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INDONESIA
Jurnal Ilmu Komputer
Published by Universitas Ngudi Waluyo
ISSN : -     EISSN : 26556316     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Multimatrix ini sebagai media publikasi artikel penelitian, pengabdian masyarakat dalam bidang ilmu komputer
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 56 Documents
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KOMPARASI NEURAL NETWORK DAN SUPPORT VECTOR MACHINE UNTUK DATA TIME SERIES DAN NON-TIME SERIES Suamanda Ika Novichasari; Restu Rakhmawati
Multimatrix Vol. 5 No. 1 (2023): Jurnal Multimatrix Juli 2023
Publisher : Universitas Ngudi Waluyo

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Abstract

Abstrak— Neural Network dan Support Vector Machine merupakan metode datamining yang sering digunakan. Penelitian ini bertujuan untuk mengetahui performa dari Neural Network dan Support Vector Machine yang diterapkan pada data time series dan non-time series. Sehingga terlihat perbedaan dan keunggulan dari kedua metode tersebut. Data yang digunakan merupakan dataset publik, “Australian Credit Approval dan Polar Ice Data”. Untuk tahap validasi model menggunakan 10fold cross-validation dan proses evaluasi model menggunakan Root Mean Square Error (RMSE). Hasil percobaan membuktikan bahwa pada data time series SVM lebih unggul dari NN dilihat dari kinerja dan waktu eksekusinya, sedangkan pada data non-time series NN lebih unggul. Hasil akhir evaluasi percobaan data time series berbanding terbalik dengan hasil percobaan data non-time series.. Kata kunci— Time series, Non-time series, Neural Nerwork, Support Vector Machine, klasifikasi kelayakan kredit, Prediksi Polar Es.
Sistem Pengenalan Retina Menggunakan Self Organizing Map Untuk Mendeteksi Retinopati Diabetika: Marsiska Ariesta P, Iwan Setiawan W, Sri Mujiyono Marsiska Ariesta Putri
Multimatrix Vol. 5 No. 1 (2023): Jurnal Multimatrix Juli 2023
Publisher : Universitas Ngudi Waluyo

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Eyes are important human sense. Diseases that damage many function of eye is diabetic retinopathy. Diabetic retinopathy is a microvascular complication that can occur in patients with diabetic and attacking vision function. Clinical symptoms of this disease is the emergence of mikroaneurisma which is swelling of blood vessels are microscopic and can be seen as reddish dots on the retina. The retina recognition process was done by taking the retina image data were processed using the Laplacian operator. Then do the feature extraction using Principal Component Analysis (PCA). PCA results of binary data is used as an input to the process of Neural Networks Self Organizing Map (SOM). The training process in order to make a decision about whether diabetic retinopathy or not . Results obtained with feature extraction Principal Component Analysis (PCA) with the variables, learning rate (a) = 0.6 , reduction of alpha (δ) = 0.5, threshold = 0.02 similarity and distance = 1x10-15, has produced recognition rate by 85% for the best possible, and 50% for the worst possible. Keyword : Retina Recognition, Principal Component Analysis, Self Organizing Map, Diabetic Retinopathy
Deteksi Rasa Kantuk Pengendara Kendaraan Bermotor Menggunakan Image Prosessing: Iwan Setiawan Wibisono,, Marsiska Ariesta Iwan Wibisono; Marsiska Putri
Multimatrix Vol. 3 No. 1 (2021): Inovasi Teknologi Di Massa Pasca Pandemi Covid 19
Publisher : Universitas Ngudi Waluyo

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Abstract - The number of traffic accidents in Indonesia is increasing. One of the main causes of this condition is drowsy drivers. Things like this need to be considered so that the number of accidents due to these factors can be avoided. Therefore, a research was conducted using a digital image processing system to detect driver sleepiness. Digital image processing is intended to determine whether the driver is not sleepy or while driving with input in the form of eye images taken using a digital camera and then entered into the Matlab programming language where the image is taken the value of bw of the sleepy eye area and not a reference image which will be processed with image processing such as cropping, grayscale, iris extraction, thresholding, and analyzed by the bwarea method compared with the image to be identified. The output is information on whether the driver is sleepy or not. Keywords: Bw area, Iris, Digital Image Processing, Thresholding
Komparasi Algoritma Machine Learning dan Ensemble Methods dalam Prediksi Penyakit Jantung dengan Dataset yang Bervariasi Abdul Rohman; Sri Mujiyono
Multimatrix Vol. 4 No. 2 (2022)
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This study aims to compare the performance of various machine learning algorithms and ensemble methods in predicting heart disease, using two different datasets: datasets from the UCI Machine Learning Repository and Kaggle. Nine algorithms were tested, including Logistic Regression (LR), K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), XGBoost, LightGBM, CatBoost, Support Vector Machine (SVM), and Naive Bayes (NB). The data were processed through data cleaning, normalization, and splitting the dataset into training and test data. The experimental results showed that K-Nearest Neighbors (KNN) performed best with an accuracy of 91.80%, followed by Support Vector Machine (SVM) and Random Forest (RF), which also demonstrated stable and effective results in handling complex datasets. Although Decision Tree (DT) and Naive Bayes (NB) performed lower, these results demonstrate that basic machine learning algorithms can provide adequate results for heart disease classification. This study recommends the use of ensemble algorithms and further exploration in feature engineering to improve predictions.
Analisis Kinerja Algoritma Machine Learning untuk Prediksi Penyakit Jantung Menggunakan Metode Data Preprocessing Terintegrasi Abdul Rohman; Sri Mujiyono
Multimatrix Vol. 5 No. 1 (2023): Jurnal Multimatrix Juli 2023
Publisher : Universitas Ngudi Waluyo

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Abstract

Penyakit jantung merupakan salah satu penyebab kematian tertinggi secara global, sehingga diperlukan metode prediksi yang akurat dan dapat dipercaya untuk mendukung deteksi dini. Penelitian ini bertujuan untuk menganalisis kinerja beberapa algoritma Machine Learning—Logistic Regression, Random Forest, Support Vector Machine (SVM) dengan kernel RBF, dan XGBoost—dalam memprediksi penyakit jantung menggunakan dataset Cleveland yang tersedia di platform Kaggle. Penelitian ini menggunakan pipeline preprocessing terintegrasi yang mencakup pembersihan data, transformasi data, reduksi data, serta pengujian dengan dua skenario: tanpa SMOTE dan dengan SMOTE untuk menangani ke kinerja kelas. Hasil penelitian menunjukkan bahwa Random Forest memberikan performa terbaik pada skenario tanpa SMOTE dengan akurasi 0.9016, recall 0.9643, F1-score 0.9000, dan ROC-AUC 0.9594. Sementara itu, penerapan SMOTE tidak secara signifikan meningkatkan akurasi, namun mampu menstabilkan recall dan F1-score pada beberapa algoritma, terutama Logistic Regression dan SVM. Secara keseluruhan, hasil eksperimen menegaskan bahwa kualitas preprocessing dan penanganan ke konsistensi kelas memiliki pengaruh utama terhadap kinerja model. Studi ini memberikan kontribusi pada penerapan praktik terbaik dalam pengembangan model prediksi penyakit jantung berbasis Machine Learning yang dapat direplikasi pada penelitian lanjutan maupun implementasi klinis. Kata kunci: Machine Learning, Prediksi Penyakit Jantung, Preprocessing Data, SMOTE, Random Forest, Regresi Logistik, SVM, XGBoost.
Implementation of Blended Learning Based on E-Learning in the e-guru.id Community Semarang Abdul Rohman; Purwosiwi Pandansari
Multimatrix Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Ngudi Waluyo

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Digital transformation in education encourages teachers to master innovative learning technologies. Digital teacher communities such as e-guru.id play a strategic role in facilitating the development of digital pedagogical competencies through the implementation of blended learning. This study aims to analyze the implementation of e-learning-based blended learning in the e-guru.id Semarang community, identify the platforms and strategies used, and explore the challenges and their impact on teacher competence. The research employed a descriptive qualitative approach with data collection techniques through observation, in-depth interviews, and documentation of 30 teacher members of the e-guru.id Semarang community. Data analysis was conducted descriptively qualitatively using the Miles and Huberman interactive model. The results showed that the e-guru.id Semarang community implemented a blended learning model with a combination of synchronous learning through Google Meet and Zoom, as well as asynchronous learning using Google Classroom, Moodle, and WhatsApp as supporting media. The implementation of blended learning in this community proved effective in increasing teachers' digital pedagogical competence by 76%, expanding access to collaboration among members, and improving the ability to design technology-based learning. However, challenges faced include limited internet access (43%), digital literacy gaps (35%), and time constraints (22%). The e-guru.id Semarang community has successfully become a model of a professional learning community that supports the sustainable development of teachers in the digital era. Keywords: blended learning, e-learning, teacher community, e-guru.id, digital competence
Sistem Informasi Penyewaan Kamera Pada Owen Rental Kamera Menggunakan Metode Waterfall Muhammad Ari Wibowo; Iwan Setiawan Wibisono
Multimatrix Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Ngudi Waluyo

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Proses bisnis penyewaan kamera pada Owen Rental Kamera menggunakan cara manual yaitu customer yang ingin menyewa kamera harus datang ke lokasi untuk mengisi form penyewaan. Kemudian customer membayarkan uang kepada Owen Rental Kamera selanjutnya akan diberikan nota sebagai bukti pembayaran. Hal tersebut menjadi kendala bagi customer yang tidak memiliki waktu luang dan customer juga terbatas oleh waktu karena hanya dilayani saat jam kerja saja. Permasalahan tersebut muncul karena belum tersedianya sistem informasi khusus untuk mendukung penyewaan kamera. Membuat sebuah sistem informasi penyewaan kamera pada Owen Rental Kamera dengan menerapkan metode waterfall. Metode pengembangan perangkat lunak yang digunakan dalam penelitian ini adalah metode air terjun atau waterfall. Pengujian pertama menggunakan Black Box menghasilkan 39 pengujian fungsi berhasil dan pengujian kedua dengan menggunakan System Usability Scale rata-rata skor yang didapat berkisar 79.62 dengan kategori Acceptable Ranges berada pada nilai Acceptable. Maka dapat diterima bahwa sistem informasi penyewaan kamera pada Owen Rental Kamera layak digunakan oleh user dan dapat di upgrade kedepannya agar menjadi lebih bagus lagi. Sistem informasi penyewaan kamera pada Owen Rental Kamera berhasil dibuat dengan menerapkan metode air terjun atau waterfall sebagai metode pengembangan perangkat lunak. Kata Kunci: Sistem Informasi; Penyewaan; Owen Rental Kamera; Waterfall. The camera rental business process at Owen Camera Rental uses the manual method, namely customers who want to rent a camera must come to the location to fill out the rental form. Then the customer pays money to Owen Camera Rental and will then be given a note as proof of payment. This is an obstacle for customers who do not have free time and customers are also limited by time because they are only served during working hours. This problem arises because there is no specific information system available to support camera rental. Create a camera rental information system at Owen Camera Rentals by implementing the waterfall method. The software development method used in this research is the waterfall method. The first test using the Black Box resulted in 39 successful function tests and the second test using the System Usability Scale, the average score obtained was around 79.62 with the Acceptable Ranges category being at the Acceptable value. So it is acceptable that the camera rental information system at Owen Camera Rental is suitable for use by users and can be upgraded in the future to make it even better. The camera rental information system at Owen Camera Rental was successfully created by applying the waterfall method as a software development method. Keywords: Information System; Rental; Owen Camera Rental; Waterfall.
Sistem Pendukung Keputusan Untuk Menentukan Penyakit Mulut dan Kuku Pada Sapi di Kecamatan Getasan Menggunakan Metode Simple Additive Weight Puput Amanda Rasyid; Sri Mujiyono
Multimatrix Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Ngudi Waluyo

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Sapi merupakan salah satu hewan yang kegunaannya banyak digunakan di Indonesia khusunya untuk di konsumsi, mulai dari daging, kulit, tulang, susu, hingga kotoran sapi sehingga penjualan sapi semakin meniingkat setiap tahunnya. Meskipun pemeliharaanya mudah, tetapi sapi juga rawan terkena penyakit yang satu ini. Penyakitnya yaitu penyakit mulut dan kuku yang disebabkan oleh virus yang berasal dari lingkungan dan pakan yang diberikan kepada sapi. Maka dari itu dibentuklah sistem pendukung keputusan untuk menentukan penyakit mulut dan kuku pada sapi. Dengan adanya sistem pendukung keputusan ini memberikan kemudahan bagi peternak untuk menentukan penyakit mulut dan kuku yang lebih efektif dan efisien. Penelitian ini menggunakan bahasa pemprograman PHP dan metode SAW untuk menentukan perhitungan nilai dari sapi sehingga mengahasilkan keputusan bahwa sapi tersebut terkena penyakit mulut dan kuku atau tidak. Dari hasil pengujian ini menghasikan bahwa sistem berjalan sesuai dengan fungsinya yaitu dapat menentukan penyakit mulut dan kuku dari hasil nilai tertinggi. Serta pengujian akurasi yang menghasilkan nilai yang sangat baik sebesar 100%. Maka disimpulkan bahwa sistem layak digunakan karena perhitungan manual dengan perhitungan sistem sangat akurat. Kata kunci: Sistem pendukung keputusan; SAW; penyakit mulut dan kuku; kecamatan getasan. Cows are one of the animals whose uses are widely used in Indonesia, especially for consumption, ranging from meat, skin, bones, milk to cow dung so that sales of cattle are increasing every year. Although maintenance is easy, cows are also prone to this one disease. The disease is foot and mouth disease caused by a virus originating from the environment and the feed given to cows. Therefore a decision support system was formed to determine foot and mouth disease in cattle. The existence of this decision support system makes it easy for farmers to determine foot and mouth disease more effectively and efficiently. This study uses the PHP programming language and the SAW method to determine the calculation of the value of the cow so that it results in a decision whether the cow has foot and mouth disease or not. From the results of this test, the system runs according to its function, namely it can determine foot and mouth disease from the highest score. As well as testing accuracy which produces an excellent value of 100%. So it was concluded that the system is feasible to use because manual calculations with very accurate system calculations. Keywords: Decision support system; SAW; foot and mouth disease; Getasan district
Sistem Pakar Diagnosa Hama dan Penyakit Tanaman Bawang Merah dan Cabai Menggunakan Metode Forwad Chaining Afif Faisal Yasin; Sri Mujiyono; Abdul Rohman
Multimatrix Vol. 6 No. 1 (2024): Juli 2024
Publisher : Universitas Ngudi Waluyo

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Permasalahan terhadap virus penyakit pada tumbuhan bawang merah dan cabai dapat menyebabkan kerugian ekonomi yang signifikan bagi Pedagang sekalipun Petani. Oleh sebab itu perlu dikembangkan suatu system pakar untuk mendiagnosa virus ini dengan cepat dan akurat. Penelitian ini menggunakan metode Forward Chaining dan aturan If dan Then yang bertujuan untuk mengembangkan system pakar diagnosa penyakit pada tumbuhan tersebut. Untuk mengembangkan system pakar ini, dapat mengumpulkan berbagai data jenis hama penyakit yang biasanya menyerang bawang merah dan cabai beserta gejala – gejalanya. Hasil uji coba system ini menunjukan bahwa metode Forward Chaining sangat efektif dalam mendiagnosa penyakit tersebut. Dengan gejala memberikan gejala tertentu, system dapat dengan cepat menentukan jenis penyakit yang terjangkit. Keakuratan sistem ini memberikan harapan bagi para petani dan pedagang untuk mengatasi permasalahan gagal panen mereka yang ditimbulkan oleh serangga hama. Kata Kunci : Sistem Pakar, Forward Chaining, If Dan Then, Diagnosa, Penyakit Tanaman Bawang Merah Dan Cabai Problems with viral diseases in shallots and chili plants can cause significant economic losses for traders and even farmers. Therefore it is necessary to develop an expert system to diagnose this virus quickly and accurately. This study uses the Forward Chaining method and If and Then rules which aim to develop an expert system for diagnosing plant diseases. To develop this expert system, I collected data on various types of pests that usually attack shallots and chilies and their symptoms. The results of this system trial show that the Forward Chaining method is very effective in diagnosing the disease. By giving certain symptoms, the system can quickly determine the type of disease that is infected. The accuracy of this system gives hope to farmers and traders to overcome their crop failure problems caused by insect pests. Keywords: Expert System, Forward Chaining, IF and Then, Diagnose, Onion and chili plant diseases
Pengembangan Sistem Informasi Algoritma Berbasis Linier Search Untuk Transaksi Jual Beli Ikan Laut Berbasis Web di Pelabuhan Perikanan Deta verrensyah; Iwan Setiawan Wibisono; Abdul Rohman
Multimatrix Vol. 6 No. 1 (2024): Juli 2024
Publisher : Universitas Ngudi Waluyo

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Perkembangan teknologi informasi telah mengubah cara manusia berinteraksi dan melakukan berbagai kegiatan,termasuk dalam perdagangan. Salah satu sektor perdagangan yang mengalami perkembangan pesat adalah perdagangan ikan. Dalam rangka untuk meningkatkan efisiensi dan kenyamanan transaksi jual beli ikan. Perikanan penjualan dan pembelian Cilacap telah mengimplementasikan sistem berbasis web. Penelitian ini bertujuan untuk menggambarkan implementasi algoritma linear search pada sistem transaksi jual beli ikan berbasis web di PPC Cilacap. Algoritma Linear search digunakan untuk mencari data ikan yang tersedia dalam sistem berdasarkan kriteria tertentu, seperti jenis ikan,ukuran,dan harga. Penerapan algoritma ini diharapkan dapat membantu para pedagang dalam menemukan ikan yang sesuai dengan kebutuhan mereka dengan kebih cepat dan efisien. Kata kunci : Algoritma linear search,transaksi jual beli ikan,berbasis web,PPC Cilacap,Efisiensi,Berbasis web The development of information technology has changed the way humans interact and carry out various activities, including in trade. One of the trade sectors that experienced rapid development was the fish trade. In order to increase the efficiency and convenience of buying and selling fish transactions. Fishery sale and purchase of Cilacap has implemented a web-based system.This study aims to describe the implementation of the linear search algorithm on a web-based fish buying and selling transaction system at PPC Cilacap. The Linear search algorithm is used to find available fish data in the system based on certain criteria, such as fish species, size, and price. The application of this algorithm is expected to help traders find fish that suit their needs more quickly and efficiently. Keywords: linear search algorithm, fish buying and selling transactions, web-based, PPC Cilacap, efficiency, web-based

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