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All Journal Jurnal Algoritma JMM (Jurnal Masyarakat Mandiri) Journal of Community Development Jurnal PkM MIFTEK Jurnal Algoritma Journal of Digital Literacy and Volunteering Indonesian Journal of Computer Science and Engineering Journal of Digital Literacy and Volunteering
Rinda Cahyana
Sekolah Tinggi Teknologi Garut
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Nursing Public Health Social Sciences Other

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Journal : Jurnal Algoritma

 1 
Analisis Sentimen Layanan Sistem Informasi Akademik Mahasiswa Menggunakan Algoritma Naive Bayes Hidayat, Taupik; Cahyana, Rinda; Julianto, Indri Tri
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1514

Abstract

AISnet For Students is an academic information system built by the Garut Institute of Technology to make it easier for students to carry out various campus academic administration activities online. This research aims to conduct sentiment analysis of online academic services at the Garut Institute of Technology by involving students as research subjects. This sentiment analysis will be carried out using the Naive Bayes Algorithm to explore student views and opinions regarding these academic services. This research was conducted with the aim of identifying potential problems that may occur in online academic services at the Garut Institute of Technology. Apart from that, this research also aims to provide recommendations that can help in improving the quality of these services. Research shows that students have positive sentiments towards academic services on campus. However, there are several problems that need to be overcome, such as technical problems and lack of features in the system. The solution to overcome this problem is to develop a user-friendly system, improve network quality, improve system features, conduct training or socialize the use of the system to students, and apply the latest technology and innovation in online student academic system services. The results of this research have the potential to provide benefits to educational institutions by helping to improve online academic services better. The results are expected to increase satisfaction and quality of services provided to students. Apart from that, this research can also be a reference or reference for further research related to sentiment analysis in the academic field or other fields. Where the Naive Bayes algorithm is used to analyze student sentiment towards academic services on the Garut Institute of Technology campus. The final results show that negative sentiment is greater than positive sentiment. Where negative sentiment is 54.75% and positive sentiment is 45.24%, this is because in the AISNet application most users provide reviews for the updates which are not real time. The following is the final result with an accuracy of 80.06%, a resolution of 83, 11 and recall 75.21.
Rancang Bangun Sistem Monitoring Kinerja Karyawan dan Penggajian Karyawan Konveksi berbasis web : Studi Kasus: FPN Collections Alawiyah, Dini; Cahyana, Rinda
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.1818

Abstract

Employee performance is a crucial factor in a company's success, especially in the convection industry which relies on labor productivity. Therefore, an effective performance monitoring and payroll system is indispensable to ensure fairness of compensation and improve employee motivation and productivity. Payroll in a convection company includes not only basic salary, but also bonuses, overtime, and deductions, which require transparent and accurate management.This research aims to develop a web-based system that integrates performance monitoring and employee payroll in a convection company. The method used is prototyping with five stages: communication, quick plan, modeling quick design, construction of prototype, and deployment delivery & feedback. Data Flow Diagram (DFD) is used for system design, while testing is done using the black box testing method.The results showed that this system can improve efficiency in performance monitoring and payroll management. The test resulted in a success rate of 87.6%, which is categorized as very good.
Penerapan Metode Customer Satisfaction Index dalam Sistem Pelaporan Masalah untuk Mengungkap Emosi Pelanggan Hidayat, Achmad Lutfi; Cahyana, Rinda; Fatimah, Dini Destiani Siti
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.20-2.1237

Abstract

Reporting or complaints are communications made to convey conditions that can be used for consideration in making decisions about services. Drinking Water Services (PAM) is managed by the Mekarwangi Village Owned Enterprise. When a problem occurs with the service, the customer must make a report to the officer by coming directly to the BUMDes office, which sometimes records the complaint being lost so it is not conveyed to the technician and results in the problem report not being handled immediately. . Based on these problems, the aim of this research is to build a Village PAM problem reporting system so that customers can report directly their complaints, so that the Rational Unified Process (RUP) methodology is the choice which has Inception, Elaboration and Construction stages, while for modeling Unified Modeling is implemented Language (UML) and black box testing as system testing. The results of this research were successful in developing a web-based system by applying the Customer Satisfaction Index method to the problem reporting system to reveal customer expressions. Knowing the customer's condition can help PAM Desa to immediately handle problems, so that service quality can be maintained and the service provided meets customer expectations. The problem reporting service system can run well based on the results of the functional suitability calculation which obtains a percentage value of 100%, or in the sense that it meets the criteria.
Rancang Bangun Sistem Pemetaan Kesenian Garut Berbasis Web Nuraisah, Siti; Cahyana, Rinda
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.1821

Abstract

Distinctive arts and local community culture as cultural heritage inherited from generation to generation, traditional art is present as a window to the local wisdom of ancestors, this art has various forms such as dance, music, theater, fine arts, to literature. The Garut Regency Culture and Tourism Office stated that traditional art information facilities still use book media, the renewal of this information system aims to map the arts in Garut Regency which is still considered ineffective for this digital era. Furthermore, the purpose of this research is to produce a web-based Garut Traditional Arts mapping system. In analyzing and designing this mapping system, the Rational Unified Process (RUP) method is used with several stages, namely Inception, Elaboration, Construction, Transition and for modeling using Unified Modelling Langguange (UML). The system was tested using the blackbox testing method. The Garut art location mapping system by applying Leaflet to display traditional art locations. This research results in a Garut art mapping system that can provide information on locations, facilities and activities as promotional media.
Aplikasi Pengingat Minum Obat Dengan Monitoring Tenaga Kesehatan Berbasis Mobile Menggunakan Metode Prototype Firdaus Al Anwari, M Riadi; Nuraeni, Fitri; Cahyana, Rinda; Fitriani, Leni; Setiawan, Ridwan; Septiana, Yosep
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2580

Abstract

The process of administering medication to patients requires timeliness and consistency to ensure optimal therapeutic outcomes. In practice, many patients struggle to remember their medication schedules, particularly when treatment extends over a long period. Addressing this issue, the present study aims to develop an Android-based medication reminder application that assists patients in adhering to their treatment schedules while enabling healthcare providers to digitally monitor patient activity. The application was designed using a prototyping method, which emphasizes iterative system development based on user feedback. The development process was conducted in two phases. The first phase involved initial design and testing of core features, such as reminder notifications and patient medication intake reporting forms. The second phase focused on improvements based on user feedback, particularly the addition of a disease information feature that provides educational content about patient diagnoses following checkups, such as hypertension and tuberculosis. Testing was carried out using a black-box testing approach to ensure proper functionality, alongside feedback collection through interviews. The results showed that the application performed effectively; its features were usable by both patients and healthcare providers as intended, and the information displayed was considered helpful in enhancing patients’ understanding of their health conditions. Furthermore, the system contributed to improving patient adherence to medication regimens and facilitated continuous monitoring by healthcare providers.
Analisis Sentimen Ulasan Wisata Budaya Menggunakan Metode Support Vector Machine dan Long Short-Term Memory Ramdani, Rizki; Cahyana, Rinda
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2585

Abstract

In the era of digital transformation, tourist behavior in expressing perceptions of travel destinations has increasingly shifted toward online platforms such as Google Maps and Twitter. These digital reviews not only represent individual experiences but also reflect collective opinions that can serve as a foundation for formulating data-driven tourism development policies. This study aims to conduct sentiment analysis on public opinion regarding Kampung Naga by comparing the performance of two classification algorithms: Support Vector Machine (SVM) and Long Short-Term Memory (LSTM). The methodological approach employed is SEMMA (Sample, Explore, Modify, Model, Assess). The dataset comprises 2,469 reviews obtained through web scraping techniques from Google Maps and Twitter. All data underwent preprocessing stages including cleaning, tokenization, stopword removal, and automatic sentiment labeling using the ChatGPT language model, with three classification labels: positive, neutral, and negative. Modeling was performed using SVM with TF-IDF representation and LSTM with an embedding layer. Model evaluation utilized precision, recall, and F1-score metrics. The results indicate that SVM achieved an accuracy of 83% and performed best on neutral sentiment, while LSTM recorded an accuracy of 81% with stable performance on positive and neutral sentiments. This research contributes to the development of text-based public opinion analysis systems to support the promotion and management of cultural tourism destinations.
Analisis Sentimen Publik Pada Media Sosial Multi-Platform Terhadap Kinerja Presiden Prabowo Subianto Menggunakan Algoritma Naive Bayes Fauzi, Sandi Muhtar; Cahyana, Rinda
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2586

Abstract

In the rapidly evolving landscape of digital politics, a deep understanding of public sentiment on social media has become crucial due to its significant influence on public opinion. This study aims to analyze public sentiment toward the performance of President Prabowo Subianto by utilizing data from three popular social media platforms: Twitter, TikTok, and Instagram.The classification method employed is the Naïve Bayes algorithm, implemented within the SEMMA framework, which consists of five stages: Sample, Explore, Modify, Model, and Assess. Data from each platform was collected and processed through text cleaning, TF-IDF transformation, and class balancing using the SMOTE technique. Evaluation was conducted using Stratified K-Fold Cross Validation and the F1-score metric to assess model performance.The results indicate that classification performance varies across platforms. The model achieved the highest F1-score on Twitter data (0.82), followed by Instagram (0.72), and TikTok (0.68). Overall, the model reached an average accuracy of 75.41%. These findings suggest that the linguistic characteristics and text structures of each platform significantly affect sentiment classification effectiveness.This research provides practical implications for the application of AI-based sentiment analysis in the realm of digital politics. It offers actionable insights for policymakers to monitor public opinion in real time and for system developers to design sentiment analysis algorithms that are more adaptive to the unique characteristics of each platform.
Pemodelan Analisis Tren Topik Penelitian Sistem Informasi Menggunakan Latent Dirichlet Allocation Nursaadah, Siti; Cahyana, Rinda
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2596

Abstract

Topic modeling is one of the text mining techniques that can be used to explore research themes in a collection of scientific documents. This study aims to identify and compare topic trends in SINTA-indexed national journal publications with student articles published in the ITG Algorithm Journal in the field of informatics and computers. The research data consisted of article abstracts that were analyzed through text preprocessing and text representation using bag-of-words, then modeled using Latent Dirichlet Allocation (LDA). The optimal number of topics was determined based on the coherence score, visualized using pyLDAvis, and labeled with the help of ChatGPT to clarify the interpretation. The results show that national journals emphasize application and information system development, while the ITG Algorithm Journal tends to address cutting-edge issues such as machine learning and data science. These findings contribute to mapping the development of information system research and can serve as a reference for formulating research policy directions at the local and national levels.
Co-Authors ., Bunyamin Afrizal, Nabil Nur Al Sidqi, Muhammad Affan Alawiyah, Dini Angga Kusumah, Angga Asep Nurzaman Asri Mulyani Asyah, Cha Cha Nisya Bajuri, Ahmad Dede Kurniadi Dewi Tresnawati Dianto, Fajar Eri Dimitri Mahayana Dini Destiani Siti Fatimah Eri Satria Fathonah, Trisma Nur Fauzi, Sandi Muhtar Firdaus Al Anwari, M Riadi Fitri Nuraeni Hidayat, Achmad Lutfi Hilmi Aulawi Indri Tri Julianto Latifah, Ayu Leni Fitriani, Leni Luthfi Nurwandi Muhammad Rikza Nashrulloh Muhammad Syauqi Mubarok, Muhammad Syauqi Nasrulloh, Muhammad Rikza Nurhidayanti, Shopi Ramadhan, Taopik Ramdani, Rizki Ridwan Setiawan Rodiansyah, Novan Rostilawati, Detila Santoso, Bambang Tri Siti Nuraisah, Siti Siti Nursaadah, Siti SRI RAHAYU Taupik Hidayat, Taupik Yosep Septiana Yudi Setiawan