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All Journal Techno.Com: Jurnal Teknologi Informasi Speed - Sentra Penelitian Engineering dan Edukasi Jurnal Teknologi Informasi dan Ilmu Komputer CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOIV : International Journal on Informatics Visualization Jurnal Informatika Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial IJCIT (Indonesian Journal on Computer and Information Technology) Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Paradigma Jurnal Pilar Nusa Mandiri JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Riset Informatika EVOLUSI : Jurnal Sains dan Manajemen JSAI (Journal Scientific and Applied Informatics) Indonesian Journal of Business Intelligence (IJUBI) Jurnal Infortech Abditeknika - Jurnal Pengabdian Kepada Masyarakat Innovative: Journal Of Social Science Research Ladang Artikel Ilmu Komputer Journal of Accounting Information System Indonesian Community Service Journal of Computer Science (IndoComs)
Rizal Amegia Saputra
Universitas Bina Sarana Informatika
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

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Implementasi Model Hybrid Regresi Linear–Moving Average dalam Sistem Prediksi Penjualan Rokok Berbasis Data Historis Amegia Saputra, Rizal; Wajhillah, Rusda; Farlina, Yusti; Ardiansyah, Angga; Masripah, Siti
JAIS - Journal of Accounting Information System Vol. 5 No. 02 (2025): Desember
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jais.v5i02.11305

Abstract

Peramalan penjualan merupakan proses penting dalam manajemen persediaan dan perencanaan produksi, khususnya pada industri rokok yang memiliki pola permintaan bervariasi antar jenis produk. Untuk meningkatkan akurasi prediksi pada data historis penjualan yang relatif pendek, penelitian ini bertujuan mengembangkan dan mengevaluasi model hybrid yang mengombinasikan Regresi Linear dan Moving Average dengan bobot dinamis. Metode penelitian mencakup pra-pemrosesan data, eksplorasi statistik, pembentukan model LR dan MA, serta pengujian model hybrid dengan variasi bobot α pada rentang 0.1-0.5. Evaluasi performa dilakukan menggunakan MAE, RMSE, dan MAPE. Hasil penelitian menunjukkan bahwa model hybrid memberikan kinerja paling optimal dibandingkan model LR dan MA tunggal. Nilai rata-rata MAPE hybrid sebesar 2.17%, lebih rendah dibandingkan MA 2.31% dan LR 3.79%. Model hybrid mampu meningkatkan akurasi sebesar 5.95% dibandingkan MA dan 42.58% dibandingkan LR. Selain itu, sebagian besar produk memiliki bobot optimum pada α = 0.1-0.2, ini menunjukan dominannya pola jangka pendek, sementara produk dengan fluktuasi lebih tinggi menunjukkan α yang lebih besar. Dengan demikian, model hybrid LR-MA efektif digunakan untuk peramalan penjualan berbasis data historis. 
Sentiment Analysis on Import Tariff Policy and Gold Price Increase with TF-IDF siti masripah; Rizal Amegia Saputra
Jurnal Riset Informatika Vol. 7 No. 3 (2025): Juni 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v7i3.361

Abstract

Changes in global economic policy, such as Donald Trump's import tariff policy in 2025, have generated various public responses recorded through social media such as Twitter. Analysis of this public opinion is important to understand public perception of the dynamics of gold prices as a strategic commodity. This study aims to analyze public sentiment towards the issue of tariff policies and gold using TF-IDF feature extraction. To overcome class imbalance in tweet data, the Synthetic Minority Over-sampling Technique (SMOTE) technique was used. The dataset was obtained from Twitter with the keywords "trump", "tariffs", and "gold", then preprocessing and sentiment labeling (positive, negative, neutral) were carried out. The results of the analysis showed that 88.8% of tweets contained positive sentiment, 6.9% negative, and 4.1% neutral. The model evaluation produced an accuracy of 81.23%, with the highest precision in the positive class (0.81) and a recall of 1.00. These findings indicate that the issue of tariff policies is associated optimistically by the public because it is considered beneficial to gold prices.
DEVELOPMENT OF MANUFACTURING INVENTORY MANAGEMENT SYSTEM USING MATERIAL REQUIREMENT PLANNING METHOD Rahmawati, Ami; Saputra, Rizal Amegia; Yulianti, Ita
Jurnal Riset Informatika Vol. 4 No. 1 (2021): December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v4i1.135

Abstract

Inventory has an important role in business activities. This is because inventory has an effect on changes in the production market and anticipates price changes in the demand for many goods. PT. Barkah Jaya Mandiri is a company engaged in manufacturing where the management of inventory at the company is still done conventionally. This causes various problems such as the occurrence of discrepancies in the stock of goods, discrepancies in data and final reports as well as obstacles in the production process in the event of a shortage or excess of raw materials. (Material Requirement Planning) in order to overcome the problems that occur in the company. The combination of the SDLC model and data collection techniques including observation, interviews and literature study were also carried out in this study in order to achieve the system that will be built to suit the targeted needs. With this system, the management of inventory data at this company can be done easily and accurately and save time compared to the previous system, so that the procurement of manufacturing raw materials is optimal and employee performance is better.
DATA AUGMENTATION EFFECTS ON PROTONET FEW-SHOT YELLOW DISEASE SEVERITY IN CHILI LEAVES Rizal Amegia Saputra; Rusda Wajhillah; Yusti Farlina; Hani Noviani; Saela Nurusysyifa
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7458

Abstract

Yellow curling disease in chili plants is one of the leading causes of declining horticultural productivity because it reduces the quality and quantity of crops. Variations in symptoms at each level of severity make the identification process difficult, especially when labeled data is minimal. This study proposes a Prototypical Network-based Few-Shot Learning (FSL) approach with VGG16 architecture as a feature extractor. Five augmentation techniques, namely horizontal flip, rotation, zoom, brightness, and contrast adjustment, were used to increase data diversity in data-scarce conditions. Experiments were conducted with N-way K-shot configurations (2–5 classes; 1, 5, and 10 examples per class) to evaluate the impact of augmentation on prototype representation stability. Results show that increasing the number of examples per class consistently improves accuracy from 34.6% in 5-way 1-shot to 49.4% in 5-way 10-shot without augmentation. However, the use of augmentation decreases performance in higher N-way scenarios because it increases intra-class variability. The t-SNE visualization reinforces this study, where the healthy and severely diseased classes are clearly separated, while the intermediate class shows overlap. The novelty of this study is that it is the first to evaluate the impact of augmentation strategies on prototype representation stability in the agricultural domain with limited data. The results of this Few-Shot Learning approach are effective for plant disease classification despite the limited dataset.
Co-Authors A Gunawan A.Gunawan Abdussomad, Abdussomad Adi Supriyatna Aira Elzahra Aisyah Aisyah Ami Rahmawati Ami Rahmawati Andi Riyanto Angga Ardiansyah Dasya Arif Firmansaha Dede Firmansyah Saefudin Dede Saefudin Desi Susilawati - AMIK BSI Sukabumi Desi Susilawati, Desi Dewi Ayu Nur Wulandari Dewi Ayu Nurwulandari Diah Puspitasari Dudus Kurnia Duwi Cahya Putri Buani Eka Fitriani Erika Mutiara Fatmawati Fatmawati Ferdian Agustiana Gumgum Darmawan Hani Noviani Ilham Kurniawan Ilham Kurniawan Ita Yulianti Ita Yulianti Jamal Maulana Hudin Julia Rahmah Lis Saumi Ramdhani Medi Firmansyah Muhammad Faittullah Akbar Muhammad Sukrisno Mardiyanto Nandya Ayu Fatmandini Neng Senja Nekida Nita Novianti Novitasari, Dian C Rini Nurul Gusriani Pribadi, Denny Rahmawati, Ami Rahmawati, Rahmawati Ramdhan Saepul Rohman, Ramdhan Saepul Resti Yulistria Rimuljo Hendradi Rinda Nariswari Rizki Ramadhan Rosita Rosita Rusda Wajhillah Rusda Wajhillah, Rusda Ruslan Ruslan Rusli Nugraha Saeful Bahri Saela Nurusysyifa Septiani Nurfauzia K, Tya Shinta Ayuningtias Siti Masripah Sri Wasiyanti, Sri Supriatman, Supriatman Taufik Baidawi, Taufik Taufik Hidayatulloh Toto Haryanto Tya Septiani Nurfauzia K Vanysia Damayanti Wasyianti, Sri Widya Apriliah, Widya Yuri Rahayu Yusti Farlina