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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 ARBITRASE: JOURNAL OF ECONOMICS AND ACCOUNTING 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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Review Analysis of SatuSehat Application Using Support Vector Machine and Latent Dirichlet Allocation Modeling Fahru Roji, Fikri; Gia Ginasta, Nava; Cahyan, Yayan; Rahayu, Dinar; Ramdani, Dendi
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

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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 Gia Ginasta, Nava; Krisnawanti; Fahru Roji, Fikri
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 Sabilul Muminin, Riyad; Ramdani, Dendi; Fahru Roji, Fikri
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 Fahru Roji, Fikri; Ariesti Anggraeni, Windi; Sabilul Muminin, Riyad; Ramdani, Dendi; Cahyan, Yayan
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.
Loyalitas Pengguna Aplikasi MyTelkomsel: Determinasi Kepuasan dan Kepercayaan Berbasis Customer Lifetime Value (CLV) Rendi Eka Herlinton; Rohimat Nurhasan; Fikri Fahru Roji
ARBITRASE: Journal of Economics and Accounting Vol. 6 No. 1 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/arbitrase.v6i1.2544

Abstract

This study aims to examine the influence of satisfaction and trust on Customer Lifetime Value (CLV) among users of the MyTelkomsel application. The research is motivated by the low level of user loyalty, despite the company’s efforts to introduce various digital features designed to enhance customer engagement. In the face of increasingly competitive digital service markets, understanding the key drivers of loyalty is essential. Employing a quantitative approach with an explanatory design, the study involved 100 purposively selected active users of the application. Data were collected through an online questionnaire using a four-point Likert scale and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that both satisfaction and trust have a significant positive effect on CLV, highlighting the importance of delivering a pleasant user experience and maintaining trust in the application's reliability to foster long-term loyalty. This research contributes to the theoretical framework of value-based loyalty and offers practical implications for telecommunications companies in developing adaptive relational marketing strategies in the digital era.
PEMILIHAN PROGRAM AFFILIATE MENGGUNAKAN PERSPEKTIF ANALYTICAL HIERARCHY PROCESS Almaiddah, Syinta; Kusmiati, Eti; Roji, Fikri Fahru
Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA) Vol 9 No 1 (2025): Edisi Januari - April 2025
Publisher : LPPM STIE Muhammadiah Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31955/mea.v9i1.4943

Abstract

Penelitian ini bertujuan untuk menganalisis faktor-faktor yang memengaruhi keputusan affiliator dalam memilih program affiliate pada platform Shopee dan Tik-Tok di Indonesia. Fokus penelitian ini adalah pada tiga kriteria utama: insentif finansial, sistem pembayaran, dan kemudahan penggunaan. Metode yang digunakan dalam penelitian ini adalah kuantitatif dengan pendekatan komparatif, di mana data dikumpulkan melalui kuesioner yang disebarkan kepada 100 responden yang merupakan affiliator di kedua platform tersebut. Teknik analisis data yang digunakan adalah Analytical Hierarchy Process (AHP) dengan bantuan perangkat lunak Expert Choice untuk menentukan prioritas kriteria yang mempengaruhi keputusan affiliator. Hasil penelitian menunjukkan bahwa insentif finansial, khususnya komisi dan bonus, menjadi faktor dominan dalam memilih program affiliate, diikuti oleh sistem pembayaran yang cepat dan aman, serta kemudahan penggunaan platform. Penelitian ini memberikan implikasi praktis bagi perusahaan dalam merancang dan meningkatkan program affiliate mereka, dengan fokus pada peningkatan insentif, sistem pembayaran yang efisien, dan kemudahan penggunaan platform. Penelitian ini juga menemukan bahwa platform yang menawarkan insentif yang lebih besar dan kemudahan dalam transaksi lebih menarik bagi affiliator.
PERAN PENERAPAN MODEL UTAUT (UNITED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY) PADA UMKM COFFEESHOP PENGGUNA GOFOOD DI KOTA GARUT Lestari, Suci; Nurhasan, Rohimat; Roji, Fikri Fahru
Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA) Vol 9 No 1 (2025): Edisi Januari - April 2025
Publisher : LPPM STIE Muhammadiah Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31955/mea.v9i1.4991

Abstract

Kemajuan teknologi, khususnya dalam era ekonomi digital, UMKM perlu menyesuaikan diri dengan perubahan yang terjadi. Salah satunya adalah pemanfaatan platform digital seperti Gofood, yang telah terbukti membantu meningkatkan pendapatan UMKM. Penelitian ini bertujuan untuk menganalisis berbagai faktor yang memengaruhi penerimaan dan penggunaan platform Gofood oleh UMKM CoffeeShop di Kota Garut melalui penerapan model UTAUT (Unified Theory of Acceptance and Use of Technology). Pendekatan kuantitatif dengan metode asosiatif digunakan dalam penelitian ini, melibatkan 35 Coffeeshop yang telah memanfaatkan Gofood. Data dikumpulkan melalui kuesioner berbasis Skala Likert serta dianalisis menggunakan teknik PLS-SEM. Temuan penelitian ini mengungkapkan bahwa Effort Expectancy dan Facilitating Conditions memiliki pengaruh positif terhadap Behavior Intention dan Use Behavior. Sebaliknya, Performance Expectancy dan Social Influence tidak menunjukkan pengaruh. Selain itu, Behavior Intention terbukti berpengaruh terhadap Use Behavior. Temuan ini memberikan wawasan bagi pengembang platform digital untuk lebih fokus pada aspek kemudahan penggunaan, dukungan teknis, dan aksesibilitas, dibandingkan dengan pengaruh sosial atau ekspektasi kinerja.
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 Novianti, Dea Nurmastin; Shiddieq, Diqy Fakhrun; Roji, Fikri Fahru; Susilawati, Wati
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) Puspita, Evi; Shiddieq, Diqy Fakhrun; Roji, Fikri Fahru
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 Fakhrun Shiddieq, Diqy; Roji, Fikri Fahru; Wufron, Wufron; Bekti, Surya Garian
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.
Co-Authors AA Sudharmawan, AA Abdi Ilahi, Pyar Abdul Latip, Abdul Alkautsar, Muslim Almaiddah, Syinta Anggraeni, Windi Ariesti Apriliya Nuraini, Raden Putri Ardiani, Kamila Syifa Arifah Nursadrina, Raisya Asri Mulyani Bekti, Surya Garian Cahyan, Yayan Dede Hendrik Dendi Ramdani Dewi Tresnawati Dinar Rahayu Dinar Rahayu Diqy Fakhrun Shiddieq Eri Satria Fakhrun Shiddieq, Diqy Fatimah, Nyinyi Ferdian Imawan Ghaida Farisya Gia Ginasta, Nava Hasbi S, Muhamad Hendrik, Dede Indri Tri Julianto Insani, Aura Krisnawanti Kusmiati, Eti Lusiana Nur Safitri Marchella, Amanda Mega Silvia Moch. Rizky Cahyadiputra Muslim Alkautsar Nava Gia Ginasta Novianti, Dea Nurmastin Nurhasan, Rohimat Permatasari, Rd Intan Puspita, Evi Putri Sukmana, Reinta Rahayu, Dinar Rahma Dianti, Ahrami Rahmawati . Ramdan, Galih Muhammad Rendi Eka Herlinton Ridian Gusdiana Ridwan Fauzi, Muhamad Ridwan Setiawan Ridwan Setiawan Rizkia, Agnia Suci Rohanudin, Muhammad Sabda Ilahi, Perceka Sabilul Muminin, Riyad Sabrina, Siti Sarah Salamah, Susi Salamatuddaroen, Intan Salman Fariz SALSABILA, ANNISA Shiddied, Diqy Fahrun Shiddieq , Diqy Fakhrun Shiddieq, Diqy Fakhrun Siti Nurhasanah Suci Lestari Susilawati , Wati Taofiqurrohman, Hendra Utami, Wulan Sri Wati Susilawati, Wati Wildan Hidayatul Hamdi Wufron Wufron Yaman Suryaman, Yaman