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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JSAI (Journal Scientific and Applied Informatics)
Iryani, Lemi
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Computer Science & IT Engineering

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Combination of Image Enhancement and U-Net Architecture for Cervical Cell Semantic Segmentation Rudiansyah, Rudiansyah; Iryani, Lemi; Kesuma, Lucky Indra; Sari, Puspa; Alamsyah, Agung
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 2 (2024): Vol. 7 No. 2 (2024): Issues January 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i2.10399

Abstract

Cervical cancer is the second leading cause of death in women and ranks fourth as a disease that occurs in women worldwide. Cervical cancer is a disease that is difficult to detect and can be detected when it is in an advanced stage. This requires early prevention by carrying out a pap-smear examination. Pap-smear examination manually requires a relatively long time, so a tool is needed by segmentation. Segmentation is image processing by performing perfection between the intended object and the background. One of the CNN methods commonly used in medical image segmentation is the U-Net architecture. Segmentation in this study was carried out on the nucleus and cytoplasm of the Herlev dataset using the U-Net architecture combined with data augmentation and image enhancement. In the learning process, this research resulted in a fairly high IoU value of 78% and an RMSE close to 20%. The results of this study also yielded an accuracy value of 89%, with an average precision, recall and F1 score of 89%, 89% and 88.67%, respectively. This shows that the combination of the CNN U-Net architecture with image quality improvement and data augmentation is quite good at segmenting cervical cells for the nucleus and cytoplasm
Evaluasi Aplikasi Pemesanan Tiket Menggunakan Metode System Usability Scale (SUS) dan Model D&M IS Success Purba, Mariana; Dianing Asri, Sri; Noprisson, Handrie; Utami, Marissa; Iryani, Lemi
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6444

Abstract

Software product development not only focuses on features but also usability aspects. User experience is very important in the evaluation of reusability to understand the user's interaction with the product or system. Reusability factors include user satisfaction, efficiency, and effectiveness to achieve specific goals. The main purpose of this study is to evaluate the usability aspect of online ticket booking applications. This evaluation process is important to identify development and improvements to user views and application usage satisfaction. In this study, the object studied was an online travel booking application in Indonesia. The research instrument uses a quantitative and qualitative mixed-method approach. For the quantitative approach, the System Usability Scale (SUS) is used and as a basis for a qualitative approach, the D&M IS Success Model approach is used. Based on the evaluation results, there are several points that should be improved including the interface design should be simple, the reduction in the size of memory used by applications, features to communicate with customer service easily, data integration, and time notifications to complete payments.
Perancangan Aplikasi Manajemen Persediaan Barang di Perusahaan Pengelola Jaringan Akses Telekomunikasi Menggunakan Unified Modelling Language dan Prototyping Purba, Mariana; Dianing Asri, Sri; Ghufron, Akhmad; Umilizah , Nia; Iryani, Lemi
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6445

Abstract

Managing inventory in a telecommunications access network management company is very important because applications with good data management effectively increase the chances of success and maximize profits for the company. In addition, proper inventory data management is essential for identifying new market opportunities, forecasting risks, and understanding market trends. This study aims to clarify the design of inventory applications in accordance with the problems that exist at PT. XYZ is owned by the government as a case study location based on minimum service standards (SPM). This design uses unified modelling language (UML) such as use cases, activity diagrams, class diagrams and prototyping models to support the development of inventory applications in telecommunications access network management companies. The inventory management application in the telecommunication access network management company provides features for admins / users in processing supplier data, incoming goods data and outgoing goods data, and printing monthly reports on inventory of goods
Analysis of Travel Ticket Booking Application Services Based on Supporting Factors for Purchase Intention Purba, Mariana; Dianing Asri, Sri; Noprisson, Handrie; Utami, Marissa; Iryani, Lemi
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6446

Abstract

Aplikasi pemesanan tiket perjalnan ini harus memiliki kualitas dari segi perspektif produk agar dapat meningkatkan purchase intention oleh pengguna. Purchase intention dari layanan aplikasi dapat dilihat dari beberapa faktor antara lain usabilitas (usability), harga (price), kemudahan penggunaan (ease of use), complementarity dan hiburan (entertainment). Penelitian ini akan mengusulkan model penelitian untuk identifikasi kualitas layanan aplikasi online travel booking berdasarkan perspektif produk untuk meningkatkan purchase intention berdasarkan analisis dataset yang dikumpulkan dari sampel responden. Dari hasil pengumpulan data, dari total 1267 kuesioner yang dikumpulkan hanya memperoleh 1029 kuesioner yang valid. Model diuji menggunakan skor tingkat signifikan two-tails sebesar 0,05 untuk pengujian hipotesis. Menurut analisis data, faktor complementary memiliki pengaruh terbesar purchase intention dengan nilai uji-t sebsar 6,771. Selain itu, faktor entertainment memiliki pengaruh terbesar kedua dengan t-nilai 5.334. Faktor usability memiliki pengaruh terhadap purchase intention terbesar ketiga nilai uji-t 4.620. Faktor ease of use memiliki pengaruh terbesar keempat dengan nilai uji-t 3.641.
Classification of Text Datasets of Public Complaints Against the Government on Social Media Using Logistic Regression Purba, Mariana; Dianing Asri, Sri; Ayumi, Vina; Salamah, Umniy; Iryani, Lemi
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6447

Abstract

Di era teknologi saat ini, salah satu media sosial yang banyak digunakan dalam berinteraksi dan memberikan opini, pengaduan masyarakat, serta saran adalah Twitter. Dalam bidang pemerintahan, tweet yang mengandung opini atau pengaduan masyarakat terhadap suatu layanan atau program organisasi dapat digunakan sebagai umpan balik untuk memperbaiki atau meningkatkan kualitas layanan. Penelitian ini berfokus pada klasifikasi tweet untuk membedakan tweet yang tergolong pengaduan masyarakat atau non-pengaduan masyarakat dengan menerapkan algoritma pemelajaran mesin yaitu logistic regression (LR). Tahap dari penelitian ini antara lain crawling dan labeling dataset, pre-processing, pemodelan menggunakan classifier logistic regression, serta evaluasi kinerja classifier. Tahapan dalam penelitian ini seperti preprocessing, klasifikasi dan evaluasi dilakukan menggunakan bahasa pemrograman Python dengan bantuan scikit-learn library. Berdasarkan hasil eksperimen, model penelitian dengan menggunakan fitur ekstraksi CountVectorizer mencapai kinerja yang lebih baik daripada TfidfVectorizer. Eksperimen dengan menggunakan ekstraksi fitur TfidfVectorizer mencapai akurasi 92% (F1 score: 0.9181, precision: 0.9191 recall: 0.9181, kappa: 0.8363) sedangkan menggunakan akurasi CountVectorizer mencapai 94% (F1 score: 0.9355, precision: 0.9406, recall: 0.9356, kappa: 0.8715).
Co-Authors Alamsyah, Agung Ayumi, Vina Dianing Asri, Sri Ghufron, Akhmad Kesuma, Lucky Indra Noprisson, Handrie Purba, Mariana Puspa Sari, Puspa Rudiansyah Rudiansyah, Rudiansyah Salamah, Umniy Umilizah , Nia