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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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Augmentasi Citra Pohon Kelapa Sawit untuk Deteksi Objek Berbasis Deep Learning Dedy Mirwansyah; Achmad Solichin; Fahrullah; Hardi, Richki; Wulan Sari, Nariza Wanti; Arista Rizki, 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.
Innovative Online Learning Media During the Covid-19 Pandemic Palupi, Shinta; Gunawan, Gunawan; Hardi, Richki
Jurnal Solusi Masyarakat (JSM) Vol. 1 No. 2 (2023): Pengembangan Kelompok
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jsm.v1i2.12198

Abstract

To improve the quality of the learning program, an efficient and effective approach in the teaching and learning process is required. Currently, educational strategies have become an essential process to enhance students' intelligence during this pandemic. In the field of education, the development of technology and communication requires training and learning using various methods. This approach involves training and teaching activities that are not limited by time and place, as they can be accessed and processed anytime and anywhere. This process aligns with the policy of the Ministry of Education and Culture of Indonesia in overcoming the challenges of learning during the Covid-19 pandemic. In the field of education, the common problem faced is the lack of effectiveness in learning. The methods of delivering materials used are not fully effective in utilizing learning resources. Additionally, suboptimal teaching schedules also affect the students' absorption of the material. Therefore, it is important to implement an approach that combines theory and practice through community service. By doing so, the results of this training will produce innovation in online learning using relevant tools, and enhance teachers' ability to implement self-directed learning approaches.
Employing Fuzzy AHP in Modeling a Decision Support System for Determining Scholarship Recipients within the University Context Mundzir, Mundzir; Zulkarnain, Riski; Hardi, Richki
Jurnal Solusi Masyarakat (JSM) Vol. 1 No. 2 (2023): Pengembangan Kelompok
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jsm.v1i2.12586

Abstract

In the realm of university scholarship programs, the process of selecting deserving recipients presents a complex decision-making challenge. This study explores the integration of Fuzzy Analytical Hierarchy Process (AHP) into the modeling of a Decision Support System (DSS) aimed at facilitating the determination of scholarship awardees. The utilization of Fuzzy AHP enables a more comprehensive and nuanced evaluation of candidates by accommodating uncertainties and imprecisions inherent in the decision-making process. This research investigates the application of Fuzzy AHP within the specific context of university scholarship recipient selection. The proposed DSS framework not only enhances the objectivity and transparency of the decision-making process but also contributes to the optimization of resource allocation and the identification of candidates best aligned with the scholarship's objectives. By employing Fuzzy AHP in this decision-support context, universities can effectively address the intricate considerations involved in awarding scholarships, thereby promoting fairness and increasing the likelihood of rewarding the most deserving individuals.
THE UTILIZATION OF COMPLEX PROPORTIONAL ASSESSMENT (COPRAS) IN DETERMINING THE SELECTION OF THE BEST SPEAKER Muhammad Rafli Nur Alam; Richki Hardi; Sumardi Sumardi
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 2 No. 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.629

Abstract

Decision-making in choosing the appropriate sound system involves numerous considerations to achieve acceptable outcomes or quality. There are many critical factors influencing the selection of speaker models, such as the required program features, brand, design, power, and price. In this study, we introduce the Complex Proportional Assessment (COPRAS) method as a solution for making effective and high-quality decisions when selecting the best alternatives based on predefined criteria. The COPRAS method is employed to analyze various different alternatives and estimate their utility values. The case study presented in this research involves identifying the best alternatives according to the criteria within the context of sound systems. The COPRAS method aids in evaluating alternatives by taking into account the relative weights of each relevant attribute. Consequently, the use of the COPRAS method in selecting the best sound system has proven to be effective and beneficial. This method assists in addressing complexity, enhancing objectivity, and yielding more informative and accurate decisions.
An Intrusion Detection System Using SDAE to Enhance Dimensional Reduction in Machine Learning Hanafi, Hanafi; Muhammad, Alva Hendi; Verawati, Ike; Hardi, Richki
JOIV : International Journal on Informatics Visualization Vol 6, No 2 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2.990

Abstract

In the last decade, the number of attacks on the internet has grown significantly, and the types of attacks vary widely. This causes huge financial losses in various institutions such as the private and government sectors. One of the efforts to deal with this problem is by early detection of attacks, often called IDS (instruction detection system). The intrusion detection system was deactivated. An Intrusion Detection System (IDS) is a hardware or software mechanism that monitors the Internet for malicious attacks. It can scan the internetwork for potentially dangerous behavior or security threats. IDS is responsible for maintaining network activity under the Network-Based Intrusion Detection System (NIDS) or Host-Based Intrusion Detection System (HIDS). IDS works by comparing known normal network activity signatures with attack activity signatures. In this research, a dimensional reduction and feature selection mechanism called Stack Denoising Auto Encoder (SDAE) succeeded in increasing the effectiveness of Naive Bayes, KNN, Decision Tree, and SVM. The researchers evaluated the performance using evaluation metrics with a confusion matrix, accuracy, recall, and F1-score. Compared with the results of previous works in the IDS field, our model increased the effectiveness to more than 2% in NSL-KDD Dataset, including in binary class and multi-class evaluation methods. Moreover, using SDAE also improved traditional machine learning with modern deep learning such as Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN). In the future, it is possible to integrate SDAE with a deep learning model to enhance the effectiveness of IDS detection
Co-Authors Achmad Solichin Agus Sasmito Alva Hendi Muhammad Amir Zakry, Khalif Anastasia Lidya Maukar Angga Pratama Apri Junaidi, Apri 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 Gunawan Gunawan Hanafi Hanafi Hashim, Ummi Rabah Hassan, Ruhana Hipiny, Irwandi 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 Mutammimul Ula Naim Che pee Naim Che Pee Nanda Arista Rizki Nanna Suryana Nanna Suryana Herman Nariza Wanti Wulan Sari Palupi, Shinta Prabawani, Isti Rahmat Saudi Alfathir Rana Zabrina Ririn Kusdyawati 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 Verawati, Ike Wahyu Fuadi Wahyu Nur Alimyaningtias Wahyu Nur Alimyaningtyas Wahyu Nur Alimyaningtyas Yamani Yamani Yana Hendriana Yustian Zabrina, Rana Zaini Zaini Zulkarnain, Riski