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All Journal Jurnal Ilmiah KOMPUTASI Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan KOMPUTA : Jurnal Ilmiah Komputer dan Informatika J-Dinamika: Jurnal Pengabdian Kepada Masyarakat
Nurfalinda, Nurfalinda
Universitas Maritim Raja Ali Haji
Computer Science & IT Education Electrical & Electronics Engineering

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Case Based Reasoning untuk Diagnosis Penyakit Gizi Buruk pada Balita Nurfalinda, Nurfalinda; Nikentari, Nerfita
Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Vol 6 No 2 (2017): Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1040.735 KB) | DOI: 10.31629/sustainable.v6i2.424

Abstract

This research is conducted to build a diagnose system malnutrition among children under five years old. The system was developed with Case Based Reasoning (CBR). CBR is a case based reasoning system, using old knowledge to solve new problems. CBR can provide new solutions to problems by looking at most similarity case to the previous cases that have been stored in the base case. CBR in this research using a bayesian model indexing to find the type of disease malnutrition among children under five years old, the process of indexing is done to speed up the retrieval process. The nearest neighbor methode used in the process to determine the most similar of cases between new cases and the old cases that have been stored in the database as a case base to be used tratment solution.Tests carried out by using 70 case based were recorded in case of data based and 20 case based serve as a new case. Testing is done with five threshold values. The first scenario is to use threshold ≥ 0.95 system able to produce accuracy 20%. The second scenario is to use threshold ≥ 0.90 system able to produce accuracy 45%. The third scenario is to use threshold ≥ 0.85 system able to produce accuracy 60%. The fourt scenario is to use threshold ≥ 0.80 system able to produce accuracy 75%. The fifth scenario is to use threshold ≥ 0.75 system able to produce accuracy 85%.
Bisnis Online UMKM melalui Aplikasi E-Commerce untuk Pemasaran di Tengah Pandemik: Online Business UMKM with E-Commerce for Marketing during a Pandemic Alena Uperiati Alena; Eka Suswaini; Tekad Matulatan; Dwi Amalia Purnamasari; Nurfalinda Nurfalinda
J-Dinamika : Jurnal Pengabdian Masyarakat Vol 7 No 3 (2022): Desember
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/j-dinamika.v7i3.3405

Abstract

Dalam situasi pandemic covid 19 seperti sekarang ini kami berfikir, bagaimana meningkatkan kesejahteraan UMKM pada bisnis Donat Mini (Domi) dengan tetap mematuhi protokol kesehatan. Maka kami membuatkan aplikasi E-Commerce dimana pemasaran akan dilakukan secara online. Dengan adanya sistem aplikasi E-Commerce ini nantinya akan memudahkan UMKM Domi dan masyarakat untuk tetap bisa melakukan transaksi jual-beli tanpa harus bertatap muka dan berkerumun antri di toko. Dengan begitu protokol kesehatan dapat dijaga untuk menjaga jarak dan kebutuhan konsumen terpenuhi. Aplikasi E-Commerce ini memiliki berbagai fitur fungsi utama antara lain adalah memberikan layanan teknis, informasi, dan promosi tentang jenis usaha yang diperjualkan kepada masyarakat. Aplikasi E-Commerce ini juga menjadi jembatan bagi masyarakat sebagai pemanfaatan teknologi dalam memenuhi kebutuhan.
Prediksi Hasil Tangkap Ikan Laut Di Kota Tanjungpinang Menggunakan Metode SARIMA (Seasonal Autoregressive Integrated Moving Average) Malik, Riani Fitri Ibnul; Bettiza, Martaleli; Nurfalinda , -
Jurnal Ilmiah Komputasi Vol. 22 No. 4 (2023): Jurnal Ilmiah Komputasi : Vol. 22 No 4, Desember 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.22.4.3448

Abstract

Tanjungpinang is an archipelago. Fish is a food that is often consumed by local people. In 2019 the fish consumption rate is 66 kg/year. and in 2020 it will reach 68 kg/year. Meanwhile, the volume of fish caught in the Riau Islands is 322 kg/year and in 2021 it will decrease to 303 kg/year. Tanjungpinang is rich in marine potential so that the local government takes advantage of this by exporting fish abroad. With fish consumption rates increasing every year, the volume of fish caught is uncertain every year and there is demand for fish exports abroad. So it is necessary to have fish catch predictions to find out the availability of fish the following month. This prediction helps the government to develop a strategy to increase fish catches in Tanjungpinang City. Therefore a fish catch prediction system was built using the SARIMA method. The stages in this study were identifying seasonal data patterns, dividing training data and test data, designing the SARIMA method. The prediction results show that the best model for predicting marine fish catches is the model (0,2,1)(1,2,0)2 with a training data MAPE of 10% which is a very good prediction category and is suitable for use as an analysis by the government to regulate budget estimation and future work program strategy.
Prediksi Temperatur Maksimum di Kota Tanjungpinang Menggunakan Model CNN-LSTM Nurfalinda; Fiani, Mia Al; Rathomi, Muhamad Radzi
Komputa : Jurnal Ilmiah Komputer dan Informatika Vol 14 No 1 (2025): Komputa : Jurnal Ilmiah Komputer dan Informatika
Publisher : Program Studi Teknik Informatika - Universitas Komputer Indonesia (UNIKOM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputa.v14i1.15377

Abstract

The prediction of maximum temperature is important for supporting decision process related to public activities and reducing the consequences of climate change. The goal of this study is to analyze the performance of the CNN-LSTM hybrid method in forecasting maximum temperature in Tanjungpinang City by utilizing average humidity and rainfall as input variables. Historical weather data was obtained through the BMKG website, covering the period from January 1, 2022, to November 30, 2024, and was used as the research dataset. The CNN-LSTM model was developed by optimizing the advantages of CNN in recognizing spatial patterns and the capability of LSTM in capturing temporal patterns. The model was trained using an optimal configuration consisting of 128 CNN filters, a kernel size of 7, 200 LSTM units, a batch size of 16, and 120 epochs. Performance evaluation was conducted using two key metrics: Root Mean Squared Error (RMSE) of 1.65 and Mean Absolute Percentage Error (MAPE) of 4.19%. The findings indicate that the model can be used to predict maximum temperature based on available historical weather data. Additionally, the model has been implemented in a web-based platform that allows users to input historical data and select prediction periods ranging from 1, 3, 7, to 10 days ahead. The prediction results are presented in tables and graphical visualizations to facilitate users in understanding and evaluating the generated information.
ANALISIS PENERAPAN METODE PENETRATION TESTING PADA KEAMANAN JARINGAN WLAN (Studi Kasus: Universitas Maritim Raja Ali Haji) Chahyadi, Ferdi; Sitompul, Afrio Triputra; Nurfalinda
Sustainable Vol 12 No 1 (2023): Jurnal Sustainable : Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/sustainable.v12i1.4803

Abstract

This test is carried out to find security holes in the Wireless Local Area Network (WLAN) network. In this paper, author simulates attacks on a WLAN network using four attack parameters: Bypassing MAC Authentication, Attacking The Infrastructure and Man In The Middle Attacks. There were four attacks carried out, and two of them were successful. Thus, it can be concluded that the Raja Ali Haji Maritime University (UMRAH) WLAN network is quite secure. Nonetheless, other offensive actions, such as infrastructure attacks or Man In the Middle Attacks, In order to ensure more security, it is necessary to add a DNS Security Extensions protocol to prevent fake DNS redirects, add a firewall to the security system and use TLS on captive portals.
Application of Gaussian Naive Bayes Algorithm in Weather Classification of Tanjungpinang City Wibisono, Ganda Bagus; Nurfalinda, Nurfalinda; Bettiza, Martaleli
Sustainable Vol 13 No 1 (2024): Jurnal Sustainable : Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/crvmg397

Abstract

Cuaca mengacu pada kondisi atmosfer sesaat di tempat dan saat tertentu. Cuaca dapat berubah dalam beberapa jam. Cuaca terdiri dari beberapa elemen cuaca. Perkiraan cuaca yang akurat bisa membantu kegiatan sehari-hari warga yang didapat dari klasifikasi yang tepat. Landasan dari klasifikasi Bayes adalah teorema tentang probabilitas bersyarat. Algoritma Naïve Bayes dan algoritma Gaussian Naïve Bayes berbeda satu sama lain. Teknik ini menggabungkan distribusi Gaussian untuk mengatasi perbedaan tersebut. Stasiun Meteorologi Raja Haji Fisabillillah Tanjungpinang menyediakan data suhu, kelembaban, tekanan udara, dan kecepatan angin yang digunakan sebagai parameter penelitian. Data tersebut merupakan data harian yang mencakup periode 1 Januari 2019 hingga 31 Desember 2019 dengan total 365 data. Hasil penelitian dikategorikan ke dalam beberapa kategori cuaca yaitu thunderstorm (TS), Lightning, Mist, lightning rain (TS/RA), Cloudy, rain (RA) dan haze (HZ). Output dari penelitian ini didapatkan akurasi tertinggi sebesar 60,87% dengan jumlah data training sebanyak 50%.
Co-Authors Alena Uperiati Anton Hekso Chahyadi, Ferdi Eka Suswaini Fiani, Mia Al Hayaty, Nurul Ibnu Kahfi Bachtiar Malik, Riani Fitri Ibnul Martaleli Bettiza Matulatan, Tekad Muhamad Radzi Rathomi Nikentari, Nerfita Purnamasari, Dwi Amalia Radzi Rathomi Sitompul, Afrio Triputra Wibisono, Ganda Bagus