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Lailan Sofinah Harahap
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TINJAUAN LITERATUR PERAN BIG DATA DALAM PENGEMBANGAN KONTEN DIGITAL Ela Khairani Br. Siregar; Lailan Sofinah Harahap
Jurnal Media Akademik (JMA) Vol. 3 No. 1 (2025): JURNAL MEDIA AKADEMIK Edisi Januari
Publisher : PT. Media Akademik Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62281/v3i1.1509

Abstract

Perkembangan teknologi yang ada di Indonesia sekarang ini semakin tak terkendalikan lagi, teknologi-teknologi yang ada sekarang ini memiliki perkembangan yang sangat pesat. Perkembangan teknologi  juga telah mendorong sebiuah perkembangan  penggunaan big data dalam berbagai bidang sektor  industri yaitu konten digital.  Big Data juga melibatkan  sebuah proses pengelolaan data,  Penyimpanan,  penelusuran informasi,  dan analisis  yang menunjukkan  dalam hal-hal seperti volume, velocity, dan variety.  Bagi kalangan bidang sektor digital  munculnya big data menjadi salah satu alternatif yang bisa mempermudah pekerjaan mereka.  Big Data juga sangat bermanfaat dikarenakan  Big Data dapat  menciptakan sebuah  konten yang lebih relavan serta terjamin dan sangat memenuhi kenutuhan audiens. Tetapi, penerapan Big Data dalam pengembangan konten digital tidak selalu mulus ada berbagai masalah dalam pengembangan  tersebut  yaitu adanya keterbatasan dalam mengakses data, kurangnya  pengetahuan yang dalam,  isu kerahasian data,  kesenjangan akases digital. Penelitian ini dibuat untuk  mengenali sebuah dampak tantangan dan memberikan solusi agar dapat mengoptimalkan sebuah peran dari big data tersebut. Hasil dari penelitian ini juga akan menampilkan bahwa Big data dapat menjadi alat atau bantuan yang sangat efektif dalam meninjau konten, efisiensi produk dan sebuah inovasi jika rintangan-rintangan itu  dapat  diatasi. Dengan demikian , perlunya kerjasama  antara si pengembangan konten dengan pembuatan kebijakan agar bisa memastikan bahwa implentasi Big Data dapat berjalan dengan baik. Penelitian ini juga bertujuan untuk mengkaji literatur lebih dalam untuk mengembangkan sebuah komten digital, dapat mengidentifikasi, dan tantangan yang ada. Hasil kajian juga akan menunjukkan bahwasannya big data berperan penting dalam personalisasi sebuah konten. Namun, diperlukan pendekatan pendekayan yang benar-benar sangat etis agar bisa mengatasu tantangan tersebut.
Identifikasi Tingkat Kematangan Buah Tomat Melalui Warna dengan Penerapan Jaringan Saraf Tiruan (JST) Nazwa Alya Faradita; Lailan Sofinah Harahap
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 2 No. 6 (2024): November : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v2i6.292

Abstract

The selection of agricultural and plantation products often relies on human perception of fruit color. Manual identification through visual observation has several drawbacks, such as time consumption, fatigue, and varying perceptions of quality. Digital image processing technology enables automatic sorting of products. This study applies the Perceptron learning method to identify tomato ripeness. Tomato images are captured using a webcam, analyzed through color histograms, and identified using artificial neural networks. The identification success rate reaches 43.33%, with outputs categorized as Unripe (10%), Half-Ripe (6.66%), and Ripe (26.66%).
Penerapan Jaringan Syaraf Tiruan untuk Pengenalan Pola Huruf Menggunakan Metode Bidirectional Associative Memory (BAM) Warda Hamidah; Lailan Sofinah Harahap
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 4 (2024): November : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v1i4.433

Abstract

The process in artificial intelligence is similar to the process that occurs in the human brain. The pattern recognition process is to determine whether the input and output values ​​are the same so that the system can detect the pattern. A reciprocal relationship between the input and output levels is made possible by the two interconnected layers of the Bidirectional Associative Memory (BAM) technique. As a result, this technique can serve as an associative memory, meaning that some of the data stored in it can be called upon.. The load signal is transmitted from the input layer X to the output layer Y in this procedure. The weight value will be modified by computing the outcomes between the ranks [1,0]. In this work, the active sigmoid function is employed. Three input characters—the letters S, O, and X—are used in this study's 5x5 order matrix. A pattern [27 4] that matches the target is produced by the target letter S [1,-1], a pattern [27 -3] that does not match the target is produced by the target letter O [1.1], and a pattern [-37 21] that matches the target is produced by the target letter X [-1,1]. Consequently, not all patterns are able to meet the established objectives.
Penerapan Algoritma Backpropagation dalam Memprediksi Kemenangan dalam Bermain Mobile Legends Rifdah Syahputri; Alwi Andika Panggabean; Lailan Sofinah Harahap
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 4 (2024): November : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v2i4.470

Abstract

Victory in Mobile Legends is influenced by various factors, such as player skills, strategy, and character selection. To predict game outcomes, the backpropagation algorithm is applied to process historical gameplay data and create an accurate predictive model. This study aims to apply the backpropagation algorithm to predict victory based on player attributes, including team role, experience level, and past performance. The research method involves training and testing the model using data from multiple gameplay sessions with varied outcomes. Findings show that the backpropagation algorithm can predict game results with high accuracy, especially when the data includes a more comprehensive range of attributes. The implications of this study suggest that a backpropagation-based predictive model can help players understand their chances of winning and optimize their gameplay strategies. Furthermore, future developments in this algorithm could provide benefits for similar applications in other digital gaming fields.
Pemanfaatan Jaringan Saraf Tiruan untuk Prediksi Curah Hujan di Sumatera Utara Arizka Anggraini; Lailan Sofinah Harahap
Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 2 No. 6 (2024): Desember : Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v2i6.457

Abstract

The use of Artificial Neural Networks (JST) for weather prediction is one of the innovative approaches in climate data analysis. This study aims to apply JST in predicting weather, especially rainfall and the number of rainy days in the North Sumatra region. Historical weather data obtained from BMKG Region I for 2022-2023 is used as input to train the JST model. With a training process that involves processing rainfall data, this model is expected to provide accurate predictions regarding weather patterns. The results of this research can help in agricultural sector planning, disaster risk mitigation, and natural resource management. JST has proven to be effective in identifying dynamic and complex weather patterns, so it has the potential to be used in long-term weather prediction.
Perancangan Model Jaringan Syaraf Tiruan untuk Memprediksi Penyakit Demam Berdarah Menggunakan Algoritma Hebb Rule Adinda Tarisyah Hsb; Mazayah Tsaqofah; Lailan Sofinah Harahap
Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 2 No. 6 (2024): Desember : Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v2i6.483

Abstract

Dangeu dengue fever or what we often call dengue fever is a disease transmitted by the Aedes aegypti mosquito and caused by the dengue virus. This disease can potentially cause serious complications if it does not receive proper treatment. In this research, the author uses the application of artificial neural networks with the Hebb rule approach to predict the risk level of dengue fever. Predictions are made based on factors such as weather conditions, population density and historical case data that influence this disease. The Hebb rule is used in this research because of its ability to strengthen connections between neurons based on the input patterns they receive, so it is hoped that it can produce more accurate predictions. Test results show that this method has a fairly high level of accuracy in predicting the pattern of dengue fever cases in an area. This research indicates that the application of artificial neural networks with the Hebb rule can be an effective tool for related parties in taking preventive measures to minimize the number of dengue cases in the future.
Penyelesaian Permasalahan Pengadaan Stok di Toko Grosir Naek Menggunakan Logika Fuzzy dengan Metode Tsukamoto Juwita Sari; Intan Widya Saputri Nst; Lailan Sofinah Harahap
Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 2 No. 6 (2024): Desember : Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v2i6.484

Abstract

Stock management is an important aspect in the operations of a grocery store. By knowing when to add stock, shop owners can optimize the availability of goods without excess stock. In this research, the fuzzy logic method is applied to determine stock procurement decisions based on sales data and remaining stock. The results of the research show that fuzzy logic can be used to assist in making stock procurement decisions with a fairly high level of accuracy.
Median Filter Optimization and Sharpening Techniques to Improve Digital Image Quality Riko Prananda Prayugo; Lailan Sofinah Harahap
Jurnal Info Sains : Informatika dan Sains Vol. 15 No. 01 (2025): Informatika dan Sains , 2025
Publisher : SEAN Institute

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

Abstract

The quality of digital images often degrade due to noise disturbances, especially impulsive noise such as salt and pepper. The aim of this study is to optimize the use of the median filter as a denoising technique and to combine it with a sharpening method to enhance the sharpness and clarity of image structures. The proposed approach involves applying an adaptive median filter reduce noise while preserving edge details, followed by a convolution kernel based sharpening technique to further emphasize visual features. The performance of the method is evaluated by compare the Peak Signal-to-Noise Ratio (PSNR) and the Structural Similarity Index Measure (SSIM) between the processed images and the original images. The experimental results demonstrated that this combined approach significantly improve both PSNR and SSIM values after filtering and sharpening, indicating that the synergy between median filtering and sharpening effectively restore the visual quality of digital images. These findings can serve as a foundation for the development of adaptive image preprocessing systems to handle impulsive noise.
Pengenalan Objek pada Citra Digital Menggunakan Metode Template Matching Tia Ramadani; Lailan Sofinah Harahap; Rika Khairani
Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 3 No. 3 (2025): Juni : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v3i3.826

Abstract

Object detection in digital images is a crucial aspect of image processing and computer vision, with applications ranging from surveillance systems and robotics to image-based search. One commonly used approach is template matching, a technique that compares a template image with sections of the target image to identify similar patterns. This study explores the implementation of the template matching method for object recognition in digital images. The process begins with image preprocessing to enhance data quality, followed by a matching procedure using normalized cross-correlation. Experimental results indicate that this method can accurately detect objects under stable lighting and scale conditions. However, its performance decreases when images undergo rotation or scale variations. Therefore, while template matching proves effective under ideal conditions, further methodological development is needed to improve its robustness against geometric transformations.s
Kombinasi Metode High Pass Filtering dan Contrast Stretching Dalam Peningkatan Detail dan Kontras Citra -, Nurhidayati; Lailan Sofinah Harahap; Juwita Sari
Journal of Informatics, Electrical and Electronics Engineering Vol. 4 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v4i4.2460

Abstract

Digital images have many functions in fields such as medicine, remote sensing, security, and social media, where cinematography and visual delivery are very complex. However, images often have problems with noise, blur, and low contrast. Furthermore, in an underwater image, another challenge arises because light is absorbed and scattered unevenly, which makes the image look blurry and dark. This study aims to explain the improvement of the digital image processing process in two ways, namely through High Pass Filtering and Contrast Stretching. Details and edges of the image that you want to focus on will be added with High Pass Filtering which is done through 2D FFT. While the name of the second method, namely Contrast Stretching, means clarifying the differences in objects and backgrounds by widening the range of pixel intensity. The trial was carried out on a grayscale image measuring 200x200 pixels in JPG format. The processes carried out include conversion to grayscale, high frequency, application of Low Pass Filter, and contrast stretching. Based on the processing results, the increase in image sharpness reached 35% and contrast 42% when compared to unprocessed images. These figures will then be very helpful in visual analysis and interpretation
Co-Authors Adinda Tarisyah Hsb Alwi Andika Panggabean Arizka Anggraini Ela Khairani Br. Siregar Fajar Syakbani Intan Widya Saputri Nst juwita sari Mazayah Tsaqofah Nasution, Mansalwa Utama Nazwa Alya Faradita Nurhidayati - Puji Sri Alhirani Rani Chantika Rifdah Syahputri Rika Khairani Riko Prananda Prayugo Tia Ramadani Warda Hamidah