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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

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Journal : RISTEC : Research in Information Systems and Technology

 1 
The Study of Decision Tree Algorithm For Classification of Student Graduation (Case Study : Faculty of Economics, University of Garut) Fikri Fahru Roji; Rahmawati .; Dendi Ramdani
RISTEC : Research in Information Systems and Technology Vol 2, No 1 (2021): Research in Information Systems and Technology
Publisher : Institut Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (338.388 KB) | DOI: 10.31980/ristec.v2i1.1215

Abstract

The academic performance is one of aspect which has remained the benchmark of the success in learning activities at the university. The indicator of academic performance in the university is the students able to complete their studies on time. Unfortunately, the problem regarding academic performance was associated with the completion time of student studies in Faculty of Economics,University of Garut. In this research explore the model that able to classify the graduation of student through the data mining classification technique by Decision Tree Algorithm. The classification conducted by evaluating the academic performance based on Semester Performance Index (IPS) and Semester Credit Unit (SKS) during two years in the beginning and use the demographics of students as attributes that will be used in the dataset. Based on the examinations that conducted by using k-fold cross validation, there are 8 attributes that influence the graduation of students. The model that represented able to applied for classify the active students in 2016 and 2017 that indicate accuracy value of 79.53% and recall value was 19.23%.
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): Riset Sistem dan Teknologi Informasi
Publisher : Institut Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/ristec.v4i1.3312

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. Keywords: Sentiment Analysis; Topic Modeling; OneHealth App; SVM; LDA
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
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

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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

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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.
Uncovering Hidden Sentiments and Topics in Online Lending Application Reviews with the Valence Aware Dictionary and sEntiment Reasoner (VADER) and Latent Dirichlet Allocation (LDA) Approaches Fikri Fahru Roji; Windi Ariesti Anggraeni; Riyad Sabilul Muminin; Dendi Ramdani; Yayan Cahyan
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

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Abstract

Online lending (pinjol) has become an important part of the digital transformation of the financial sector, offering people easy access to funds. However, the increasing reliance on user reviews as a decision-making factor raises concerns about their authenticity and credibility. This research aims to analyze the sentiments and topics that appear in the reviews of Akulaku, Kredivo, and EasyCash lending apps on the Google Play Store. Using text mining techniques, VADER sentiment analysis, and LDA topic modeling, this research reveals dominant positive sentiments related to ease of use, service speed, and customer support. However, there were also negative reviews regarding loan application difficulties, technical issues, and bad experiences with billing and payments. This research provides valuable insights into the preferences and concerns of pinjol users, which can serve as a reference for service providers to improve the quality of their products and services.
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