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ALGORITMA APRIORI UNTUK MENENTUKAN PAKET PENJUALAN BARANG DI UMKM BINAAN DISPERINDAG KABUPATEN GROBOGAN Eko Supriyadi; Adri Tiyono; Agus Susilo Nugroho; Dhika Malita Puspita Arum; Achmad Rizki Ramadhani
Jurnal Informatika dan Rekayasa Elektronik Vol. 6 No. 1 (2023): JIRE April 2023
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v6i1.726

Minat beli dari masyarakat di Kab. Grobogan sangat kurang di penjualan online Usaha Mikro Kecil Menengah (UMKM). Dikarenakan penawaran yang ada di e-commerce (UMKM) tidak adanya paket diskon yang ditawarkan, Oleh karena itu pengembangan e-commerce (UMKM) sebagai wadah penjualan barang oleh masyarakat sangatlah diperlukan perubahan, perubahan yang harus dilakukan adalah menerapkan algoritma apriori yang ditanam di aplikasi e-commerce yang telah ada. Dengan menggunakan algoritma apriori, dapat menghasilkan aturan asosiasi untuk menunjukkan seberapa kuatnya pengaruh item ke item lain dan pola beli konsumen. Data yang di proses adalah data penjualan yang paling diminati dn juga yang kurang diminati masyarakat dipergunakan sebagai paket diskon penjualan. Dari hasil pengujian aplikasi tersebut dapat membantu pemilihan produk yang akan dipaketkan dengan diskon yang ditawarkan kepada masyarakat guna meningkatkan minat beli masyarakat pada UMKM di Kab Grobogan.

ALGORITMA RANDOM FOREST, DECISION TREE, DAN XGBOOST UNTUK KLASIFIKASI STUNTING PADA BALITA Dhika Malita; DHIKA MALITA PUSPITA ARUM; KARTIKA IMAM SANTOSO; ANDRI TRIYONO; EKO SUPRIYADI; AGUS SUSILO NUGROHO; Widodo, Edi
Jurnal Transformatika Vol. 23 No. 1 (2025): July 2025
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v23i1.12202

At the age of toddlers, children need special attention because their brains develop around 80%. Stunting is a form of long-term nutritional deficiency that occurs during the growth and development of children, which are marked with height that is not appropriate or less compared to children their age based on the standard WHO. This condition can adversely affect the cognitive development and health of children. Identifying toddlers who are at risk of experiencing stunting at an early stage is very important to reduce the adverse effects that can affect their quality of life in the future. Traditional methods are less effective in predicting stunting because they often ignore the complex factors that affect the nutritional status of toddlers. This study aims to classify stunting toddlers using Random Forest, Decision Tree, and Extreme Gradient Boost (XGBOOST) algorithms. The results obtained showed that the accuracy of the Random Forest algorithm received the highest accuracy of 99.72 %, Extreme Gradient Boost (XGBOOST) at 99.58 %, and Decision Tree received 98 87 %accuracy.

Peringkasan Dokumen Teks Bilingual Sebagai Reduksi Fitur Untuk Klasifikasi Menggunakan Algoritma K-NN Rahmawan Bagus Trianto; Agus Susilo Nugroho
LogicLink Vol. 1 No. 1, June 2024
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v1i1.7801

Summarizing text is a step to extract the essence of a text document with no more than half. Summarizing text has an important role in extracting the core information from a document in a more concise form. Summarizing text documents can be used as feature reduction in classifying text documents because it can reduce features that are considered irrelevant. Text documents are summarized using the Term Frequency-Inverse Document Frequency (TF-IDF) method, then classified using the K-Nearest Neighbor (K-NN) algorithm. One of the disadvantages of the K-NN algorithm is that it is not optimal in classification if the k value is not appropriate, as well as the selection of an inappropriate distance calculation method. By testing various k values and using the Euclidean Distance distance measurement method, you can increase the accuracy of text document classification. Text document summarization using the proposed TF-IDF method is proven to increase when classification is carried out with K-NN. From the research results, it was found that the classification accuracy at the compression rate increased by 50% with a k value of 6 to 8 of 95.33%. This shows that text document summarization as feature reduction has a positive role in the classification process using the K-NN algorithm.

PENGGUNAAN METODE REGRESI LINIER UNTUK ESTIMASI ANGKA PERCERAIAN : STUDI KASUS PENGADILAN AGAMA KABUPATEN GROBOGAN Alfianaa Khanifiyah; Agus Susilo Nugroho; Andri Tiyono
Julia: Jurnal Ilmu Komputer An Nuur Vol 5 No 1 (2025): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v5i1.1

Data mining is the process of analyzing large datasets to discover hidden patterns, trends, and valuable information. This study utilizes data mining to address a social issue, specifically estimating divorce rates in the Religious Court of Grobogan Regency. The method used is multiple linear regression, with the dependent variable being the number of divorces and independent variables including 'cerai talak' (divorce initiated by the husband), 'cerai gugat' (divorce initiated by the wife), and 'dispensasi kawin' (marriage dispensation). The objective of this research is to test and develop a data mining method to estimate divorce rates, thereby aiding the Religious Court of Grobogan Regency in formulating more effective policies, based on divorce data from 2023-2024. The research process includes data collection, pre-processing, algorithm implementation, and result evaluation. The analysis shows that the multiple linear regression model provides reasonably accurate estimates, with a Root Mean Square Error (RMSE) of 6.505 and a Relative Root Squared Error (RRSE) of 0.070. Further analysis reveals that 'cerai talak,' 'cerai gugat,' and 'dispensasi kawin' significantly affect divorce rates, with 'cerai gugat' being the most dominant factor. These findings provide a solid foundation for developing strategic policies to handle divorce cases in Grobogan Regency. To improve model accuracy, data enrichment and additional variables are needed. Collaboration between academics and the Religious Court of Grobogan Regency is also crucial to ensure the successful implementation of this research’s findings.

STRATEGIC PLANNING OF MONTHLY DONATION PAYMENT INFORMATION SYSTEM AT SMK AT-THOAT TOROH Agus Susilo Nugroho; Eko Supriyadi
Julia: Jurnal Ilmu Komputer An Nuur Vol 1 No 01 (2021): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v1i01.12

The development of a school, has an impact on the development of various services in the school. If school doesn’t improve the services, schools can lose competition, especially for private schools. The same thing happened at SMK At-Thoat Toroh. This Vocational High School, located in Grobogan Regency, Central Java, experiences significant development every year. One of the indicators is the increasing number of new students enrolling to the school. Even though the number of new students is increasing, At-Thoat Toroh Vocational School must still be able to serve the needs of all its students well. One form of this service is the payment of monthly donations. So far, students who will pay monthly contributions have to come to the teacher's office to meet the administration department. This often creates a crowd at the teacher's office door. Apart from being uncomfortable, it's certainly not a good thing in the midst of the current Covid-19 outbreak. In addition, the recording of monthly contributions by the administrative division is still done manually. This often causes disorder and confusion in recording student monthly contributions. Even though this record is very sensitive, because it relates to school finances. To overcome this problem, it is necessary to have a strategic planning of a monthly donation payment information system. This strategic planning uses the waterfall method and SWOT analysis. It aims to facilitate the analysis and process of making a monthly donation payment information system. The result of this research is the formulation of a monthly donation payment information system business strategy.

PREDIKSI TINGKAT KELULUSAN MAHASISWA S1 UNIVERSITAS AN NUUR DENGAN METODE DECISION TREE C4.5 Umar Haji Mussa’id; Agus Susilo Nugroho; Rahmawan Bagus Trianto
Julia: Jurnal Ilmu Komputer An Nuur Vol 4 No 1 (2024): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v4i1.18

One of the private universities in Purwodadi is An Nuur Purwodadi University. Many students have graduated from An Nuur Purwodadi University, but there are some students who did not graduate on time. This poses a problem and raises a significant question as to why these students did not graduate on time. A decision tree is a suitable data mining method for this research because it has the advantage of identifying and summarizing patterns in the data. The Decision Tree algorithm has an accuracy of 96.25%. The recall values for each class are 97.37% for the "Late" class and 95.00% for the "On-Time" class. Meanwhile, the precision values for each class are 94.87% for the "Late" class and 97.44% for the "On-Time" class

IMPLEMENTASI ALGORITMA APRIORI UNTUK MENCARI POLA TRANSAKSI PENJUALAN PADA TOKO PERTANIAN TOKO BIDSALTANI Muhamad Nuryahya; Andri Triyono; Agus Susilo Nugroho
Julia: Jurnal Ilmu Komputer An Nuur Vol 4 No 1 (2024): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v4i1.20

Progress in the industrial sector is currently growing rapidly, especially in medium and upper-class businesses, especially in agricultural shop businesses. Agricultural shops are one of the medium-sized businesses where competition is quite tight, this can be seen from the high consumer demand for fertilizer and agricultural equipment.With the high demand of consumers for agricultural needs as well as intense competition, agricultural shop companies must further improve their business performance in order to be able to face the problems that occur.Bidsal Tani is one of the many agricultural shops in Purwodadi District that sells agricultural necessities, such as chemical fertilizer, compost, plant seeds and all other agricultural necessities, it can be seen that to make a profit as expected.The a priori algorithm is a market basket analysis algorithm used to produce association rules. Association rules can be used to find relationships or cause and effect. The results of the research are that the products frequently purchased by consumers are PHONSKA, NPA, ZA, FASTAC, KOGE, UREA, GANDASIL, FLORAN, SP36, TSP, WUXAL, BAYFOLAN, BLOPATEK, KCL, HYDRASIL AND DECIS products.

Sistem Informasi Pembuatan Aplikasi Berbasis Web Pada Konveksi ‘Sania Komveksi’ Erika Dwi Saputra; Muhammad Muzammil; Rheimanda Devin Emmanuel; Agus Susilo Nugroho; Eko Supriyadi
Julia: Jurnal Ilmu Komputer An Nuur Vol 5 No 1 (2025): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v5i1.21

Perkembangan teknologi informasi yang pesat telah mempengaruhi berbagai sektor bisnis, termasuk industri konveksi. Sistem informasi berbasis web kini menjadi solusi efektif untuk meningkatkan efisiensi operasional dan manajemen data. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sebuah aplikasi berbasis web pada konveksi ‘Sania Konveksi’ yang dapat membantu dalam pengelolaan data produksi, pemesanan, inventaris, serta pelaporan secara lebih terstruktur dan real-time. Aplikasi ini dibangun dengan menggunakan metode pengembangan perangkat lunak Waterfall, dimulai dari tahap analisis kebutuhan, desain sistem, implementasi, sampai dengan pengujian. Hasil penelitian ini adalah sebuah aplikasi berbasis web yang mampu mengintegrasikan berbagai proses bisnis pada konveksi, memudahkan pihak manajemen dalam memonitor kinerja operasional, serta meningkatkan efisiensi dalam pengelolaan data dan proses produksi. Berdasarkan hasil pengujian, sistem ini terbukti dapat memberikan kemudahan dan efisiensi dalam pengelolaan operasional konveksi ‘Sania Konveksi’

PREDIKSI LUAS PANEN DI KECAMATAN PURWOADADI MENGGUNAKAN ALGORITMA REGRESI LINEAR BERGANDA Muhammad Akbar Mustofa; Andri Triyono; Agus Susilo Nugroho
Julia: Jurnal Ilmu Komputer An Nuur Vol 5 No 1 (2025): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v5i1.23

Agriculture, particularly rice cultivation, is highly vulnerable to climate change because it depends on water cycles and weather conditions to maintain productivity. Climate change affects crop growth, development, and yields, as agricultural activities are heavily dependent on weather and climate. This study utilizes data mining to introduce a new breakthrough in addressing rice farming issues in Grobogan Regency, Purwodadi District. The method used is multiple linear regression, with the dependent variable being harvested area and the independent variables including plxanted area and rainfall. The objective of this research is to test and develop data mining methods to predict yield levels, thereby assisting local governments in decision-making during crop failures, based on agricultural data from 20192023. The research process involves data collection, preprocessing, algorithm implementation, and result evaluation. The analysis shows that the multiple linear regression model provides reasonably accurate predictions, with a Root Mean Square Error (RMSE) value of 209.042 and a Relative Root Squared Error (RRSE) of 0.111. Furthermore, the analysis reveals that planted area significantly influence the harvested area. These findings offer insights for local governments as policymakers in providing aid during crop failures.

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