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All Journal Jurnal Media Infotama Jurnal Sains dan Teknologi REKAYASA JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Media Computer Science Jurnal Komputer Indonesia
Yupianti, Yupianti
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Physics Social Sciences

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Application Of K-Means Method In Grouping Horticultural Commodity Production Results In The Department Of Food Crops Horticulture And Plantations Of Bengkulu Province Silola, Alun; Yupianti, Yupianti; Sudarsono, Aji
Jurnal Media Computer Science Vol 4 No 2 (2025): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v4i2.8423

Abstract

The Department of Agriculture, Food Crops, Horticulture and Plantations of Bengkulu Province is a government agency whose task is to collect data on horticultural commodities in the Bengkulu Province. In the Department of Agriculture, Food Crops, Horticulture and Plantations of Bengkulu Province, there is no specific system used to group data on horticultural commodity production results, so it is difficult to obtain information on horticultural commodities that fall into high, medium, and low production levels in Bengkulu Province. The application of the k-means method in grouping horticultural commodity production results at the Department of Food Crops, Horticulture and Plantations of Bengkulu Province can help the department obtain information on the results of grouping horticultural commodity data in Bengkulu Province, and can help determine planning programs and provide counseling to farmers in horticultural commodities, especially those in the low production group to increase their production results. Based on the data used in 2023 with 3 categories of horticultural commodities, the results of the grouping in the vegetable category cluster C1 were 3 commodities, cluster C2 was 9 commodities, cluster C3 was 13 commodities, in the fruit category cluster C1 was 4 commodities, cluster C2 was 7 commodities, cluster C3 was 20 commodities, in the medicinal plants and spices category cluster C1 was 2 commodities, cluster C2 was 1 commodity, cluster C3 was 13 commodities. In the vegetable horticultural commodity category that includes high production results are Large Chili (Group), Cabbage, Eggplant, the fruit horticultural commodity category that includes high production results is Durian, Orange (Group), Siamese Orange/Tangerine, Banana, and the vegetable horticultural commodity category that includes low production results is Ginger, Rhizome (Group).
Implementation Of Apriori Algorithm To Analyze Sales Data Of Goods At Izza Aquarium Shop Febianda, Kanita; Asnawati, Asnawati; Yupianti, Yupianti
Jurnal Media Computer Science Vol 4 No 2 (2025): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v4i2.8569

Abstract

Toko Izza Aquarium is a business that sells animal feed and aquarium equipment. This research analyzes the sales data of Toko Izza Aquarium by applying the Apriori algorithm with the aim of providing data-based strategic recommendations to increase sales and customer satisfaction. This research is also expected to contribute in the field of sales data analysis in small and medium enterprises. The application of data mining to analyze the sales data of the Izza Aquarium Store is to provide information. The results of the analysis of Monthly sales data for the Izza Aquarium Store. Can be used as a parameter for inventory management at the Izza Aquarium Store and also provides information about the best-selling items at the Izza Aquarium Store. In analyzing sales data, the Apriori method is applied, so that the final result stage of the analysis passes the Apriori Method stage by meeting the Minimum Support and Minimum Confidence that has been determined. Based on the results of tests carried out on a data sample of 20 transactions in August 2024, the sales products that are most in demand by the public meet Minimum Support of 15% and Confidence 90% It turns out that Misster Puss Salmon and Chat Choice Green.
PENGOLAHAN CITRA DIGITAL UNTUK IDENTIFIKASI OBJEK MENGGUNAKAN METODE HIERARCHICAL AGGLOMERATIVE CLUSTERING Jumadi, Juju; Yupianti, Yupianti; Sartika, Devi
JST (Jurnal Sains dan Teknologi) Vol. 10 No. 2 (2021)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (456.193 KB) | DOI: 10.23887/jstundiksha.v10i2.33636

Abstract

Identifikasi objek (object recognition) merupakan suatu bidang keillmuan dari komputer vision yang menggambarkan suatu objek yang didasarkan pada sifat utama dari objek tersebut. Identifikasi objek pada citra digital membutuhkan teknik dan metode yang mampu untuk mengekstraksi dan mengidentifikasi fitur-fitur yang terdapat pada citra digital, dimana komponen utamanya adalah warna sebagai dasar dari representasi objek pada citra digital. salah satu metode yang mampu menerapkan pengelompokan warna – warna objek pada citra digital sehingga dapat menjadi fitur utama dari objek pada citra digital adalah Hierarchical Agglomerative Clustering. Analisa dilakukan secara bertahap yaitu analisis sistem dan analisis algoritma agglomerative clustering. Proses analisa kemudian dilanjutkan dengan tahap perancangan yang mana dimulai dengan perancangan use case diagram dan perancangan flowchart. Akurasi dari algoritma Hierarchical Agglomerative Clustering cukup baik khususnya pada objek yang memiliki warna khusus atau warna yang telah menjadi ciri dari objek tersebut namun dapat menghasilkan pengenalan yang buruk jika objek yang berbeda memiliki warna dominan yang sama
Co-Authors Abimanyu, Iqbal Kresna Agustin, Decki Aji Sudarsono Alinse , Rizka Tri Angga Dwi Supardi Putra, Edo Aprilinda, Tara Asnawati Asnawati Beti, Ila Yati Dimas Aulia Trianggana Edy Hermansyah Febianda, Kanita Feri Hari Utami, Feri Hari Galih Putra Kusuma Indra Kanedi Juju Jumadi Julita , Rina Jutriansyah, Dodon Khairil Khairil Kurnianto, Ridho Rahman Lena Elfianty Lianda, Deri Liza Yulianti Meta, Rio Sefrin Alfa Monika, Lola Eris Muhammad Ikbal Muhammad Soleh Nurul Husna Prasetyo R, Eko Putra, Nanda Pratama Putra, Repal Kesatria Putra, Riski Adi Rianda, Reszha S Siswanto Sari, Heni Kusnita Sartika , Devi Sartika, Devi Septiyadi, Muhammad Harri Silola, Alun Supardi , Reno Suriatno, Tommy Ulandari, Puspa Zulfiandry, Ricky