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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Telematika : Jurnal Informatika dan Teknologi Informasi JOURNAL OF INFORMATICS AND COMPUTER SCIENCE JOIV : International Journal on Informatics Visualization Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JST ( Jurnal Sains Terapan ) JTT (Jurnal Teknologi Terpadu) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) METIK JURNAL Mulia International Journal in Science and Technical Seminar Nasional Teknologi Informasi Komunikasi dan Administrasi [SEMINASTIKA] JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Multica Science and Technology MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Jurnal Malikussaleh Mengabdi Jurnal Solusi Masyarakat (JSM) Language Circle : Journal of Language and Literature
Richki Hardi
Universitas Mulia
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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E-Learning course design and implementation in fuzzy logic Gunawan Gunawan; Richki Hardi
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 12 No. 1 (2022): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v12i1.31-37

Abstract

The goal of e-learning in fuzzy logic courses is to assist students in the learning process, create menu structures and simple operation techniques, and create prototypes for e-learning in fuzzy logic courses. The difficulty of students in implementing what they have learned stems from the fact that the advent of e-learning can make it simpler for students to access material that they do not comprehend. In this study, an analytic learning prototype was used as the research approach. The outcomes of e-learning products based on online apps in this fuzzy logic course can be used as learning material. The menu structure developed in this e-learning is a home page with an introduction to e-learning, a site page with participants, calendars, and notes. Pages that can be used to grow the network and courses are the most significant aspects of e-learning. E-learning includes material, discussion, forums, quizzes, and other activities. The findings of the validation by media specialists on this e-learning application are pretty good, indicating that it is suitable for use. According to the results of material expert validation, the material used is excellent, suggesting that it is ideal for use in fuzzy logic courses. The limited test results for Informatics study program students were in the very good category, indicating that this e-learning tool was simple to use.
Predicting financial default risks: A machine learning approach using smartphone data Shinta Palupi; Gunawan; Ririn Kusdyawati; Richki Hardi; Rana Zabrina
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 14 No. 3 (2024): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v14i3.107-118

Abstract

This study leverages machine learning (ML) techniques to predict financial default risks using smartphone data, providing a novel approach to financial risk assessment. Data were collected from 1,000 individuals who had taken personal loans, focusing on key behavioral parameters such as app usage frequency, GPS location data, and communication patterns over a six-month period prior to loan application. The analysis employed Logistic Regression, Decision Trees, and Random Forest models to determine correlations between these parameters and default risks. The Random Forest model demonstrated superior performance, achieving 85% accuracy. Key findings show that high usage of financial apps was associated with lower default risks, while irregular communication patterns and erratic mobility were significant indicators of higher risk. These results suggest that smartphone-derived behavioral data can significantly enhance traditional credit scoring methods. The study not only contributes to predictive analytics in financial risk management but also raises ethical considerations around privacy and data security.
Augmentasi Citra Pohon Kelapa Sawit untuk Deteksi Objek Berbasis Deep Learning Dedy Mirwansyah; Achmad Solichin; Fahrullah; Hardi, Richki; Wulan Sari, Nariza Wanti; Arista Riski, Nanda; Aldo, Dasril
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 1 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v9i1.1001

Abstract

Penelitian ini menitikberatkan pada Augmentasi citra pohon kelapa sawit untuk deteksi objek menggunakan pendekatan Deep Learning. Pohon kelapa sawit memiliki peran penting dalam industri perkebunan dan pertanian, sehingga pengembangan metode deteksi pohon kelapa sawit yang efisien menjadi krusial dalam pemantauan perkebunan dan pengelolaan sumber daya alam. Metode penelitian melibatkan augmentasi citra, seperti flip, crop, hue, saturation, brightness, exposure dan pra-pemrosesan auto orient dan resize untuk meningkatkan kualitas data pelatihan. Model Deep Learning yang digunakan adalah Convolutional Neural Network (CNN) yang terintegrasi dengan teknik object detection, memungkinkan identifikasi pohon kelapa sawit dari latar belakang dengan akurasi tinggi. Penelitian ini menggunakan 101 citra kepala sawit dan setelah dilakukan augmentasi berjumlah 253 citra pohon kelapa sawit yang bervariasi dalam kondisi pencahayaan, sudut pandang, dan penutupan daun. Hasil eksperimen menunjukkan bahwa metode ini mampu mengidentifikasi pohon kelapa sawit dengan akurasi yang baik, bahkan dalam kondisi yang kompleks. Hasil penelitian ini memiliki potensi aplikasi dalam pemantauan perkebunan kelapa sawit, perencanaan lahan, dan pemantauan lingkungan. Dengan peningkatan akurasi deteksi dan ekstraksi, manajemen perkebunan dan pemantauan lingkungan dapat menjadi lebih efisien dan berkelanjutan.
Designing Mobile Application Dictionary Based on Students' Needs for Enhancing IT-Focused English Vocabulary Riski Zulkarnain; Rahmat Saudi Alfathir; Richki Hardi; Mundzir , Mundzir; Lisda Hani Gustina; Wahyu Nur Alimyaningtias; Nove Kurniati Sari; Syaddam , Syaddam
Language Circle: Journal of Language and Literature Vol. 19 No. 1 (2024): October 2024 Regular Issue
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/lc.v19i1.10507

Abstract

The present study aims to design a mobile application dictionary that caters to students' needs for enhancing IT-focused English vocabulary. The study explores the effectiveness of the designed mobile application in improving students' IT-focused English vocabulary, their engagement in vocabulary learning, and their overall satisfaction with the application. This research aims to design a mobile application dictionary to enhance IT-Focused English Vocabulary. The study employs a mixed-methods approach, combining qualitative interviews and a quantitative survey, to understand the design requirements, implementation strategies, and effectiveness of the mobile application dictionary. The qualitative phase involves semi-structured interviews with IT students and subject matter experts to gain insights into the learners' challenges, preferences, and needs, as well as the crucial IT English vocabulary concepts. The quantitative phase evaluates the impact of the mobile application dictionary on IT students' vocabulary knowledge, confidence, and overall satisfaction through a survey. The integrated findings will provide a comprehensive understanding of the factors that contribute to the success of mobile application dictionaries in enhancing IT students' informatics English vocabulary, with practical implications for the development of similar language learning tools.
Co-Authors Achmad Solichin Agus Sasmito Alva Hendi Muhammad Amir Zakry, Khalif Anastasia Lidya Maukar Angga Pratama Apri Junaidi, Apri Arista Riski, Nanda Budi Sunaryo Dahlan Abdullah Dasril Aldo Dedy Mirwansyah Ermatita - Eva Darnila Fahrullah Fahrullah Fajriana, Fajriana Farah Farhana Fathiah Fathiah Gunawan Gunawan Gunawan Gunawan Gunawan Gunawan Hanafi Hanafi Hashim, Ummi Rabah Hassan, Ruhana Hipiny, Irwandi Ike Verawati ilham - sahputra Iwan Pahendra Iwan Pahendra Anto Saputra Jack Febrian Rusdi Kamalrudin, Massila Kusdyawati, Ririn Lisda Hani Gustina M. Yamani Mauliza Mochammad Imron Awalludin Mohamad Adriyanto Muhammad Rafli Nur Alam Muhammad Sadli Mundzir , Mundzir Mundzir Mundzir Mundzir Mundzir, Mundzir Mutammimul Ula Naim Che pee Naim Che Pee Nanna Suryana Nanna Suryana Herman Nariza Wanti Wulan Sari Prabawani, Isti Rahmat Saudi Alfathir Rana Zabrina Ririn Kusdyawati Riski Zulkarnain Riski Zulkarnain Riyadhul Fajri Saiful Ghozy Saputra A, Andi Indra Sari, Nove Kurniati Shinta Palupi Shinta Palupi Sigit Sigalayan Sigit Sigalayan Sujacka Retno SUMARDI Sumardi Sumardi syaddam, syaddam Syahiran Soria, Mohamad Tsania Asha Fadilah Daulay Ujir, Hamimah Wahyu Fuadi Wahyu Nur Alimyaningtias Wahyu Nur Alimyaningtyas Wahyu Nur Alimyaningtyas Yamani Yamani Yana Hendriana Yustian Zabrina, Rana Zaini Zaini Zulkarnain, Riski