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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Telematika : Jurnal Informatika dan Teknologi Informasi International Journal of Artificial Intelligence Research Jurnal Pilar Nusa Mandiri Jusikom: Jurnal Sistem Informasi Ilmu Komputer INTI Nusa Mandiri Jurnal Sistem Informasi Journal of Applied Data Sciences JUSTIN (Jurnal Sistem dan Teknologi Informasi) Journal of Hypermedia & Technology-Enhanced Learning
Nita Merlina, Nita
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Social Sciences Other

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PENERAPAN METODE STRAIGHT SELECTION PADA SISTEM PARKIR UNIVERSITAS BINA NUSANTARA Maharani, Mega; Merlina, Nita
Jurnal Pilar Nusa Mandiri Vol 10 No 1 (2014): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.6 KB) | DOI: 10.33480/pilar.v10i1.466

Abstract

The parking information System is designed to develop the current system that has been employed at BINA NUSANTARA University. Currently, the parking system is limited only recording the police number and they are still manually looking for the available parking area. The system implements a straight selection sorting data method, also known as the smallest number search method to determine the available parking location. The parking area will be automatically printed at a parking ticket, thus the driver could find it easily. This method also provides accurate data for building management about the available parking area and all data needed about the vehicles that parked at that area. This research is software based on web program using internet access.
PEMBANGUNAN MEDIA KONSULTASI PENYAKIT GIGI MENGGUNAKAN METODE DEMSPTER-SHAFER Saptorini, Ernest Dwi; Merlina, Nita
Jurnal Pilar Nusa Mandiri Vol 10 No 2 (2014): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Septemb
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1125.047 KB) | DOI: 10.33480/pilar.v10i2.477

Abstract

Media Consulting Dental Disease Using Dempster-Shafer Method. The expert system could serve as a consultant which would advise the user as well ass the assistant for the expert. One way to prevent and help to detect persons' level of risk dental disease, by making the anexpert system as a consultant media in order that could minimize the risk of serious illness or death resulting. Diagnostic result of dental disease expert system is equal with The Dempster-Shafer inference engine. The conclusion is an expert system has been built could be applied for dental disease diagnostic.
FAKTOR – FAKTOR YANG MEMPENGARUHI MUTU WEB TERHADAP KEPUASAN AKTIVITAS BELAJAR BAGI PENGGUNA WANITA Merlina, Nita; Frieyadie, Frieyadie
Jurnal Pilar Nusa Mandiri Vol 8 No 2 (2012): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Septembe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (416.802 KB)

Abstract

This study aims to determine the factors that affect the quality of the web to satisfaction of learning activities for female users. Final model obtained in this study approached the research UTAUT (Unified Theory Of Aceptual and Use Of Technology) with data analysis using Structural Equation Modelling (SEM) on the software Analysis of Moment Structure (AMOS) version 6.0, a causal relationship between these factors which affect the quality of web-user satisfaction for women adalahVariabel beajar Performance Expectancy effect on Symbolic Adoption means the higher the student achievement expectations tehadap the greater web of learning opportunities to receive an online learning web mentally, Variable Effort Expectancy effect on Attitude Toward Technology means the higher expectations tehadap student effort, the greater web of learning attitude to receive online learning web, Social Influence Variables no effect on the Attitude Toward Technology college student means that studying the web with online learning medium was not influenced by others but their own consciousness to be able to learn the web, Variable Faciliting Condition effect on Symbolic Adoption means the student will receive an online learning web fasilatas when supported by adequate, Variable Attitude Toward Technology effect on Symbolic Adoption means the better the level of technology acceptance more likely to receive an online learning web mentally.
SIMPEL: A Modernized System for Enhancing Efficiency in Plant Seed Import and Export Licensing Jessika Aryani Juniarti; Pratama, Kasahana Indra; Utami, Cheilla Cahya Utami; Merlina, Nita; Mayangky, Nissa Almira
Journal of Hypermedia & Technology-Enhanced Learning Vol. 1 No. 1 (2023): Journal of Hypermedia & Technology-Enhanced Learning—Digital Frontiers
Publisher : Sagamedia Teknologi Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58536/j-hytel.v1i1.29

Abstract

In the era of globalization, PT. XYZ recognizes the importance of developing a licensing system for exporting and importing plant seeds to modernize the current manual recording processes. The existing manual system results in low effectiveness and efficiency, queues during license application, repetitive verification processes, difficulty monitoring license applications, potential fraud between applicants and officials, inaccurate reports on license application outcomes, and negative environmental impacts due to excessive paper usage. This research aims to create the Plant Seed Export and Import Licensing Service Information System (SIMPEL) to enhance licensing services’ speed, accuracy, transparency, and accountability. The development method used is the waterfall method, employing the PHP programming language, Vue.Js as the Frontend framework, Laravel as the Backend, and PostgreSQL as the database. The significance of developing this system lies in the urgency for partner companies to improve operational efficiency and provide optimal licensing services. SIMPEL is designed as a web-based solution that facilitates businesses or applicants in submitting licensing applications online while also providing ease for officials in delivering optimal licensing services. Thus, this research aims to present an information technology solution that aligns with the demands of the times and supports the partner company’s development in adopting digital technology in its operational activities.
Improving Early Detection of Cervical Cancer Through Deep Learning-Based Pap Smear Image Classification Merlina, Nita; Prasetio, Arfhan; Zuniarti, Ida; Mayangky, Nissa Almira; Sulistyowati, Daning Nur; Aziz, Faruq
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.576

Abstract

Cervical cancer is one of the leading causes of death in women worldwide, making early detection of the disease crucial. This study proposes a deep learning-based approach that has the advantage of leveraging pre-trained models to save data, time, and computation to classify Pap smear images without relying on segmentation, which is traditionally required to isolate key morphological features. Instead, this method leverages deep learning to identify patterns directly from raw images, reducing preprocessing complexity while maintaining high accuracy. The dataset used in this study is a public data repository from Nusa Mandiri University (RepomedUNM), which has a wider variety of data. This dataset is used to classify images into four categories: Normal, LSIL, HSIL, and Koilocytes. The dataset consists of 400 images evenly distributed, ensuring class balance during training. Transfer learning is applied using five Convolutional Neural Network (CNN) architectures: ResNet152V2, InceptionV3, ResNet50V2, DenseNet201, and ConvNeXtBase. To prevent overfitting, techniques such as data augmentation, dropout regularization, and class weight adjustment are applied. The evaluation results in this study showed the highest accuracy with a value of ResNet152V2 = 0.9025, InceptionV3 = 0.8953 and DenseNet201 = 0.8845. ResNet152V2 excelled in extracting complex features, while InceptionV3 showed better computational efficiency. The study also highlighted the clinical impact of misclassification between Koilocytes and LSIL, which may affect diagnostic outcomes. Data augmentation techniques, including horizontal and vertical flipping and normalization, improved the model's generalization to a wide variety of images. Specificity was emphasized as a key evaluation metric to minimize false positives, which is important in medical diagnostics. The findings confirmed that transfer learning effectively overcomes the limitations of small datasets and improves the classification accuracy of pap smear images. This approach shows potential for integration into clinical workflows to enable automated and efficient cervical cancer detection.
IMPLEMENTATION OF FINITE STATE AUTOMATA ON THE DATE TO SEASON CONVERSION ENGINE BASED ON PRANATA MANGSA SEASON CALENDAR iboy, rahmat satria buana; Gata, Windu; Bayhaqy, Achmad; Sulaeman, Okky Robiana; Merlina, Nita
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 6 No. 1 (2022): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v6i1.2615

Abstract

The world is now starting the trend of going green or back to nature. The slogan goes green or back to nature can also be interpreted as living in harmony with nature. Our beloved country of Indonesia has implemented a harmonious life with nature, we can find it in the Javanese planting season calendar called Pranata Mangsa. In the pranata mangsa, we are taught the method of living in harmony, especially in an agricultural system. Harmony with nature means harmony between seasons, weather, living things, and types of plants. If everything is applied, there will be harmonization between all elements both from outside and inside so that additional elements such as chemical fertilizers and pesticides in agriculture, which essentially eliminate the harmonization of nature itself, are not needed. The implementation of Finite State Automata on the farming season calendar is expected to be able to educate and make it easier for farmers in particular and the Indonesian people, in general, to able to recognize the farming time and apply it to daily life. The final result of this research is the calendar system that can convert the date and month in the masehi calendar into the period or season of the pranata mangsa system. Key word : FSA, DFA, calendar, pranata mangsa, season
IMPROVING THE IMAGE OF A BANANA USING THE OPENING AND CLOSING METHOD Fauziah, Siti; Merlina, Nita; Mayangky, Nissa Almira; Hasan, Muhamad; Fahrurrozi4, Nabil Ali; Panjaitan, Yogi Yosua; Putra, Ananta Kusuma
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.5968

Abstract

One significant technique in image processing is morphological image operations, which include methods such as opening and closing. This research explores the application of the opening and closing methods in improving the quality of banana images. The Opening process effectively reduces noise and eliminates small, unwanted details, improving the clarity of the image. However, the Closing process presents some challenges, particularly in altering the natural texture of the banana and blurring fine lines. Careful adjustments are necessary to avoid reducing the visual quality of the image. The study begins with pre-processing steps such as image cleaning and contrast adjustment to enhance the image clarity. The Opening operation, using mathematical morphology and a structural element, removes unwanted small elements from the image, making fine lines and textures more visible for further analysis. The Closing operation, applied after Opening, fills small gaps and connects separated parts of the banana image, restoring the original structure and maintaining image continuity. The combined application of opening and closing methods significantly enhances the quality of banana images by improving clarity, preserving structural integrity, and optimizing overall visual appearance.
Improving the Efficiency of Water Meter Reading at Perumdam Tirta Kerta Raharja Using Microcontroller-Based Implementation of the YOLOv9 Method: Peningkatan Efisiensi Pembacaan Angka Meter Air Perumdam Tirta Kerta Raharja Berbasis Mikrokontroler dengan Penerapan Metode Yolov9 Putra, Septian Ade; Merlina, Nita
Telematika Vol 22 No 1 (2025): Edisi Februari 2025
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v22i1.14802

Abstract

Manual water meter reading remains a challenge for Perumdam Tirta Kerta Raharja due to its labor-intensive process, susceptibility to human errors, and inefficiency. This study aims to develop an automated water meter reading system using YOLOv9 and a microcontroller to improve efficiency and data accuracy. The model was trained using a dataset of water meter images under various lighting conditions and viewing angles. Evaluation results indicate that the 20-epoch configuration is the best model, achieving 99,91% accuracy, 91,16% average precision, and 91,04% average recall. The developed system successfully detects digits in real-time with high accuracy when deployed on a Raspberry Pi-based platform. However, the model still faces challenges in detecting the Background class. With further optimization, this system can be widely implemented to enhance operational efficiency in Perumdam and related industries.
PENERAPAN PSO UNTUK SENTIMEN ANALISIS PADA REVIEW MATA UANG KRIPTO MENGGUNAKAN METODE NAÏVE BAYES Merlina, Nita; Chandra, Ade; Mayangky, Nissa Almira
INTI Nusa Mandiri Vol. 18 No. 2 (2024): INTI Periode Februari 2024
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v18i2.4982

Abstract

In the digital age emerging currencies using digital technology called currency crypto money. Many people use cryptocurrencies to invest. This triggered the sentiment in society on social media twitter, there are positive opinions and there are negative opinions. The purpose of this study is to determine the public sentiment regarding the review of crypto currency and then classify it into two sentiments, namely positive and negative sentiments. The classifier method used is Naïve Bayes, Naïve Bayes is a good classifier method but has shortcomings in the selection of features therefore Particle Swarm Optimization (PSO) is applied as a feature selection in order to improve the accuracy value. After conducted experiments using Naïve Bayes method, obtain accuracy value of 66% with AUC 0.482 and after Applied Particle Swarm Optimization (PSO) as feature selection in Naïve Bayes obtain accuracy value of 85% with AUC 0.716 has increased accuracy .
VISUAL HISTORICAL DATA-BASED TRAFFIC MOVEMENT AND DENSITY PATTERN EXTRACTION FOR ADAPTIVE PATTERN DETECTION BASE ON VEHICLE TYPE Angellia, Filda; Merlina, Nita; Subekti, Agus; Handayanto, Rahmadya Trias
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1570

Abstract

Traffic congestion in urban areas has become a crucial issue, impacting time efficiency, energy consumption, and quality of life. One of the main causes of difficulties in traffic management is the lack of optimal predictive systems capable of detecting and adaptively responding to vehicle movement patterns. This study proposes a historical digital image-based approach to extract traffic movement patterns and density based on vehicle type and dimensions. The developed model utilizes historical traffic video footage from CCTV systems as a visual data source, which is then processed using the YOLOv5 algorithm to detect the number, size, and type of vehicles. After the detection process, vehicle information is converted into a sequential format that reflects vehicle movement in the temporal dimension. This data is then analyzed using a Long Short-Term Memory (LSTM) model to generate traffic density prediction patterns. This study also compares the performance of LSTM with other algorithms such as Random Forest and XGBoost in terms of prediction accuracy. Model evaluation is conducted using MSE and RMSE metrics to measure accuracy against actual data.The research results show that the integration of dimension-based vehicle detection with a visual historical data-driven prediction approach can improve the accuracy and flexibility of modeling future traffic conditions. This approach significantly contributes to the development of intelligent transportation systems that can adapt to dynamic environmental conditions and traffic patterns
Co-Authors Ade Chandra Agus Subekti Aziz, Faruq Bayhaqy, Achmad Ernest Dwi Saptorini, Ernest Dwi Fahrurrozi4, Nabil Ali Filda Angellia Fitri Rahmawati Frieyadie Gata, Windu Guntur Guntur Herlawati Herlawati iboy, rahmat satria buana Ida Zuniarti, Ida Jessika Aryani Juniarti Karnita Afnisari, Karnita Kurniawan, Setiadi Mayangky, Nissa Almira Mega Maharani, Mega Muhamad Hasan Mulyana, Kaka Nurmalasari Nurmalasari Nurul Aisyah Oktaviani, Nia Oktaviani, Nia Panjaitan, Yogi Yosua Prasetio, Arfhan Pratama, Kasahana Indra Putra, Ananta Kusuma Putra, Septian Ade Rahmadya Trias Handayanto Rahmat Hidayat Sarifah Sarifah Siti Fauziah Sulaeman, Okky Robiana Sulistyowati, Daning Nur Utami, Cheilla Cahya Utami Wardiani, Ditta Sri