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All Journal Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal Teknik Informatika (JUTIF) Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Eduvest - Journal of Universal Studies SATIN - Sains dan Teknologi Informasi PADIMAS: Jurnal Pengabdian Masyarakat International Journal of Informatics and Computing

Haerani, Erna

Siliwangi University, Tasikmalaya, Indonesia

Author-ID : 2138780

Aerospace Engineering Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Medicine & Pharmacology Neuroscience Social Sciences Other

Published : 8 Documents Claim Missing Document

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Articles

Finding Customer Patterns Using FP-Growth Algorithm for Product Design Layout Decision Support Erna Haerani; Christina Juliane
Sistemasi: Jurnal Sistem Informasi Vol 11, No 2 (2022): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

The transaction database contains a very large and irregular dataset that requires another mechanism to read it, even though there is a lot of new knowledge that can be revealed, including associations or relationships between goods or products that are often purchased by customers. The new finding of the relationship between these variables is usually called association rule mining. The algorithm that is developing and often used is frequent pattern-growth (FP-Growth). The problem of very many transaction databases also occurred in Mr. A. So, in this research, we will look for customer patterns using the FP-Growth algorithm. The algorithm aims to find the maximum frequent itemset. The frequent itemset will be generated into associative rules so that it becomes valuable new knowledge. This knowledge can be used as a reference and consideration in making decisions. The FP-Growth algorithm will be implemented using the rapidminer tools on the transaction data of Mr.A's goods sales. The pattern of rules that will be searched for is based on data on sales of goods transactions. The results of the study obtained six association rules with five conclusions being the gift category. So that the suggestion for decision making is to lay out items close to and around the gift category in order to improve marketing and service strategies in order to attract the attention and interest of pointers in making purchases of goods.

Chatbot for Diagnosis of Pregnancy Disorders using Artificial Intelligence Markup Language (AIML) Alam Rahmatulloh; Anjar Ginanjar; Irfan Darmawan; Neng Ika Kurniati; Erna Haerani
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1595

Artificial Intelligence has evolved in sophistication and widespread use. This study aims to create a chatbot application in the health sector regarding the early diagnosis of pregnancy disorders. Based on basic health research, only 44 percent of pregnant women know the danger signs of pregnancy. The chatbot application developed is expected to facilitate and increase knowledge for pregnant women about the danger signs of pregnancy, especially early diagnosis of pregnancy disorders. The chatbot application was developed with artificial intelligence technology based on Artificial Intelligence Markup Language with the question-answer concept using the Pandorabots framework. The test is carried out in two stages: functional and pattern matching. The functional testing uses the black-box testing method, and the pattern-matching test on the chatbot uses the sentence similarity and bigram methods based on user input and keywords similarity in the bot's knowledge base. The functional testing results show that the chatbot application runs well, with the eligibility criteria reaching 81.4% and the results of the keyword similarity test (pattern matching) are zero to one, in the sense that the value of one has the same similarity between user input and pattern. Meanwhile, the zero value has no similarities, so the bot will respond to it as free input. So it can be concluded that the bot can respond to user questions when the pattern and input have the same level of similarity.

The Implementation Of The Care-Protect (Pedulilindungi) Application: The Economic Impact And Constraints Faced Franciskus Antonius Alijoyo; Erna Haerani
Eduvest - Journal of Universal Studies Vol. 2 No. 1 (2022): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

The COVID-19 pandemic has harmed the global economy. This is due to the imposition of restrictions on social activities, which have a negative impact on employment and subsequently harm people's income and purchasing power. For this reason, the government has issued Care-Protect (PeduliLindungi) application, which functions to ensure that everyone active outside the house has been vaccinated and is free from the virus. This study aims to analyze the impact of the implementation of the PeduliLindungi application on community and economic activities in Indonesia and the obstacles faced in its implementation. This research was carried out by following a systematic literature review research method. The data were collected from previous studies that examined the enforcement of PeduliLindungi applications. The data were collected from the research results in articles published in Sinta indexed journals. The collected data is then analyzed using an interactive data analysis model. The results of this study indicate that the PeduliLindungi application has some impacts on the people's economy in Indonesia. In addition, this research also identifies several obstacles faced by the community and the government in implementing the PeduliLindungi application. Detailed results regarding the positive and negative impacts and constraints are discussed in this article, and some suggestions based on the findings are also presented.

Analisis User Experience Aplikasi Peduli Lindungi untuk Menunjang Proses Bisnis Berkelanjutan Erna Haerani; Alam Rahmatulloh
SATIN - Sains dan Teknologi Informasi Vol 7 No 2 (2021): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Pandemi ini sangat berdampak banyak hampir keseluhur sektor. Pemerintah terus berusaha menekan penyebaran coronavirus diantaranya dengan menerapkan aplikasi PeduliLindungi. Aplikasi tersebut dikembangkan untuk membantu dalam melakukan pelacakan. Pelacakan dan fitur-fitur lainnya mulai dipergunakan di sarana prasarana umum seperti di bandara, termasuk hasil tes swab PCR maupun antigen sudah mampu diintegrasikan dengan aplikasi tersebut. Selain itu digunakan untuk masuk dan check-in ke berbagai tempat umum seperti mall. Walaupun sudah banyak penggunaan dan integrasi pada aplikasi Peduli Lindungi, namun belum diketahui tingkat penerimaan di masyarakat. Diharapkan dengan penerapan aplikasi tersebut proses bisnis yang terhenti disemua sektor dapat kembali beroperasi. Maka untuk membantu pemerintah dalam melancarkan tujuannya mengembalikan proses bisnis yang terhenti dampak pandemi. Perlu dilakukan analisa aplikasi pedulilindungi dari segi pengalaman pengguna. Analisis menggunakan tools user experience questionnaire (UEQ). UEQ terdiri dari 26 butir pertanyaan. Hasil penelitian dari enam skala: daya tarik, kejelasan, efisiensi, ketepatan, stimulasi dan kebaruan masih menghasilkan nilai yang sangat rendah. Terutama pada skala ketepatan dengan nilai buruk.

Optimizing Data Management in Web Applications through Google Drive API Integration and Synchronization Putri Septia Amalia; Erna Haerani; Rusnida Romli; Trisna Ari Roshinta
JICO: International Journal of Informatics and Computing Vol. 1 No. 1 (2025): May 2025
Publisher : IAICO

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

The rise of Web-based applications has created a demand for streamlined data management and automatic data synchronization. Even manually stored local data is often insufficient to meet these requirements, necessitating a solution that can efficiently manage data access and storage through Cloud technology. This study advocates for utilizing the Google Drive API to resolve these issues. By leveraging the benefits of Google Drive's Cloud storage, Web applications can seamlessly synchronize user-uploaded data to the Cloud. To initiate this integration, a Google account is required to authenticate the process and serve as a mediator for data exchange. This approach employs secure authentication and authorization mechanisms to ensure data privacy. The system is developed using an iteration-based approach starting with user requirements analysis, followed by interface design and API integration. Pilot tests were then conducted to validate system performance under various usage scenarios. The findings revealed a noteworthy advancement in the synchronization and administration of data through the Web-based application with a data transmission duration of under 60 seconds, contingent on internet speed. Google Drive's API integration enables users to access files and manage them in real-time, surpassing prior limitations. To meet the demands of progressively intricate Web-based applications, future research can concentrate on enhancing data security and optimizing performance.

Bidirectional Encoder Representations from Transformers Fine-Tuning for Sentiment Classification of Cek Bansos Reviews Haerani, Erna; Rahmatulloh, Alam; Elmeftahi, Souhayla
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 4 No. 1 (2025): March 2025
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v4i1.4981

Social assistance programs are essential government initiatives aimed at supporting underprivileged communities. One such program is facilitated through the Cek Bansos application, which enables users to check their eligibility for social aid. However, user experiences with the application vary, leading to various sentiments in their reviews. Understanding these sentiments is crucial for improving the application’s functionality and user satisfaction. This study focuses on sentiment analysis of user reviews of the Cek Bansos application by leveraging a fine-tuned Indonesian-language Bidirectional Encoder Representations from Transformers (BERT) model. This research aims to evaluate the BERT model's effectiveness in classifying sentiments in user reviews and provide insights that could improve the Cek Bansos application. This research method is the BERT model was fine-tuned using hyperparameters such as a learning rate of 3e-6, batch size of 16, and 9 epochs. The dataset consisted of 8,000 reviews, divided into training (70%), validation (20.1%), and test (9.9%) sets. Review scores were manually categorized, where ratings of 1 to 2 were classified as negative sentiment, 3 as neutral, and 4 to 5 as positive. The results of this research are as follows: the fine-tuned model achieved an accuracy of 77%, with additional evaluation metrics such as precision, recall, and F1 score, demonstrating the model's effectiveness in identifying positive, negative, and neutral sentiments separately. This study concludes that the BERT model provides a reliable method for sentiment classification of user reviews, which could support developers and policymakers in refining the Cek Bansos application to enhance user experience. Additionally, a web-based application developed using Streamlit allows government officials to visualize sentiment trends in real time, improving their understanding of user feedback. Future research could further explore alternative machine learning models and additional linguistic features to improve sentiment classification accuracy and the overall user experience.

MAnTra: A Transformer-Based Approach for Malware Anomaly Detection in Network Traffic Classification Rizal, Randi; Darmawan, Muhamad Aditya; Selamat, Siti Rahayu; Rahmatulloh, Alam; Haerani, Erna; Tarempa, Genta Nazwar
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.5462

Cybersecurity is a critical priority in the ever-evolving digital era, particularly with the emergence of increasingly sophisticated and difficult to detect malware. Traditional detection techniques, such as static and dynamic analysis, are often limited in their ability to recognize novel and concealed malware that poses a threat to security systems. Consequently, this study investigates the potential of Transformer models for network traffic classification to detect anomalies associated with malware activity. The proposed approach emphasizes retrospective analysis, wherein the model is evaluated across various platforms and datasets encompassing different virus variants. By incorporating diverse types of malwares into the training data, the model is better equipped to identify a range of attack patterns. The Transformer model employed in this study was trained over 30 epochs. The evaluation results demonstrated excellent performance, achieving a training accuracy of 99.16% and a test accuracy of 99.32%. The very low average loss value of 0.01 indicates that the model effectively reduces classification errors. These findings underscore the potential of Transformer models as an efficient method for malware detection, offering greater accuracy and speed compared to traditional approaches. The results further reveal that the Transformer exhibits strong capabilities in handling sequential data, which is highly relevant to the dynamic nature of network traffic. For future research, it is recommended to explore the scalability of this method in larger network environments and assess its effectiveness in real-time detection scenarios. Expanding its application could establish the Transformer model as a more reliable and efficient solution for identifying evolving malware threats, thereby enhancing overall network security. This approach presents a robust framework for protecting systems and data against increasingly complex cyber threats.

PELATIHAN TEKNOLOGI ROBOTIKA BAGI GURU DAN SISWA SEKOLAH DASAR : TRAINING OF ROBOTICS TECHNOLOGY FOR ELEMENTARY SCHOOL TEACHERS AND STUDENTS Rohmat Gunawan; Alam Rahmatulloh; Randi Rizal; Perdi Setiawan; Erna Haerani
PADIMAS Jurnal Pengabdian Masyarakat Vol. 4 No. 02 (2025): Padimas (Jurnal Pengabdian Masyarakat)
Publisher : PADIMAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/padimas.v4i02.5624

Pembelajaran teknologi informasi dan rancang bangun perangkat elektronik di setiap jenjang pendidikan masih terbatas di beberapa sekolah tertentu saja. Penggunaan robot edukasi dalam sektor pendidikan masih sangat minim, terutama pada jenjang Sekolah Dasar (SD). Padahal, minat peserta didik terhadap bidang ini semakin meningkat, ditandai semakin banyaknya kontes robotika di daerah maupun skala nasional. Mengenalkan teknologi robot sejak dini, dapat mendorong anak untuk berpikir logis, belajar menganalisis masalah, belajar dari setiap kesalahan, mengenal Science Technology Engineering Mathematics (STEM), serta mendorong anak untuk berpikir kreatif. Tujuan dari kegiatan pengabdian ini melakukan sosialisasi teknologi informasi dan rancang bangun komponen eleketronik (khususnya komponen penyusun robot). Terdapat 3 aktivitas utama yang dilakukan dalam kegiatan pengabdian ini, diantaranya: persiapan awal, pelaksanaan, evaluasi dan pelaporan. Kegiatan pengabdian masyarakat telah dilaksanakan pada hari Jumat 8 Agustus 2025 dimulai pukul 08:00 sampai dengan selesai, diikuti oleh guru dan 35 siswa kelas VI Sekolah Dasar Negeri (SDN) Citapen Kota Tasikmalaya, yang berlokasi di Jalan Tentara Pelajar No. 16 Kelurahan Empangsari Kecamatan Tawang Kota Tasikmalaya Jawa Barat. Hasil evaluasi responden terhadap kegiatan pengabdian ini, rata-rata kategori “Sangat Setuju”=64%, “Setuju”=32%, “Netral”=4%, “Tidak Setuju”=0%, “Sangat Tidak Setuju”=0%.

Co-Authors Alam Rahmatulloh Anjar Ginanjar Christina Juliane Darmawan, Muhamad Aditya Elmeftahi, Souhayla Franciskus Antonius Alijoyo Genta Nazwar Tarempa Irfan Darmawan Neng Ika Kurniati Perdi Setiawan Putri Septia Amalia Randi Rizal Rizal, Randi Rohmat Gunawan Rusnida Romli Selamat, Siti Rahayu Trisna Ari Roshinta

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