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All Journal Jurnal Mantik Journal of Intelligent Decision Support System (IDSS) Jurnal Mandiri IT Jurnal Janitra Informatika dan Sistem Informasi Brilliance: Research of Artificial Intelligence Jurnal Ekonomi, Teknologi dan Bisnis Innovative: Journal Of Social Science Research Jurnal Teknik Informatika dan Desain Komunikasi Visual
Kurniawan, Rifki Dwi
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Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Other

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Performance evaluation of single moving average and exponential smoothing in shallot production prediction Santoso, Aisyach Aminarti; Surorejo, Sarif; Kurniawan, Rifki Dwi; Gunawan, Gunawan
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5205

Abstract

Shallots are a strategic commodity that has significant health benefits, including its ability to prevent cancer. The commodity also plays an important role in the agricultural economy, especially in Indonesia, where high demand in domestic and international markets contributes greatly to farmer’s income. However, fluctuations in shallot production often lead to price instability, which has a negative impact not only on consumers but also on the sustainability of farmers' income. This research aims to develop a forecasting model that can assist in more effective planning of shallot production. To achieve this goal, the study tested and compared two forecasting methods: Single Moving Average (SMA) and Single Exponential Smoothing (SES), which are known for their ease of implementation and accuracy in predicting time series data. Using a dataset of shallot production from Brebes Regency over the period 2020-2023, the study found that Single Exponential Smoothing consistently provided more accurate results than Single Moving Average. SES performance is more responsive to recent changes in production data, which is particularly important given the rapid fluctuations that often occur in the agricultural sector. The findings suggest that the application of the SES method in shallot production forecasting can facilitate more informed decision-making in production management and distribution planning, potentially stabilizing market prices and improving farmers' economic conditions
Machine Learning Model for Human Resource Placement in Higher Education Syefudin, Syefudin; Kurniawan, Rifki Dwi
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6861

Abstract

This study presents the development and evaluation of a machine learning model designed to support human resource (HR) placement decisions in higher education institutions. Using combined personnel data from STMIK YMI Tegal and Politeknik Harber, we built a predictive model to estimate staff attendance at institutional progress reporting events, a critical indicator for performance evaluation and role suitability. The dataset comprised 137 records with six categorical predictors: Position, Homebase, Origin, Tegal_Status, Gender, and Institution. Categorical variables were encoded using label encoding, and a Random Forest classifier was trained using a stratified 75%/25% train-test split. The model achieved a held-out test accuracy of 97.14%, precision of 93.33%, recall of 100%, and F1-score of 96.55%, outperforming baseline models (Logistic Regression and Decision Tree). Five-fold cross validation confirmed robust generalization with an average accuracy of 91.22%. Feature importance analysis revealed Position as the most influential variable (76.88% importance), followed by Homebase and Origin. The results suggest that machine learning, particularly ensemble based methods, can provide reliable decision support tools for HR managers in academic settings, enabling data driven placement strategies. This research highlights the potential of predictive analytics for optimizing staff assignments and fostering institutional effectiveness. Future work should include larger datasets, additional features, and external validation to enhance model generalizability.
Implementasi Keamanan Jaringan Menggunakan Port Knocking Santoso, Nugroho Adhi; Affandi, Khaediar Bagus; Kurniawan, Rifki Dwi
Jurnal Janitra Informatika dan Sistem Informasi Vol. 2 No. 2 (2022): Oktober - Jurnal Janitra Informatika dan Sistem Informasi
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/janitra.v2i2.156

Abstract

Teknologi informasi harus diperbarui setiap tahun karena masalah keamanan data dan informasi. Keamanan informasi menjadi semakin penting seiring dengan perubahan teknologi informasi dan masih terus berubah hingga saat ini. Serangan pada server telah sering dilakukan oleh pengguna yang ceroboh. Keamanan jaringan perlu ditingkatkan untuk mengurangi penyalahgunaan jaringan hacker. Pada penelitian ini port knocking digunakan untuk melakukan penelitian untuk pembuatan jaringan komputer yang aman. Berdasarkan hasil analisis dan pengujian implementasi sistem, dapat disimpulkan bahwa sistem dapat berfungsi secara efektif dan keamanan jaringan bawaannya dapat ditingkatkan dibandingkan dengan keamanan non-jaringan. Pasang keamanan port knock pada tempatnya. Kehadiran otentikasi yang sesuai saat mengakses adalah buktinya.
Tinjauan Pustaka Sistematis: Data Mining Dalam Bidang Kesehatan Nugroho, Bangkit Indramawan; Lestari, Nindy Putri; Kurniawan, Rifki Dwi; Gunawan, Gunawan
Jurnal Ekonomi Teknologi dan Bisnis (JETBIS) Vol. 1 No. 1 (2022): Jurnal Ekonomi, Teknologi dan Bisnis
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/jetbis.v1i1.2

Abstract

Kesehatan adalah syarat utama yang dibutuhkan oleh tubuh untuk menjalani kegiatan sehari hari. Tanpa kesehatan, manusia akan mengalami penurunan fisik. Kesehatan juga merupakan suatu kondisi dimana orang merasakan keseimbangan yang unik, dipengaruhi oleh faktor keturunan, teknologi dan cara hidup sehari hari-hari seperti makan, minum, bekerja, istirahat hingga berurusan dengan kehidupan yang mendalam. Kesehatan mempunyai faktor penting seperti menjaga pola asupan makanan, diperbanyak untuk meminum air putih setiap hari, tidur yang cukup dengan minimal sehari 8 jam. Data mining adalah informasi yang menggabungkan berbagai informasi dan penanganan yang digunakan untuk menemukan contoh dan koneksi yang tersimpan dalam kumpulan informasi besar yang ada dalam kumpulan data. Data mining adalah salah satu tahap waktu yang dihabiskan untuk menemukan contoh informasi dalam kumpulan data yang sangat besar atau disebut juga Knowledge Discovery in database (KDD). Di dalam tinjauan ini menggunakan metode Systematic Literature Review (SLR) yaitu dengan tahap awal mencari dan merekap jurnal terdahulu yang sesuai dengan penelitian ini dan tahap selanjutnya dengan meneliti isi jurnal tersebut.
Tinjauan Pustaka Sistematis: Penerapan Multimedia Dalam Pengembangan Media Pembelajaran Gunawan, Gunawan; Marzuqi, Maezun Nafis; Santoso, Nugroho Adhi; Kurniawan, Rifki Dwi
Jurnal Ekonomi Teknologi dan Bisnis (JETBIS) Vol. 1 No. 1 (2022): Jurnal Ekonomi, Teknologi dan Bisnis
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/jetbis.v1i1.5

Abstract

Media adalah sesuatu yang menyalurkan pesan atau perantara pesan. Sedangkan media pembelajaran adalah perangkat yang menyampaikan pesan-pesan pembelajaran. Tujuan dari penelitian ini sendiri adalah untuk mengkaji dan membandingkan jurnal penelitian yang berbeda, apakah penerapan multimedia sebagai media pembelajaran akan membuat pembelajaran lebih efektif dan mempengaruhi hasil belajar. Metode yang saya gunakan adalah Systematic Literature Review (SLR), jurnal yang akan dianalisis adalah jurnal yang berkaitan dengan penerapan multimedia dalam pengembangan media pembelajaran. Pertama-tama, penelitian ini terlebih dahulu mengumpulkan jurnal-jurnal yang berhubungan dengan penelitian saya. Hasil akhir dari penelitian ini diperoleh bahwa penerapan multimedia dalam media pembelajaran menunjukkan dapat difungsikan dengan hasil yang efektif dan berpengaruh positif terhadap pembelajaran.
Application of computer vision techniques to detect diseases and pests of chili plants Nurokhman, Akhmad; Surorejo, Sarif; Kurniawan, Rifki Dwi; Gunawan, Gunawan
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 1 (2024): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v7i1.201

Abstract

This research aims to develop a disease and pest detection system in chili plants using computer vision techniques. In this study, deep learning methods, especially Convolutional Neural Networks (CNN), were applied to identify and classify various types of diseases and pests that often attack chili plants. The data used included images of chili leaves infected with various diseases and pests, which were then trained in CNN models to recognize certain patterns that indicate the presence of infection. The results showed that the developed system was able to detect and classify diseases and pests in chili plants with a very high degree of accuracy. The novelty of this research lies in the use of computer vision techniques combined with sophisticated deep learning algorithms to automatically detect diseases and pests, which were previously done manually by farmers or agricultural experts. These findings make an important contribution to improving efficiency and effectiveness in chili crop health management, offering innovative solutions to support agricultural sustainability through the use of advanced technology.
Application of fuzzy expert system method for early detection of dengue fever Prayoga, Alan Eka; Surorejo, Sarif; Kurniawan, Rifki Dwi; Gunawan, Gunawan
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 1 (2024): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v7i1.217

Abstract

The application of the Fuzzy Expert System method in the early detection of dengue fever offers a promising approach to improve diagnostic accuracy. This study aims to develop a system that can overcome the diversity of dengue fever symptoms and uncertainty in the diagnosis process. Using medical record data of patients who have confirmed DHF, the study designed fuzzy rules for symptom evaluation, resulting in more precise diagnostic outputs. The results indicate the system's success in identifying dengue cases with high sensitivity and good positive predictive value. These findings confirm the importance of FES technology in clinical practice, especially for controlling and preventing dengue fever in endemic areas. Continued research will test this system in a broader clinical scenario to ensure its effectiveness and practicality in diverse medical environments.
Implementation of fuzzy mamdani method in predicting cayenne chili prices in Tegal Regency Surorejo, Sarif; Mutaqin, Ahadan Fauzan; Kurniawan, Rifki Dwi; Gunawan, Gunawan
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 2 (2024): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v7i2.231

Abstract

This study investigates the application of Fuzzy Mamdani's method in predicting the price of cayenne pepper in Tegal Regency, one of the important agricultural commodities that has significant economic implications. This study aims to develop an accurate and reliable cayenne pepper price prediction model in Tegal Regency using the fuzzy Mamdani method. Research methods include collecting historical data on cayenne pepper prices, cayenne pepper production, and rainfall, as well as the implementation of the Mamdani fuzzy method consisting of fuzzification, inference, and defuzzification using Python programming language computing. The results showed that the fuzzy Mamdani method can predict the price of cayenne pepper with a good level of accuracy, with an average prediction error of 16.653285% and a prediction correctness rate of 83.346715%. This finding has implications for improving production planning capabilities and marketing strategies for cayenne pepper farmers in Tegal District, as well as contributing to the scientific literature in the application of fuzzy methods in agriculture
Penerapan Metode Rule Based System Untuk Menentukan Jenis Tanaman Pertanian Berdasarkan Ketinggian Dan Curah Hujan Supratman, Ardhi; Nugroho, Bangkit Indarmawan; Syefudin, Syefudin; Kurniawan, Rifki Dwi
Innovative: Journal Of Social Science Research Vol. 4 No. 2 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i2.10235

Abstract

Penelitian ini mengembangkan sebuah metode Rule Based System untuk menentukan jenis tanaman pertanian yang optimal berdasarkan ketinggian dan curah hujan. Dengan menggabungkan data ketinggian dan data curah hujan dari Badan Pusat Statistik (BPS) Kabupaten Tegal, sistem ini menggunakan pengetahuan ahli pertanian untuk menghasilkan rekomendasi tanaman. Implementasi dilakukan dengan menggunakan Python dan framework flask, menyajikan hasil dalam bentuk website. Evaluasi menunjukkan bahwa metode ini efektif dalam menghasilkan rekomendasi tanaman yang sesuai dengan kondisi lingkungan. Meskipun ada beberapa kasus ketidaksesuaian, hasilnya menegaskan potensi metode Rule Based System dalam meningkatkan akurasi pengambilan keputusan pertanian. Penelitian ini memberikan wawasan untuk pengembangan lebih lanjut dengan fokus pada peningkatan keakuratan dan validasi sistem yang lebih komprehensif.
Application of WASPAS method in determining the best flour for nastar making Nugroho, Bangkit Indarmawan; Dewi, Errika Mutiara; Kurniawan, Rifki Dwi; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.303

Abstract

This study explores the use of the Weighted Aggregated Sum Product Assessment (WASPAS) Method in selecting the best wheat flour for pineapple cake production. The aim of this study is to develop a more systematic and quantitative approach in assessing flour quality, provide useful guidance for pineapple cake producers and enrich the academic literature in the field of food science and food technology. This study used quantitative methodology data analysis and model validation with WASPAS, aimed at overcoming the challenge of selecting the best wheat flour for pineapple cake making. Results showed that the WASPAS method was effective in identifying the best flour, with Bungasari Hana Emas flour obtaining the highest WASPAS score of 0.952863, followed by the Falcon Hijau with a score of 0.931373. This score indicates the optimal balance between cost and quality. The study emphasizes the importance of objective decision-making tools in the food industry, suggesting that such an approach can significantly improve product quality and production efficiency.
Co-Authors Aang Alim Murtopo Adhi Santoso, Nugroho Affandi, Khaediar Bagus Arif, Zaenul Bangkit Indarmawan Nugroho Dewi, Errika Mutiara Gunawan Gunawan Karsidin, Karsidin Lestari, Nindy Putri Marzuqi, Maezun Nafis Mutaqin, Ahadan Fauzan Nugroho, Bangkit Indramawan Nurokhman, Akhmad Prayoga, Alan Eka Santoso, Aisyach Aminarti Santoso, Bayu Aji Santoso, Nugroho Adhi Sarif Surorejo Supratman, Ardhi Syefudin, Syefudin