Article Per Year (5 Year)
p-Index From 2021 - 2026
4.997
P-Index
This Author published in this journals
All Journal Jurnal Fitopatologi Indonesia Jurnal Agroteknos Sistemasi: Jurnal Sistem Informasi AL ISHLAH Jurnal Pendidikan Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Pengabdian Pada Masyarakat INOVTEK Polbeng - Seri Informatika Dinamisia: Jurnal Pengabdian Kepada Masyarakat MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Teknologi Dan Sistem Informasi Bisnis Zonasi: Jurnal Sistem Informasi Community Empowerment Journal Of Human And Education (JAHE) J-COSCIS : Journal of Computer Science Community Service CONSEN: Indonesian Journal of Community Services and Engagement Jurnal Teknologi Komputer dan Informasi Contributions of Central Research Institute for Agriculture GMPI Conference Series JURNAL KARYA ILMIAH MULTIDISIPLIN INOVTEK Polbeng - Seri Informatika
Lisnawita Lisnawita
Fakultas Ilmu Komputer, Universitas Lancang Kuning
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 55 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 55 Documents
Search

 2   3   4   5   6 
Importance Performance Analysis (IPA) of Patient Satisfaction with Fuzzy Logic at the Rumbai Maternity Clinic Costaner, Loneli; Lisnawita, Lisnawita; Guntoro, Guntoro
Sistemasi: Jurnal Sistem Informasi Vol 13, No 1 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i1.3527

Abstract

This study focuses on the level of patient satisfaction at the Rumbai Maternity Clinic. Quality of service is the main key that influences patient trust and satisfaction with this health facility. Therefore, the purpose of this study was to analyze patient satisfaction with the Importance Performance Analysis (IPA) method using fuzzy logic. This study will identify service attributes that are considered important by patients and evaluate the extent to which patient expectations have been met at the clinic. Attributes studied include cleanliness of facilities, courtesy of medical staff, availability of medicines, quality of medical services, information conveyed to patients, and others. The (IPA) method will help measure the level of importance and performance of each service attribute based on patient perceptions. Fuzzy logic is used to overcome the complexity and subjectivity of assessing patient satisfaction. The results of this study are expected to provide a comprehensive picture of patient perceptions and satisfaction at the Rumbai Maternity Clinic. Clinical management can use the results of this study to identify service improvement priorities and increase patient satisfaction. The scientific contribution of this research lies in combining the IPA method and fuzzy logic in the analysis of patient satisfaction. Thus, this research has the potential to help improve the quality of health services at the Rumbai Maternity Clinic and can be applied as a guide for developing similar methods in other health facilities.
Feature Extraction Analysis for Diabetic Retinopathy Detection Using Machine Learning Techniques Costaner, Loneli; Lisnawita, Lisnawita; Guntoro, Guntoro; Abdullah, Abdullah
Sistemasi: Jurnal Sistem Informasi Vol 13, No 5 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i5.4600

Abstract

Diabetic retinopathy is a serious complication of diabetes that can lead to blindness if not detected and treated early. Automated detection of diabetic retinopathy requires effective feature extraction techniques to enhance diagnostic accuracy. This study aims to develop a method for detecting diabetic retinopathy by utilizing Local Binary Pattern (LBP) combined with wavelet transform, and then classifying the extracted features using Support Vector Machine (SVM). The approach includes feature extraction from retinal images using LBP and wavelet transform. The extracted features are subsequently classified with SVM to evaluate performance in detecting diabetic retinopathy. Analysis results show that the dominant feature is found in the fifth row with a value of 0.57006, indicating the effectiveness of the LBP method in feature extraction. The developed model demonstrates high performance with an accuracy of 95.59%, precision of 96%, recall of 97.96%, and F1-score of 96.97%. The combination of feature extraction methods with SVM proves to be effective and reliable in detecting diabetic retinopathy, offering low error rates and high accuracy, thus potentially serving as a valuable tool in clinical diagnosis
Mendeley-Assisted PTK Writing Assistance for Teachers of SMKN 1 Mempura Siak: Pendampingan Penulisan PTK Berbantuan Mendeley Untuk Guru SMKN 1 Mempura Siak Lisnawita, Lisnawita; Asril , Elvira; Muzdalifah , Indah
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 5 (2024): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v8i5.16417

Abstract

Teachers are expected to be able to articulate creative ideas and research findings arising from diverse difficulties encountered in the field toimprove the quality of learning both within and outside the classroom. This document serves as a reference andunique requirementfor teachers managing promotions. However, many teachers struggle with writing scientific papers because one of the conditions for their promotion is to produce scientific papers that will be published in a journal. The purpose of this paper is to provide answers for teachers who are makingscientific papers. The Mendeley desktop application can help teachers compile references and bibliographies in article papers. This activitywas conductedat SMKN 1 Mempura. This activity is carried out through the use of theory and practice. The outcome of this activity was that the teacher responded positively, gained new knowledge about the Mendeley program, and earnedbenefits in writing PTK.It is evident from one of the teachers who was able to publish his scientific work in the Dinamisia Journal after participating in this PKM activity
Improving Digital Literacy to Prevent the Spread of Hoax News: Peningkatan Literasi Digital untuk Mencegah Penyebaran Berita Hoax Lisnawita, Lisnawita; Guntoro, Guntoro; Anggie Johar, Olivia; Costaner, Loneli
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 1 (2024): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v8i1.17275

Abstract

Perkembangan teknologi, khususnya internet, membawa dampak signifikan dengan memungkinkan penyebaran berita hoaks. Literasi digital menjadi penting, terutama bagi siswa aktif dalam internet dan media sosial. Penelitian ini menggunakan metode ceramah, kuesioner, dan penjelasan untuk meningkatkan literasi digital siswa dalam mengenali dan mencegah penyebaran berita palsu. Studi literatur menyoroti dampak negatif berita hoaks, terutama terkait isu SARA dan politik, di media sosial seperti Twitter dan Instagram. Masalah utama literasi digital di sekolah adalah kurangnya pengetahuan tentang program literasi digital. Pengabdian ini bertujuan memberikan landasan untuk meningkatkan kesadaran siswa terhadap penyebaran berita hoaks di era digital. Hasil evaluasi menunjukkan peningkatan pengetahuan peserta sebesar 69.78%, membuktikan bahwa pendekatan interaktif dan penerapan literasi digital dapat memberikan manfaat positif.
Optimizing Random Forest for IoT Cyberattack Detection using SMOTE: A Study on CIC-IoT2023 Dataset Guntoro, Guntoro; Lisnawita, Lisnawita; Costaner, Loneli
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 25 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v25i1.5382

Abstract

The growing number of Internet of Things devices has led to an increased risk of complex and diverse cyberattacks. However, a significant challenge in this domain is the imbalanced class distribution in most Internet of Things datasets, cautilizing classification algorithms to be biased towards the majority class, hindering effective threat detection. This study addresses this issue by leveraging the Random Forest algorithm optimised by the Synthetic Minority Oversampling Technique. This research aims to develop an effective model for detecting cyberattacks in Internet of Things environments by resolving class imbalance issues inside of the CIC-IoT2023 dataset. The methodology involves several stages, comprising data preprocessing and applying Synthetic Minority Oversampling Technique for data balancing. The balanced dataset was then used to train a Random Forest model, by its performance evaluated utilizing accuracy, precision, recall, F1-score, and Cohen's Kappa metrics. The results demonstrate the model's effectiveness, achieving an accuracy of 99.01%, an F1-score of 98.96%, and a Cohen's Kappa of 98.92%. This marks a notable improvement in performance, particularly in detecting minority classes, compared to the model trained devoid of Synthetic Minority Oversampling Technique, that struggled to identify several less common attack types. The outcomes suggest that combining Random Forest by Synthetic Minority Oversampling Technique can significantly enhance the development of intrusion detection systems by improving detection accuracy for all 33 attack types and reducing the risks associated by undetected threats. In conclusion, this study advances Internet of Things cybersecurity by presenting an effective and efficient method for addressing data imbalance in attack detection. Future research should focus on evaluating the model's robustness utilizing more complex datasets and enhancing its performance for real-time deployment on resource-constrained Internet of Things Devices.
Co-Authors Abdullah Abdullah AHMAD RAFIQI TANTAWI Ahmad Zamsuri, Ahmad Al-ghifari, Faza Anto Ariyanto Antonius Fernando Asma Alhusna Bambang HADISUTRISNO Budia Misri Costaner, Loneli Costaner Dafwen Toresa David Setiawan Desmawan, Wahyu Edriyansyah Elvira Asril, Elvira Evi Lianda Fajrizal Fajrizal, Fajrizal Fana Wiza, Fana Febi Yanto Fenty Widya Fuad Renadi GEDE SUASTIKA Guntoro Guntoro, Guntoro Hamidah Hanum Hartana, I Haryono Semangun Ikhsan Hidayat Irda Safni Jeni Wardi Johar, Olivia Anggie Keumala Anggraini Khairunnisa Lubis, Khairunnisa Latifa Siswati Loneli Costaner loneli costaner Lucky Lhaura Van FC Lucky Lhaura Van FC, Lucky Lhaura Mariza Devega Monika, Winda Monika Muhamad Sadar, Muhamad Musfawati Musfawati Musfawati Musfawati Musfawati Musfawati Mustika Mustika Muzdalifah , Indah Muzdalifah, Indah NABABAN, TRIWANTO Novisa Rahmadani novi Nugraha, Alif Nurhamin Nurhamin Pandu Pratama Putra, Pandu Pratama Panigoran, Abdullah Rezmia Febrina Ririn Sari Wati Rizky Octa Putri Charin Rometdo Muzawi, Rometdo RR. Ella Evrita Hestiandari Saragih, Wismaroh Sanniwati Sitepu, Suzanna Fitriani Supramana Susi Handayani Sutejo Sutejo Syafrika Deni Rizki, Syafrika Deni Tantawi, A. Rafiqi Toresa, Dafwen Yogi Yunefri, Yogi