Article Per Year (5 Year)
p-Index From 2020 - 2025
0.983
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Jurnal INKOM Bulletin of Electrical Engineering and Informatics Teknologi Indonesia Computer Science and Information Technologies Infomans: Jurnal Ilmu-ilmu Informatika dan Manajemen BACA: Jurnal Dokumentasi dan Informasi
Wiwin Suwarningsih
Sekolah Teknik Elektro dan Informatika Institut Teknologi Bandung
Computer Science & IT Electrical & Electronics Engineering Engineering Library & Information Science

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
Generate fuzzy string-matching to build self attention on Indonesian medical-chatbot Suwarningsih, Wiwin; Nuryani, Nuryani
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp819-829

Abstract

Chatbot is a form of interactive conversation that requires quick and precise answers. The process of identifying answers to users’ questions involves string matching and handling incorrect spelling. Therefore, a system that can independently predict and correct letters is highly necessary. The approach used to address this issue is to enhance the fuzzy string-matching method by incorporating several features for self-attention. The combination of fuzzy string-matching methods employed includes Jaro Winkler distance + Levenshtein Damerau distance and Damerau Levenshtein + Rabin Carp. The reason for using this combination is their ability not only to match strings but also to correct word typing errors. This research contributes by developing a self-attention mechanism through a modified fuzzy string-matching model with enhanced word feature structures. The goal is to utilize this self-attention mechanism in constructing the Indonesian medical bidirectional encoder representations from transformers (IM-BERT). This will serve as a foundation for additional features to provide accurate answers in the Indonesian medical question and answer system, achieving an exact match of 85.7% and an F1-score of 87.6%.
Virtual assistant upper respiratory tract infection education based natural language Suwarningsih, Wiwin
Computer Science and Information Technologies Vol 2, No 3: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v2i3.p132-146

Abstract

The high incidence of upper respiratory tract infection (URTI) in Indonesia requires an efficient healthcare solution to maintain human wellbeing. The e-health education model proposed in this paper is a virtual assistant in the form of an interactive question and answer system assistant virtual interactive question answering (AVIQA) with a natural language approach. AVIQA is a form of problem-solving approach to design some aspects of education and consultation in helping parents to recognize symptoms and dealing with several preventive actions for toddlers when exposed to Upper Respiratory Tract Infection. The technologies proposed for the development of AVIQA include (i) Representation of sentence meanings to build an URTI knowledge base; (ii) Design of dialogue models for interactive consultation using a combination between information state and frame base model and (iii) Development of IQA based on casebase reasoning and semantic role labelling. The purpose of developing this technology is to achieve a system that is capable of assisting the users especially mothers in searching for information, reducing user time compared to reading a document, and providing a good advice for finding the right answers, which then can be constructed from a management model prototype information for the education and independent consultation for users. The final result of this study is e-health education system based Indonesian natural language that has an ability in terms of health consultations especially health of children under five in acute respiratory infection disease. This system is expected to have a significant impact on the ability of a mother to recognize symptoms and deal with children attacked by URTI.
Chili leaf segmentation using meta-learning for improved model accuracy Suwarningsih, Wiwin; Kirana, Rinda; Husnul Khotimah, Purnomo; Riswantini, Dianadewi; Fachrur Rozie, Andri; Nugraheni, Ekasari; Munandar, Devi; Arisal, Andria; Roufiq Ahmadi, Noor
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.7929

Abstract

Recognizing chili plant varieties through chili leaf image samples automatically at low costs represents an intriguing area of study. While maintaining and protecting the quality of chili plants is a priority, classifying leaf images captured randomly requires considerable effort. The quality of the captured leaf images significantly impacts the development of the model. This study applies a meta-learning approach to chili leaf image data, creating a dataset and classifying leaf images captured using mobile devices with varying camera specifications. The images were organized into 14 experimental groups to assess accuracy. The approach included 2-way and 3-way classification tasks, with 3-shot, 5-shot, and 10-shot learning scenarios, to analyze the influence of various chili leaf image factors and optimize the classification and segmentation model's accuracy. The findings demonstrate that a minimum of 10 shots from the meta-test dataset is sufficient to achieve an accuracy of 84.87% using 2-way classification meta-learning combined with the mix-up augmentation technique.
Kumpulan data citra telepon pintar untuk identifikasi varietas cabai merah berbasis daun Suwarningsih, Wiwin; Evandri, Evandri; Kirana, Rinda; Purnomo Husnul Khotimah; Dianadewi Riswantini; Ekasari Nugraheni; Andri Fachrur Rozie; Andria Arisal; Devi Munandar; Noor Roufiq Ahmadi
BACA: Jurnal Dokumentasi dan Informasi 2024: SPECIAL ISSUE - DATA IN BRIEF FOR REPOSITORI ILMIAH NASIONAL
Publisher : Direktorat Repositori, Multimedia, dan Penerbitan Ilmiah - Badan Riset dan Inovasi Nasional (BRIN Publishing)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/baca.2024.7786

Abstract

Chili plants played an important role in human life, serving as a source of income for farmers, as a provider of employment, and as a source of vitamins and minerals for the community. Market demand for red chili continued to increase, encouraging seed producers to provide quality plant seeds. The requirements for selecting plant varieties were based on market demand (taste, color, appearance, size, etc.), high productivity, resistance to plant pest attacks, and suitability for planting in local ecosystem conditions. Based on this, a smart approach was needed to identify plant varieties to maintain seed purity. To facilitate and streamline leaf-based chili variety identification, a comprehensive dataset was compiled. This dataset, consisting of 3877 leaf images divided into 12 variety classes, aimed to determine which plants were parent seeds or seeds that had deviations from their varieties. Leaf images were collected from the BALITSA garden through observations of leaf growth from shoots to 20 days of plant age. Various strict steps were taken to ensure the quality of the dataset and increase its usefulness. Chili leaf images taken from various angles and having high resolution were designed to assist in the development of highly accurate models. By leveraging this curated dataset, it was possible to train a model for real-time leaf-based identification of chili varieties, which significantly helped in the timely identification of such conditions.
Optimization of Information Security Standard Operating Procedures for The Academic Information System at Sebelas April University Hidayat, Eka; Prasetyo Utomo, Hadi; Suwarningsih, Wiwin
Infoman's : Jurnal Ilmu-ilmu Informatika dan Manajemen Vol. 19 No. 1 (2025): Infoman's
Publisher : LPPM & Fakultas Teknologi Informasi UNSAP

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

Abstract

The Academic Information System at Sebelas April University housed various essential data, including student information, faculty information, and academic records. These data were susceptible to cybersecurity threats, data breaches, and unauthorized access, potentially disrupting academic processes and tarnishing the university's reputation. This study aimed to enhance the security of UNSAP's Academic Information System by optimizing the Standard Operating Procedures for information security. A descriptive qualitative research method was employed to analyze the current information security conditions and formulate recommendations for improving the Standard Operating Procedures. The Octave Allegro approach and the ISO 27001:2022 standard served as frameworks in this study. The analysis revealed that the existing Standard Operating Procedures for information security were inadequate. Consequently, new, more comprehensive Standard Operating Procedures were developed, encompassing access control, data management, incident handling, and data backup. These new Standard Operating Procedures were expected to bolster the security of UNSAP's Academic Information System and assist UNSAP in complying with applicable information security standards.
Co-Authors Andri Fachrur Rozie Andria Arisal Andria Arisal, Andria Ayu Purwarianti Devi Munandar Devi Munandar, Devi Dianadewi Riswantini Ekasari Nugraheni Evandri, Evandri Fachrur Rozie, Andri Hidayat, Eka Husnul Khotimah, Purnomo Iping Supriana Noor Roufiq Ahmadi Nugraheni, Ekasari Nuryani Nuryani Prasetyo Utomo, Hadi Purnomo Husnul Khotimah Rinda Kirana Riswantini, Dianadewi Roufiq Ahmadi, Noor Suryawati, Endang Suryawati, Endang Suwartuti, Wiwik Wirahman, Taufiq Wulandari, Trida