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All Journal Jurnal Komputer Terapan Seminar Nasional Teknologi Informasi Komunikasi dan Industri JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Media Informatika Jurnal Pengabdian Masyarakat Multidisiplin Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Ilmiah Raflesia Akuntansi Jurnal Nasional Teknik Elektro dan Teknologi Informasi Literasi: Jurnal Pengabdian Masyarakat dan Inovasi Proceeding Applied Business and Engineering Conference JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat)
Nurmalasari, Dini
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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

 1 
Analisis Proses Reduksi Dimensi dengan Metode Frequent Itemset Mining pada Sistem Rekomendasi Referensi Karya Ilmiah Dini Nurmalasari; Warnia Nengsih
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3332

Abstract

Salah satu tahapan dalam penelitian yang harus dilakukan adalah mencari referensi jurnal yang relevan dengan penelitian yang akan dikerjakan. Dalam melakukan pencarian referensi, biasanya peneliti memasukan kata kunci atau keyword yang sesuai dengan tema yang akan diteliti. Kata kunci tersebut biasanya terdiri dari satu atau dua kata, sehingga hasil yang didapatkan kurang sesuai dengan pencarian yang diinginkan, atau diperlukan studi literatur yang cukup banyak untuk mencukupi referensi keseluruhan penelitian. Pada penelitian ini akan dilakukan pencarian referensi yang relevan dengan menggunakan masukan berupa dokumen teks publikasi ilmiah atau jurnal ilmiah. Dokumen teks yang dijadikan masukan, akan dilakukan ekstraksi kemudian akan dicari tingkat kemiripan dengan dokumen lain dalam database. Keluaran dari system ini berupa daftar dokumen yang relevan dengan masukan dokumen teks beserta persentase kemiripannya. Melalui system rekomendasi referensi karya ilmiah yang dibuat dengan menerapkan metode frequent itemset mining (FIM), akan dilakukan analisis keberhasilan reduksi dimensi yang dapat mempengaruhi akurasi hasil. Dari pengujian yang telah dilakukan diperoleh bahwa FIM berhasil mereduksi dimensi fitur kata dengan rata-rata sebesar 80,17% menggunakan minimum support 0,1. Sehingga dapat disimpulkan bahwa metode FIM efektif dalam melakukan reduksi dimensi sehingga menjadi salah satu factor yang mempengaruhi akurasi hasil.
Improving Panic Disorder Classification Using SMOTE and Random Forest Nurmalasari, Dini; Yuliantoro, Heri R; Qudsi, Dini Hidayatul
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8315

Abstract

Panic disorder is a serious anxiety disorder that can significantly impact an individual's mental health. If left undetected, this disorder can disrupt daily life, social relationships, and overall quality of life. Early detection and intervention are crucial for managing panic disorder and improving the well-being of those affected. Technology plays a pivotal role in facilitating early detection through data-driven approaches that employ algorithms to identify patterns of behavior or symptoms associated with panic disorder. Accurate classification of panic disorder is crucial for effective diagnosis and treatment. However, machine learning models trained on imbalanced datasets, such as those containing panic disorder patients, are prone to overfitting, leading to poor generalization performance. This study investigates the effectiveness of the Synthetic Minority Oversampling Technique (SMOTE) in addressing overfitting in panic disorder dataset classification using the Random Forest algorithm. The results demonstrate that SMOTE significantly improves the classification performance of Random Forest. By mitigating overfitting and improving generalization to unseen data, SMOTE increases accuracy by 15 percentage points. Before using SMOTE, the accuracy was 82%, and after using SMOTE it is 97%. The findings underscore the promise of SMOTE as a tool for boosting the performance of machine learning algorithms in classifying panic disorder from imbalanced data.
Analisis Faktor-Faktor yang Mempengaruhi Harga Saham pada Perusahaan Sub Sektor Kosmetik dan Barang Keperluan Rumah Tangga dengan Python Yuliantoro, Heri Ribut; Nurmalasari, Dini
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4606

Abstract

This study aims to determine the relationship between stock prices of companies listed on the Stock Exchange in the Household Goods and Cosmetics sub-sector with several independent variables, namely quick ratio, current ratio, net profit margin, and return on assets. The analysis carried out is multiple regression analysis, conventional hypothesis testing, and descriptive analysis. The results of this study indicate that the current ratio and return on assets have a large influence on stock prices on the IDX, quick ratios and net profit margins have no significant effect. Return on assets, net profit margin, quick ratio, and current ratio all together have a big influence on stock prices. The results of the analysis of this study can be concluded that stock prices are positively influenced by the variables quick ratio, current ratio, net profit margin, and return on assets of 49.4%, and the remaining 50.6% is influenced by other factors.
Co-Authors Akbar, Memen Akbar, Memen Alim Syahbana, Yoada Alim Syahbana, Yoanda Arifulsyah, Hamdani Chairani, Nessa Cici Patmala Dini Hidayatul Qudsi Emansa Hasri Putra Erwin Setyo Nugroho Fadhly, Mardhiah Fadli, Mardhiah Fathu Rahmi Heri Ribut Yuliantoro, Heri Ribut Heri Yuliantoro Hidayat, Muhammad Taufiq Kartina Diah K. W. Mardhiah Fadhli Mardhiah Fadhli, Mardhiah Mardhian Fadhly memen akbar Mutia Sari Zulvi mutia sari zulvi Nabilah Nasution Nazifa Hayati Neni Febriani Nurzikriah Nurzikriah Palapa, Yusmar Patmala, Cici Puja Hanifah Purwantoro E.S.G.S, Sugeng Purwantoro, Sugeng Putri Radha Retro Tri Wahyuni Rizky Mirza, Junaldo Saleha Indri Yanti Sugeng Purwantoro E.S.G.S Sugeng Purwantoro ESGS Tinambunan, Theresia Elfina Tri Wahyuni, Retro Uun Patrio Warnia Nengsih Wenda Novayani Wenda Novayanti Yoanda Alim Syahbana Yuli Fitrisia Yuli Fitrisia Yuli Fitrisia, Yuli Fitrisia Yuliantoro, Heri R Yusmar Palapa Zusanti Syahrial