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All Journal ELSE (Elementary School Education Journal) : Jurnal Pendidikan dan Pembelajaran Sekolah Dasar JOURNAL OF APPLIED INFORMATICS AND COMPUTING JSiI (Jurnal Sistem Informasi) Journal of Information Systems and Informatics Neo Teknika: Jurnal Ilmiah Teknologi International Journal of Advances in Data and Information Systems MEANS (Media Informasi Analisa dan Sistem) Jurnal UNITEK Journal La Multiapp Jurnal Pengabdian Masyarakat (ABDIRA) Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Jurnal Mandiri IT Jurnal Locus Penelitian dan Pengabdian Jurnal Algoritma Jurnal Masyarakat Madani Indonesia Indonesian Journal of Community Empowerment (IJCE) "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Jurnal Informatika dan Kesehatan INOVTEK Polbeng - Seri Informatika Jurnal Ilmu Komputer
Sri Mujiyono
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Sistem Pakar Diagnosa Hama dan Penyakit Tanaman Bawang Merah dan Cabai Menggunakan Metode Forwad Chaining Afif Faisal Yasin; Sri Mujiyono; Abdul Rohman
Multimatrix: Jurnal Ilmu Komputer Vol. 6 No. 1 (2024): Juli 2024
Publisher : Universitas Ngudi Waluyo

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Permasalahan terhadap virus penyakit pada tumbuhan bawang merah dan cabai dapat menyebabkan kerugian ekonomi yang signifikan bagi Pedagang sekalipun Petani. Oleh sebab itu perlu dikembangkan suatu system pakar untuk mendiagnosa virus ini dengan cepat dan akurat. Penelitian ini menggunakan metode Forward Chaining dan aturan If dan Then yang bertujuan untuk mengembangkan system pakar diagnosa penyakit pada tumbuhan tersebut. Untuk mengembangkan system pakar ini, dapat mengumpulkan berbagai data jenis hama penyakit yang biasanya menyerang bawang merah dan cabai beserta gejala – gejalanya. Hasil uji coba system ini menunjukan bahwa metode Forward Chaining sangat efektif dalam mendiagnosa penyakit tersebut. Dengan gejala memberikan gejala tertentu, system dapat dengan cepat menentukan jenis penyakit yang terjangkit. Keakuratan sistem ini memberikan harapan bagi para petani dan pedagang untuk mengatasi permasalahan gagal panen mereka yang ditimbulkan oleh serangga hama. Kata Kunci : Sistem Pakar, Forward Chaining, If Dan Then, Diagnosa, Penyakit Tanaman Bawang Merah Dan Cabai Problems with viral diseases in shallots and chili plants can cause significant economic losses for traders and even farmers. Therefore it is necessary to develop an expert system to diagnose this virus quickly and accurately. This study uses the Forward Chaining method and If and Then rules which aim to develop an expert system for diagnosing plant diseases. To develop this expert system, I collected data on various types of pests that usually attack shallots and chilies and their symptoms. The results of this system trial show that the Forward Chaining method is very effective in diagnosing the disease. By giving certain symptoms, the system can quickly determine the type of disease that is infected. The accuracy of this system gives hope to farmers and traders to overcome their crop failure problems caused by insect pests. Keywords: Expert System, Forward Chaining, IF and Then, Diagnose, Onion and chili plant diseases
Peramalan Penjualan Mitra Konsinyasi Menggunakan SARIMA Berbasis Grid Search dan Evaluasi Akurasi Muhamad Hasanudin; Sri Mujiyono
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3147

Abstract

This study aims to forecast the sales of four consignment partner products using the Seasonal Autoregressive Integrated Moving Average (SARIMA) method based on monthly historical sales data from January 2023 to August 2025. The consignment system faces a high risk of product returns due to demand uncertainty, making accurate and reliable forecasting methods essential. The novelty of this research lies in the application of automatic parameter optimization using Grid Search to reduce subjectivity in selecting SARIMA models. The results indicate that the optimized SARIMA models provide good predictive performance and satisfy residual diagnostic tests. The KSP product shows the highest accuracy with a MAPE value of 7.69%, followed by KSO at 17.28%, while MO and MSM yield MAPE values of 25.54% and 27.55%, respectively, which are still acceptable for short-term operational planning. These findings confirm that a Grid Search–based SARIMA approach can serve as a reliable basis for decision-making in inventory control and in mitigating the risks of overstock and stockout in consignment schemes.
Prediksi Hasil Panen Padi Berdasarkan Data Cuaca dan Tanah Menggunakan Metode Regresi Linear Berganda Mita Halimatus Sa'diah; Sri Mujiyono
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3306

Abstract

Rice farming plays a strategic role in Indonesia's economy and food security because rice is the main source of energy for the community. Rice yields are greatly influenced by environmental factors, particularly weather and soil conditions. This study aims to predict rice yields by utilizing machine learning technology using multiple linear regression methods. The research was conducted in West Ungaran District with independent variables in the form of weather and soil condition data and dependent variables in the form of rice harvest yields. The analysis results show that the multiple linear regression model is valid and significant, as proven by the ANOVA test with a significance value of 0.03 (< 0.05). The correlation coefficient value of 0.739 indicates a strong relationship, while the coefficient of determination (R square) value of 0.630 indicates that 63% of the variation in yield can be explained by the model. These findings show that machine learning has the potential to support decision-making in maintaining food production stability.
Co-Authors ABDUL ROHMAN Abdul Rohman Abdul Rohman Ade Pratama Ade Pratama Afif Faisal Yasin Amalia, Alifah Anton Anton Aripin, Ahmad Nurul Dewanto, Bernadus Ela Suryani Fahrizal Alfian Dante fifi maqfiroh Fiktina Vifri Ismiriyam Galih Agil Febri Hidayatullah Hani Latifah Heni Setyowati Hesti Yunitiara Rizqi Ilham, Dimas Muhammad Iwan Setiawan Wibisono Kartika Yuni Purwanti Khafid, Ahmad Noor Lisa Virdinarti Putra Mita Halimatus Sa'diah Muhamad Hasanudin Nafi, Tri Maula Novan Syaiful Nugroho, Aventura Suryo Nugroho, Ivan Pangestu, Andi Polinus Gulo Puput Amanda Rasyid Purnamasari, Yessy Sabilla Sanjaya, Ucta Pradema Suamanda Ika Novichasari Syarifudin, Nanang Irfan Wahyu Kristiningrum Widayati Widayati Yeni Fitri Afidah Zulmi Roestika Rini