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All Journal ILKOM Jurnal Ilmiah Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Tecnoscienza
Marniyati H. Botutihe
Universitas Pohuwato
Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Mathematics Neuroscience Transportation Other

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Neural Network Method Based on Particle Swarm Optimization for Predicting Satisfaction of Recipients of Internet Data Support from the Ministry of Education and Culture Annahl Riadi; Irvan Muzakkir; Marniyati H. Botutihe
ILKOM Jurnal Ilmiah Vol 14, No 1 (2022)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

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Abstract

The free quota assistance program for students and lecturers is an assistance program carried out by the ministry of education and culture, this program has been implemented since the impact of the covid-19 pandemic in all regions of Indonesia, this assistance is expected to help students and lecturers in carrying out online learning caused by the pandemic covid-19, the purpose of this study is to measure the level of visitor satisfaction through predictions of satisfaction so that it can help the government in advancing the world of education., data processing is carried out using the rapid miner application and using the neural network method with particle swarm optimization, from the results of data processing the results obtained are Values the accuracy for the neural network algorithm model is 42.44% and the accuracy value for the PSO-based neural network algorithm model is 91.86%.
Perbandingan Metode Forecasting K-NN, NN dan SVM Untuk Peramalan Jumlah Produksi Coconut Oil Ivo Colanus Rally Drajana; Marniyati H. Botutihe
JURNAL TECNOSCIENZA Vol. 7 No. 2 (2023): TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/tecnoscienza.v7i2.919

Abstract

Abstrak Tanaman pohon kelapa memiliki banyak bagian yang dimanfaatkan, sehingga tumbuhan ini dianggap tumbuhan serbaguna. Minyak kelapa (coconut oil) dihasilkan oleh buah pohon kelapa salah satunya adalah buah kelapa yang diolah menjadi minyak kelapa (coconut oil). Peramalan sangat diperlukan untuk meramalkan jumlah produksi minyak kelapa (coconut oil) pada sebuah perusahaan untuk mencapai target produksi. Penelitian ini memiliki tujuan untuk membandingkan metode forecasting untuk mendaptkan model terbaik. Dari hasil eksperimen menggunakan data sales order (SO) di peroleh model terbaik untuk peramlan menunjukkan bahwa model yang terbaik dihasilkan oleh algoritma Support Vector Machine (SVM) dilihat dari hasil RMSE terkecil yaitu 0,172 jika di bandingkan dengan model K-Nearest Neighbor (K-NN) dan model Neural Network (NN).
Metode Case Based Reasoning untuk Sistem Pakar Diagnosa Penyakit Akibat Serangan Hama pada Tanaman Padi Marniyati H. Botutihe; Bahrin Bahrin; Rahmat Arbabu
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 6 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i6.10207

Abstract

Abstrak - Tanaman padi merupakan salah satu jenis pangan utama di dunia setelah gandum dan jagung, dengan peran signifikan dalam pemenuhan kebutuhan karbohidrat hampir setengah populasi global. Namun, berbagai hama seperti serangga, hewan, dan mikroorganisme dapat merusak pertumbuhan dan produksi tanaman padi. Penelitian ini bertujuan untuk merancang sistem pakar yang menggunakan metode Case Based Reasoning (CBR) untuk mendiagnosis penyakit akibat serangan hama pada tanaman padi, Tujuan utamanya adalah Memperoleh hasil penerapan metode Case Based Reasoning pada sistem pakar diagnosa penyakit serangan hama pada  tanaman padi. Metode CBR memungkinkan diagnosis dengan membandingkan gejala baru terhadap kasus sebelumnya yang terdokumentasi, sehingga memanfaatkan pengalaman untuk menyelesaikan masalah baru. Hasil implementasi sistem ini menunjukkan bahwa sistem berfungsi sesuai harapan melalui pengujian White Box dengan Cyclomatic Complexity sebesar 9, serta pengujian Black Box. Dengan demikian, sistem pakar tersebut layak digunakan untuk membantu petani dalam mengidentifikasi penyakit pada tanaman padi dan mengambil tindakan yang tepat.Kata kunci : Padi; hama; Sistem Pakar; Case Based Reasoning; CBR; Abstract - Rice is one of the world’s main food crops after wheat and corn, playing a significant role in fulfilling the carbohydrate needs of nearly half of the global population. However, various pests such as insects, animals, and microorganisms can damage the growth and production of rice plants. This study aims to design an expert system that uses the Case-Based Reasoning (CBR) method to diagnose diseases caused by pest attacks on rice plants. The main objective is to obtain the results of applying the Case-Based Reasoning method in an expert system for diagnosing pest-attack diseases in rice plants. The CBR method enables diagnosis by comparing new symptoms with previously documented cases, thus utilizing past experiences to solve new problems. The results of implementing this system indicate that it functions as expected through White Box testing with a Cyclomatic Complexity of 9, as well as Black Box testing. Therefore, the expert system is considered feasible to assist farmers in identifying diseases in rice plants and taking appropriate action.Keywords: Rice; Pests; Expert Systems; Case Based Reasoning; CBR;
Co-Authors Annahl Riadi Bahrin Bahrin Irvan Muzakkir Ivo Colanus Rally Drajana Rahmat Arbabu