Article Per Year (5 Year)
p-Index From 2020 - 2025
4.968
P-Index
This Author published in this journals
All Journal Jurnal Algoritma Jurnal Teknologi Informasi dan Ilmu Komputer JAIS (Journal of Applied Intelligent System) CESS (Journal of Computer Engineering, System and Science) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Proaksi Jurnal E-Bis: Ekonomi Bisnis Jurnal Akuntansi dan Keuangan Journal of Management and Digital Business Jurnal Algoritma Malcom: Indonesian Journal of Machine Learning and Computer Science Literacy : International Scientific Journals of Social, Education, Humanities Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) Jurnal Teknologi Informasi RISTEC : Research in Information Systems and Technology Journal of Knowledge Management Jurnal Pengabdian Masyarakat
Fikri Fahru Roji
Universitas Garut
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

Published : 40 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 40 Documents
Search

 1   2   3   4 
Topic Modeling in Thesis Titles of Students from the Faculty of Economics Universitas Garut Using Latent Dirichlet Allocation Modeling Fikri Fahru Roji; Dinar Rahayu; Riyad Sabilul Muminin; Dendi Ramdani; Dede Hendrik
RISTEC : Research in Information Systems and Technology Vol 4, No 1 (2023): Riset Sistem dan Teknologi Informasi
Publisher : Institut Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/ristec.v4i1.3380

Abstract

In higher education, the completion of a thesis within a 1-year timeframe is a prerequisite for graduation. The selection of a thesis topic is influenced by personal interest, the expertise of the thesis supervisor, and data availability. This research is designed to analyze the thesis topics of Economics Faculty students at Garut University using the Latent Dirichlet Allocation (LDA) Modeling method. Utilizing quantitative and qualitative approaches, this research applies the concept of big data with techniques such as Data Crawling, Data Preprocessing, and Text Mining. The research successfully conducted topic modeling using the LDA method. The analysis showed that topic modeling with the LDA algorithm resulted in seven common thesis topics used in the students' thesis titles. With this, the research contributes to the understanding and efficacy in the determination of students' thesis topics. It is hoped that the results of this research can be utilized to assist in the efficient completion of theses. Keywords: Topic Analysis; Topic Modeling; Thesis Title; Latent Dirichlet Allocation; LDA
Analisis Sentimen Publik terhadap Kebijakan Insentif Perpajakan Dengan Pendekatan VADER (Valence Aware Dictionary And Sentiment Reasoner) Windi Ariesti Anggraeni; Fikri Fahru Roji; Muslim Alkautsar
Jurnal Proaksi Vol. 10 No. 4 (2023): Oktober - Desember
Publisher : Fakultas Ekonomi dan Bisnis, Universitas Muhammadiyah Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32534/jpk.v10i4.4732

Abstract

Kebijakan perpajakan sering kali menjadi isu yang kontroversial dan mendapat reaksi yang berbeda dari publik. Kebijakan yang dirancang oleh pemerintah sering kali memicu beragam tanggapan di kalangan masyarakat. Tanggapan ini mengandung beragam sentimen serta respons positif dan negatif di berbagai platform media sosial. Tujuan dari penelitian ini adalah untuk menganalisis bagaimana sentimen publik terhadap kebijakan perpajakan khususnya program insentif pajak melalui media sosial Twitter. Metode penelitian yang digunakan adalah deskriptif kualitatif dengan pendekatan  VADER (Valence Aware Dictionary And Sentiment Reasoner). Penelitian ini menghadirkan kebaruan dengan menerapkan metode analisis sentimen VADER yang belum banyak digunakan pada penelitian sebelumnya. Pendekatan ini dapat mengukur bagaimana respons masyarakat terhadap kebijakan perpajakan melalui media sosial,  serta memberikan pemahaman yang lebih mendalam tentang interaksi antara kebijakan publik dan persepsi masyarakat. Hasil penelitian menunjukkan bahwa terdapat sentimen positif, apresiasi, dan dukungan atas kebijakan insentif pajak, sejalan dengan pernyataan bahwa insentif perpajakan memiliki potensi untuk mendorong pertumbuhan ekonomi dan membantu sektor-sektor tertentu. Namun, juga terdapat kritikan dan pandangan negatif yang menyoroti masalah ketidaksetaraan dan ketidakpuasan terhadap distribusi insentif pajak.
Komparasi Algoritma Support Vector Machine dan Naïve Bayes untuk Analisis Sentimen pada Metaverse: Comparison of Support Vector Machine and Naïve Bayes Algorithms for Sentiment Analysis of the Metaverse Dea Nurmastin Novianti; Diqy Fakhrun Shiddieq; Fikri Fahru Roji; Wati Susilawati
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 1 (2024): MALCOM January 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i1.1061

Abstract

Metaverse telah mencuri perhatian dunia karena kemampuannya untuk menggabungkan dunia nyata dan dunia virtual. Minat terhadap metaverse semakin meningkat seiring dengan dampak pandemi COVID-19 dan proyek pembangunan Ibu  Kota Nusantara (IKN), serta pertumbuhan penggunaan platform digital. Perbincangan isu metaverse semakin meroket naik setelah perusahaan Facebook merubah namanya menjadi Meta. Studi ini bertujuan untuk membandingkan  akurasi tertinggi antara metode algoritma Naïve Bayes dengan SVM  dalam menganalisis respons masyarakat terhadap metaverse. Studi ini menggunakan metode sentiment analisis. Penggunaan dua algoritma menjadi keterbaruan penelitian. Studi kali ini  menggunakan data yang diambil dari Twitter (x) dan disimulasikan menggunakan sentiment analisis dari algoritma SVM dan  algoritma Naïve Bayes. Berdasarkan penelitian, ditemukan bahwa akurasi algoritma SVM mencapai 90,32% presisi sebesar 0,90 dan recall sebesar 0,86, sedangkan algoritma Naïve Bayes mencapai 84,23% presisi sebesar 0,87 dan recall sebesar 084. Dengan adanya penelitian ini dapat memberikan wawasan terhadap tren metaverse, serta membandingkan hasil akurasi tertinggi antara  dua algoritma.  
Pemodelan Topik pada Media Berita Online Menggunakan Latent Dirichlet Allocation (Studi Kasus Merek Somethinc): Topic Modeling on Online News Media Using Latent Diriclet Allocation (Case Study Somethinc Brand) Evi Puspita; Diqy Fakhrun Shiddieq; Fikri Fahru Roji
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1204

Abstract

Somethinc merupakan salah satu merek kosmetik lokal di Indonesia yang aktif memanfaatkan media, seperti berita online untuk menyampaikan informasi terkini seputar merek. Dari banyaknya berita online mengenai merek Somethinc, sering kali topik dan tren yang sedang dibahas tidak menggambarkan informasi secara keseluruhan. Untuk menganalisis topik yang paling sering dibahas dalam berita online mengenai merek Somethinc, peneliti menggunakan metode topic modeling, yaitu Latent Dirichlet Allocation, yang dinilai lebih unggul dalam menghasilkan topik secara terstruktur. Penelitian ini memanfaatkan nilai coherence untuk menganalisis dan mengevaluasi jumlah topik terbaik, selanjutnya pendekatan human judgement digunakan untuk menginterpretasikan topik. Hasil analisis kemudian divisualisasikan secara interaktif menggunakan pyLDAvis, untuk mengetahui persebaran kata dari setiap topik. Berdasarkan hasil penelitian, jumlah topik terbaik terdapat pada topik 6 dengan nilai coherence sebesar 0.404. Keenam topik tersebut diinterpretasikan berdasarkan pendekatan human judgement, menghasilkan topik-topik meliputi produk skincare untuk kulit berjerawat, penghargaan brand kecantikan terbaik, kolaborasi produk, produk perawatan kulit dan kecantikan, kampanye pemasaran produk, dan brand lokal dengan produk perawatan kecantikan. Dapat disimpulkan bahwa jumlah topik 6 menghasilkan topik-topik yang relevan mengenai merek Somethinc.
Model dan Implementasi Geographic Information System untuk Pemetaan UMKM di Kabupaten Garut Diqy Fakhrun Shiddieq; Fikri Fahru Roji; Wufron Wufron; Surya Garian Bekti
Jurnal Algoritma Vol 20 No 2 (2023): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.20-2.1455

Abstract

Usaha Mikro Kecil dan Menengah (UMKM) have an important role in the economy in Indonesia. UMKM have a significant contribution to national gross domestic product (PDB) and encourage the creation of new jobs. Based on data, more than half of the MSMEs in Indonesia are on the island of Java. Garut Regency is one of the regions in West Java which has more than 200 thousand UMKM with various products. UMKM products owned include wickerwork, weaving, specialty foods, leather centers and others. The Garut Regency area is quite large and it is noted that the distribution of UMKM is not centralized. So that stakeholders and the government experience difficulties in planning, implementing and evaluating programs designed to encourage increased performance of UMKM. Researchers found the urgency of research that had not been fully tested empirically and an ideal model had not been produced, so it was felt necessary to carry out this research. Previous research was carried out only on certain UMKM, namely the partial implementation of the Geographic Information System (GIS) for Garut Regency UMKM. However, overall UMKM data has not been found, so this is a novelty in this research. The methodology used is a prototype which has three main processes, namely listening to customer needs, building software and testing. The result of this research is to build a web-based geographic information system for the distribution of UMKM in Garut Regency which is expected to help understand the condition of UMKM better.
Perancangan Sistem Informasi Bimbingan Skripsi Online (SIBIMO) dengan SCRUM Framework Fikri Fahru Roji; Diqy Fakhrun Shiddieq; Ridian Gusdiana; Evi Puspita
Jurnal Algoritma Vol 20 No 2 (2023): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.20-2.1459

Abstract

The development of technology and the internet has opened up opportunities for advances in information systems. In this context, the Online Thesis Guidance Information System (SIBIMO) is an efficient solution in the thesis guidance process in higher education. With the SCRUM method, SIBIMO allows students to submit thesis titles, interact with supervisors, and manage seminar and trial stages through a designed user interface. This methodology combines stages such as UI design, functionality testing, and progress evaluation. Testing each SIBIMO menu ensures the system is running as intended. SCRUM allows achieving development time targets and efficient adaptation at each iteration. This research concludes that SIBIMO, which was developed using the SCRUM method, was successful in designing an Information System that was carried out effectively and efficiently in managing the Online Tutoring Information System design process.
Topic Modeling in Thesis Titles of Students from the Faculty of Economics Universitas Garut Using Latent Dirichlet Allocation Modeling Fikri Fahru Roji; Dinar Rahayu; Riyad Sabilul Muminin; Dendi Ramdani; Dede Hendrik
RISTEC : Research in Information Systems and Technology Vol. 4 No. 1 (2023): JURNAL RISTEC : Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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

Abstract

In higher education, the completion of a thesis within a 1 -year timeframe is a prerequisite for graduation. The selection of a thesistopic is influenced by personal interest, the expertiseof the thesis supervisor, and data availability. This research is designed to analyzethe thesis topics of Economics Faculty students at Garut University using the Latent Dirichlet Allocation (LDA) Modeling method. Utilizing quantitative and qualitative approaches, this research applies the concept of big data with techniques such as Data Crawling, Data Preprocessing, and Text Mining. The research successfully conducted topic modeling using the LDA method. The analysis showed that topic modeling with the LDA algorithm resulted in seven common thesis topics used in the students' thesis titles. With this, theresearch contributes to the understanding and efficacy in the determination of students' thesis topics. It is hoped that the results of this research can be utilized to assist in the efficient completion of theses.
Review Analysis of SatuSehat Application Using Support Vector Machine and Latent Dirichlet Allocation Modeling Fikri Fahru Roji; Nava Gia Ginasta; Yayan Cahyan; Dinar Rahayu; Dendi Ramdani
RISTEC : Research in Information Systems and Technology Vol. 4 No. 1 (2023): JURNAL RISTEC : Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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

Abstract

SatuSehat is a contact tracing application that replaces the PeduliLindungi application initiated by the Government of Indonesia with the aim of tracking the Covid -19 Virus. The success of the application can be known by analyzing sentiment reviews. In addition to the high number of reviews, there are also other things that need to be highlighted, namely the pattern of reviews that are not in accordance with refined spelling and diverse topics, so that identifying a topic from a collection of reviews is very difficult and takes a lot of time if done manually by humans. This research describes sentiment analysis and topic modeling on SatuSehat app user reviews. By applying Support Vector Machine (SVM) method for sentiment analysis and Latent Dirichlet Allocation (LDA) for topic modeling, this study reveals the views and trends expressed by users. The analyzed review data from Google Play Store includes 171,428 positive reviews and 131,246 negative reviews. The sentiment analysis results indicated the dominance of positive responses. LDA modeling resulted in 8 identified topics, from health concerns to app appreciation. However, negative topics included vaccination challenges, access issues, and app functionality. This research provides insight into users' perceptions of the SatuSehat app, providing a basis for further development and improvement of the app.
Conducting Penetration Testing to Identify Vulnerabilities in a Bank Company Information Technology Nava Gia Ginasta; Krisnawanti; Fikri Fahru Roji
RISTEC : Research in Information Systems and Technology Vol. 4 No. 2 (2023): RISTEC : Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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

Abstract

Company XYZ is a regional business entity that manages finances and provides credit to small businesses. However, their e-banking applications have vulnerabilities that hackers can exploit. This research aims to identify and understand potential attacks on these vulnerabilities, assess the impact of exploitation by attackers, and provide recommendations for securing computer systems and networks based on penetration testing results. The XYZ e-banking application web server can be tested using five methods: Vulnerability Scanning, Apache Tomcat Sample Directory Vulnerabilities, Cross-Site Request Forgery (CSRF), Weak Cryptographic Testing, and Header Security. The application is in the Warning to High category, which indicates that it requires follow-up action. To mitigate the vulnerability, developers can take steps such as deleting the /examples directory, limiting the validity of cookies, using SSL and enabling Mod Security.
Design and Development of a Web-Based Community Service Information System at Garut University Riyad Sabilul Muminin; Dendi Ramdani; Fikri Fahru Roji
RISTEC : Research in Information Systems and Technology Vol. 4 No. 2 (2023): RISTEC : Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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

Abstract

The Community Service Program (KKN) is a mandatory activity in universities aimed at enhancing students' competencies in teamwork, leadership, and soft skills partnerships with the community. However, the implementation of KKN often faces challenges such as data inconsistencies, complex registration processes, and difficulties in activity management. This research aims to design and build a website-based KKN information system at Garut University to address these issues. By utilizing website technology, this system is expected to improve the efficiency and effectiveness of KKN implementation.This research employs the Unified Software Development Process (USDP) methodology, which is iterative and adaptive. The stages in USDP, namely inception, elaboration, construction, and transition, are followed systematically. In the inception phase, a needs analysis and feasibility study are conducted to determine the project scope. The elaboration phase produces the system architecture design and functional requirements specifications. The construction phase focuses on implementing the system according to the design that has been made. Finally, the transition phase includes testing, deployment, and system maintenance.The result of this research is a complete and functional website-based KKN information system. The system provides features such as online registration, group management, activity reporting, monitoring, and evaluation. System testing shows that this system is able to meet user needs and provide significant benefits in the implementation of KKN at Garut University. This system can also be an example for other universities that want to improve the quality of KKN implementation through the use of information technology.
Co-Authors AA Sudharmawan, AA Abdi Ilahi, Pyar Abdul Latip, Abdul Alkautsar, Muslim Anggraeni, Windi Ariesti Apriliya Nuraini, Raden Putri Ardiani, Kamila Syifa Arifah Nursadrina, Raisya Asri Mulyani Bekti, Surya Garian Cahyan, Yayan Dea Nurmastin Novianti Dede Hendrik Dede Hendrik Dendi Ramdani Dewi Tresnawati Dinar Rahayu Dinar Rahayu Diqy Fakhrun Shiddieq Eri Satria Evi Puspita Fakhrun Shiddieq, Diqy Fatimah, Nyinyi Ferdian Imawan Ghaida Farisya Hasbi S, Muhamad Indri Tri Julianto Insani, Aura Krisnawanti Kusmiati, Eti Lusiana Nur Safitri Marchella, Amanda Mega Silvia Moch. Rizky Cahyadiputra Muslim Alkautsar Nava Gia Ginasta Nurhasan, Rohimat Permatasari, Rd Intan Puspita, Evi Putri Sukmana, Reinta Rahma Dianti, Ahrami Rahmawati . Ramdan, Galih Muhammad Ridian Gusdiana Ridwan Fauzi, Muhamad Ridwan Setiawan Ridwan Setiawan Riyad Sabilul Muminin Rizkia, Agnia Suci Rohanudin, Muhammad Sabda Ilahi, Perceka Sabrina, Siti Sarah Salamah, Susi Salamatuddaroen, Intan Salman Fariz SALSABILA, ANNISA Shiddied, Diqy Fahrun Shiddieq , Diqy Fakhrun Shiddieq, Diqy Fakhrun Siti Nurhasanah Suci Lestari Surya Garian Bekti Susilawati , Wati Syinta Almaiddah Taofiqurrohman, Hendra Utami, Wulan Sri Wati Susilawati Wildan Hidayatul Hamdi Wufron Wufron Yaman Suryaman, Yaman