthetic function but also has a religious function.
Capaian Level Industri Rumah Tangga Pangan (IRTP) Cara Produksi Pangan yang Baik untuk Industri Rumah Tangga (CPPB-IRT) di Wilayah Kerja Dinas Kesehatan Kabupaten Barito Kuala Tahun 2023 Anam, Khairul; Mahmudah; Bahrul Ilmi, Muhammad; Setiandari LO, Elsi; Hartini, Dina
Health Research Journal of Indonesia Vol 3 No 5 (2025): Health Research Journal of Indonesia
Publisher : CV. Wadah Publikasi Cendekia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63004/hrji.v3i5.621

Abstract

Pendahuluan: Tata Cara produksi pangan yang baik (CPPB) bisa meminimalisir terjadinya dampak cemaran, menaikan kualitas pangan dan terjaminnya keamanan pangan. CPPB bermanfaat bagi perkembangan industri mikro, sedang, dan makro. Tujuan: menggambarkan capaian level industri rumah tangga pangan (IRTP) cara produksi pangan yang baik untuk industri rumah tangga (CPPB-IRT). Metode penelitian menggunakan mix metode. Pengumpulan data menggunakan wawancara mendalam (Indepth Interview) terhadap 5 orang informan kunci dan 61 orang pelaku usaha. Analisis data menggunakan analisis distribusi frekuensi dan field research. Hasil penelitian menunjukkan bahwa dari 61 pelaku usaha IRTP terdapat 17,5% parameter CPPB-IRT yang tidak sesuai pada variabel pencatatan dan dokumentasi dengan indikator tertinggi yaitu “Dokumen produksi tidak mutakhir, tidak akurat, tidak tertelusur dan tidak disimpan selama 2 (dua) kali umur simpan produk pangan yang diproduksi” dengan skor 61. Sebanyak 47 IRTP (77,05%) masuk dalam kategori capaian level IV. Faktor yang menyebabkan ketidaksesuaian serius dan kritis disebabkan oleh tenaga kerja, faktor bahan baku, faktor mesin, faktor metode, faktor Lingkungan. Dalam Pengawasan terhadap Industri Rumah Tangga Pangan ini sebaiknya pemerintah memberikan alokasi anggaran yang lebih besar serta menetapkan kebijakan dan komitmen untuk melakukan pengawasan rutin setiap bulannya agar tercipta Industri Rumah Tangga Pangan yang memenuhi standar yang telah ditetapkan. Selain itu perlu ada pemberian sanksi yang tegas bagi pelaku Industri Rumah Tangga Pangan yang melakukan pelanggaran. Kata kunci: Capaian Level, Industri Rumah Tangga, Produksi Pangan
Gugus Konsonan (Klaster) Bahasa Sasak Dialek Ngeno-Ngene di Desa Tetebatu Selatan Kabupaten Lombok Timur Hartini, Dina; Sukri, Muhammad; Hidayat, Rahmad
JURNALISTRENDI : JURNAL LINGUISTIK, SASTRA, DAN PENDIDIKAN Vol 9 No 1 (2024): Edisi April 2024
Publisher : Universitas Nahdlatul Wathan Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51673/jurnalistrendi.v9i1.2088

Abstract

Consonant groups (clusters) are consonants in a row contained in one syllable. In the Sasak language, the Ngeno-ngene dialect in South Tetebatu village, there are many words that are classified as clusters, whereas in the Sasak language, the Ngeno-ngene dialect in other areas, these words are not classified as clusters. The aims of this research are (1) to determine the forms of clusters in the Sasak language, the Ngeno-ngene dialect in Tetebatu Selatan village, (2) to determine the syllabic pattern of each word that contains clusters. Data collection in this research used listening, speaking and introspection methods. The data that has been obtained will be analyzed using the intralingual matching method, the comparison technique of differentiating and comparing the main things. The results of data analysis in this research will be presented using formal and informal methods. The results of the research show that there are several forms of clusters in the Sasak language of the Ngeno-ngene dialect in South Tetebatu village such as [tr], [kl], [tl], [mb], [br], [nd], [pl], [nj ], [ŋg], [str], [pr], [bl], [jl], [bt], [nt], [bk], [bg], [mp], [sr], [ŋk], and [jd]. The syllable pattern formed from words containing consonant clusters in the Sasak language of the Ngeno-ngene dialect in South Tetebatu village is KVK-KKVK, KKVK, KKV-KVK, KKV, KKV-KV, KKV-VK, KKV-KV-KVK , KKV-KVK-KVK, KV-KVK-KKVK, KKV-KV-V, KKKVK, KKV-KV-VK, KKV-V, VK-KKVK, KKVK-KVK, KKV-KV-KV, KKV-1/2KV and KKV-KV-1/2KV.
Co-Authors Anam, M. Khairul Bahrul Ilmi, Muhammad Hariadi, Eka Putra Hidayati, Baiq Rosida Lestari, Santi Arum Puspita Mahmudah Muhammad Sukri Nahdiah, Fadhilatul Nurmayanti, Trisya Rahmayani, Dwina Rohana, Tatang Saharudin Saharudin Setiandari LO, Elsi Wahiddin, Deden