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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 Rekam Kegiatan Pengabdian Masyarakat (REKAGAMA)
Richki Hardi
Universitas Balikpapan
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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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
Pelatihan Pemanfaatan Canva dan Google Business Profile untuk Penguatan Pemasaran Digital UMKM di Sanden Bantul Richki Hardi
REKAGAMA Vol. 1 No. 2 (2026): REKAGAMA (Rekam Kegiatan Pengabdian Masyarakat)
Publisher : CV Mazaya Cahaya Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Transformasi digital membuka peluang bagi usaha mikro, kecil, dan menengah (UMKM) untuk memperluas jangkauan pasar, namun sebagian pelaku usaha masih menghadapi keterbatasan dalam pembuatan konten promosi dan pengelolaan informasi bisnis pada mesin pencari. Kegiatan pengabdian kepada masyarakat ini dirancang untuk meningkatkan kompetensi pemasaran digital pelaku UMKM di Sanden, Kabupaten Bantul, melalui pelatihan Canva dan Google Business Profile. Metode kegiatan menggunakan pendekatan partisipatif yang terdiri atas analisis kebutuhan, sosialisasi, pelatihan berbasis praktik, pendampingan pembuatan luaran digital, serta evaluasi melalui pretest, posttest, observasi, dan penilaian produk. Sebanyak 20 peserta dilibatkan dalam skenario evaluasi . Materi meliputi prinsip desain promosi, pembuatan templat konten, penyusunan katalog sederhana, pembuatan dan optimasi profil bisnis, penambahan lokasi, jam layanan, foto, serta pengelolaan ulasan pelanggan. Hasil menunjukkan peningkatan skor rata-rata pengetahuan dan keterampilan dari 39,0 menjadi 80,8. Sebanyak 18 peserta berhasil menghasilkan minimal dua konten promosi, 17 peserta menyusun katalog digital, dan 16 peserta menyelesaikan profil bisnis yang memuat informasi utama. Kegiatan juga menghasilkan panduan singkat dan grup pendampingan sebagai sarana tindak lanjut. Model pelatihan berbasis praktik dinilai relevan karena menggabungkan kreativitas visual dan visibilitas pencarian lokal. Keberlanjutan program memerlukan pembaruan konten secara rutin, pengamanan akun, evaluasi statistik interaksi, dan dukungan kelembagaan dari pemerintah kalurahan atau komunitas UMKM.
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.
Co-Authors Achmad Solichin Agus Sasmito Alva Hendi Muhammad Amir Zakry, Khalif Anastasia Lidya Maukar Andi Indra Saputra Alamsyah 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 Hanafi Hanafi Hashim, Ummi Rabah Hassan, Ruhana Hipiny, Irwandi ilham - sahputra Iwan Pahendra 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 Rana Zabrina Ririn Kusdyawati Ririn Kusdyawati Riski Zulkarnain Riyadhul Fajri Saiful Ghozy 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