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INDONESIA
Jurnal Informatika Upgris
Published by Universitas PGRI Semarang
ISSN : 24604801     EISSN : 24776645     DOI : -
Core Subject : Science,
Computer Science & IT
Journal of Informatics UPGRIS published since June 2015 with frequency 2 (two) times a year, ie in June and December. The editors receive scientific writings from lecturers, teachers and educational observers about the results of research, scientific studies and analysis and problem solving closely related to the field of Information Technology and Communications / Informatics.
Arjuna Subject : -
Articles 17 Documents
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Search results for , issue "Vol 7, No 2: Desember 2021" : 17 Documents clear
Rancang Bangun Pendeteksi Kualitas Beras Menggunakan Metode K-Nearest Neighbor Berbasis Android Mitra Saputra Ardi; Abdullah Abdullah; Usman Usman
Jurnal Informatika Upgris Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.8467

Abstract

Beras merupakan kebutuhan yang sangat penting bagi penduduk di kawasan Asia termasuk Indonesia, begitu juga yang terjadi pada Kabupaten Indragiri Hilir. Namun demikian, harga beras di pasaran semakin melonjak dan banyak beredar beras yang kualitasnya kurang baik. Oleh karena itu perlu adanya standar kualitas mutu beras dipasaran. Standar pengujian kualitas biasanya terdapat dua tahap, yaitu uji laboratorium dan uji visual. Namun, pengujian secara visual selama ini masih dilakukan secara manual sehingga masih sering terjadi kesalahan karena terbatasnya penglihatan manusia dan subjektivitas penguji. Oleh sebab itu, sistem pengujian secara visual dengan citra digital dapat menjadi solusi yang efektif untuk menentukan klasifikasi dan kualitas beras yang ingin kita ketahui. Proses pengujian dapat dilihat dari nilai putih, dan nilai bersih yang diakuisisi melalui pengolahan citra digital, data yang telah diakuisisi kemudian diklasifikasi ke dalam 3 kelas yaitu kelas baik, kelas sedang dan buruk. Berdasarkan hasil evaluasi metode holdout dari 10 data eksperimen diketahui bahwa metode k-Nearest Neighbor memiliki tingkat ketelitian 85,55 % untuk k=1, 82,21 % untuk k=3 dan 85,55 % untuk k=5
A comparative evaluation for Detection Brain Tumor in MRI Image using Machine learning algorithms Shahab Kareem; shavan askar; Ibrahim Abdulkhaleq; Roojwan Sc. Hawezi
Jurnal Informatika Upgris Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.9503

Abstract

In medical imaging, automated defect identification of defects has taken on a prominent position. Unaided prediction of tumor (brain) recognition in magnetic resonance imaging process (MRI) is vital for patient preparation. With traditional methods of identifying z is designed to reduce the burden on radiologists. One of the problems with MRI brain tumor diagnosis is the size and variation of their molecular structures. This article uses deep learning techniques (Artificial neural network ANN, Naive Bayes NB, Multi-layer Perceptron MLP ) to discover brain tumors in the MRI scans. First, the brain MRI images are run through the preprocessing steps to remove texture features. Next, these features are used to train a machine learning algorithm.
Model Average-Based Fuzzy Time Series untuk Prediksi Perkembangan Kasus Terkonfirmasi Positif COVID-19 Endro Dwi Wuryanto; Nella Valen Ika Puspita
Jurnal Informatika Upgris Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.9559

Abstract

The number of positive confirmed COVID-19 cases in Indonesia continues to rise on a daily basis. A prediction model is required to examine and measure the current progression of positive verified COVID-19 instances and to anticipate these circumstances in the future. The goal of this research is to create a prediction application that uses a fuzzy time series approach as a prediction method and an average-based length algorithm as an interval length determinant. The effective interval length can have a greater impact on the prediction outcomes. The data for this study came from the COVID-19 task force's website, and it tracked the progression of positive confirmed COVID-19 cases from November 2020 to July 2021. The Mean Absolute Percentage Error (MAPE) is relatively little based on the findings of the prediction application performance. This can help the management unit make decisions by giving information and establishing policies relating to actual efforts to prepare for, plan for, prevent, and control the spread of COVID-19.
Designing Mathematics Learning Media Using Adobe Animate Application at SMKN 1 Bukittinggi Miftahul Fikri; Hari Antoni Musril
Jurnal Informatika Upgris Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.9036

Abstract

To achieve the goals of education, of course, students must go through a process, namely learning by following all the series of learning processes that are expected by a teacher to create an interesting learning atmosphere, for example by utilizing learning media. Research on the design of mathematics learning media using adobe animate applications at SMKN 1 Bukittinggi uses the 4D version of the research and development (R&D) method, namely Define, Design, Develop, and Disseminate. The system development model uses Luther Sutopo's Multimedia Development Life Cycle development model which consists of 6 stages: Concept, Design, Material Collection, Assembly, Testing, and Distribution. The product test used in this research is the validity test, practicality test, and effectiveness test. The results of the product test that the author did obtained a validity test from 3 experts obtained a value of 0.96 with a very valid category, the practicality test of 8 practitioners obtained a value of 0.95 with a very high category, and the effectiveness test of 11 assessors obtained a value of 0, 90 with very effective category.
PROTOTIPE APLIKASI PENGENALAN WAYANG KULIT MENGGUNAKAN CNN BERBASIS VGG16 dwi puji prabowo; D.I.I Ullumudin; R.A. Pramunendar
Jurnal Informatika Upgris Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.10485

Abstract

Indonesia has various types of culture and traditional arts. In this era of globalization, local culture and arts have begun to be eroded by the times. One of the diverse Indonesian culture is wayang kulit. Where the shadow puppets in Indonesia vary and vary from region to region. In this case, the puppet characters have different forms and curves, so recognizing the shape of a puppet is very difficult. In the development of technology, computer vision technology began to be widely used to perform object recognition with deep learning learning. So that an object being studied can be detected properly. In this study, a prototype was made with the detection of puppet types using Deep Learning learning using Convolutional Neural Networks to detect shadow puppet objects based on the VGG16 architecture. The results obtained by the CNN and VGG16 methods reached 86%. With the results obtained, a prototype model is made which will later be able to help the community in the introduction of shadow puppets.Keyword: CNN, shadow puppets ,VGG16
Implementasi Algoritma Brute Force Dalam Pencocokan String Pada Aplikasi Pencarian Musik Kana Saputra S; M. Hafizh Al-Areef; Nazifatul Fadhilah; Muhammad Rifqi Naufal; Muhammad Rifqi Maulana; Muhammad Fajar Harahap
Jurnal Informatika Upgris Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.8464

Abstract

Musik adalah hal yang sering kita jumpai dalam kehidupan sehari-hari. Banyak kegiatan sehari-hari kita yang ikut ditemani dengan musik. Aplikasi musik berbasis web ini dapat membantu pengguna dalam pencarian informasi mengenai suatu musik, seperti judul, album, artis, dan liriknya. Sebelumnya pencarian lirik lagu berdasarkan judul lagu, penyanyi adalah hal yang sulit. Penelitian ini bertujuan untuk membuat aplikasi pencarian lirik lagu dengan menerapkan algoritma brute force sebagai fitur pencari. Pengguna hanya memasukkan judul lagu atau lirik lagu atau nama penyanyi untuk melakukan pencarian. Algoritma brute force cocok digunakan dalam kasus pencocokan string dalam pencarian informasi mengenai musik yang dilihat dari sisi efektifitas dan efesiensi waktu.
Evolusi Cipher Vigenere dalam Peningkatan Pengamanan Informasi Eka Ardhianto; Widiyanto Tri Handoko; Edy Supriyanto; Hari Murti
Jurnal Informatika Upgris Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.9333

Abstract

Pertukaran informasi melalui ruang publik masih menyisakan kerentanan keamanan, sehingga perlu mekanisme pengamanan melalui proses kriptografi. Salah satu model kriptografi yang dapat bertahan hingga lebih dari 300 tahun adalah Vigenere Cipher, sebelum dipecahkan oleh Kasiski dan Friedman. Artikel ini membahas tentang perkembangan dan evlolusi Vigenere Cipher. Hingga saat ini, penggunaan Vigenere Cipher masih dapat diaplikasikan untuk mengamankan petukaran informasi dan transaksi komunikasi. Dalam perkembangannya, bentuk evolusi pada Vigenere terfokus pada tiga bagian, pengembangan dengan metode hibrid, pengembangan pada proses penerbitan kunci yang digunakan dan pengembangan pada jumlah karakter set yang digunakan pada Vigenere. Dengan pengembangan pada ketiga fokus tersebut, maka Vigenere Cipher mampu menyuguhkan tingkat keamanan yang lebih baik pada informasi yang disandikannya. Keuntungan lain adalah Vigenere Cipher dengan pengembangan ini dapat diaplikasikan dan diterima untuk pengamanan dan pertukaran infomasi pada bidang yang lebih luas
PENGEMBANGAN POLYCLINIC MOBILE APPLICATION UNTUK MENINGKATKAN PELAYANAN KESEHATAN PADA MASYARAKAT PEKERJA Andi Setiyadi; Endro Dwi Wuryanto
Jurnal Informatika Upgris Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.9500

Abstract

The use of mobile devices is increasingly popular. Mobile devices are increasingly equipped with advanced hardware and software technology. With dynamic performance and practical on mobile devices can master the development of the world ICT industry (information and communication technology). Software has become one of the spearheads of mobile success device. The creation of application programs is an important breakthrough in mobile development device. Likewise, the development of the Polyclinic Mobile Application in lecturer research This beginner is to provide solutions to problems that exist at the polyclinic at environment of PT. Eka Sandang Duta Prima Semarang, which is not yet supported by ICT, so in providing health services to the community, workers who are less than optimal can resolved. In developing the Polyclinic Mobile Application, it is not only a registration feature only, but there are several other features that were developed such as; polyclinic profile, schedule practice, modern queuing system, recording medical records, view patient history, take notes medical action, noting the drug administered.
Sistem Pendukung Keputusan Untuk Menentukan Customer Segment Pasar Salah Satu UMKM Di Bandung ( Foodendez ) Dengan Metode Decision Tree Dewayana, Baramukti
Jurnal Informatika Upgris Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.8987

Abstract

                                                Abstract  Foodendez is a UMKM in Bandung which is well known for its products, namely Uthi & Mies Krispi Patin Fish Skin which is a best seller product at Foodendez. This business has been running for about 5 years.In these 5 years Foodendez already has its own customer / market segment for the sale of this Foodendez product, however, this Foodendez has a problem predicting the customer / market segment for product sales from Foodendez, this is not suitable. expected expectations, because in analyzing / predicting customers / market segments still using a simple method or it can only be said to only use initial predictions by guessing roughly what estimates are known from the business plan or by other methods that make this Foodendez product get the wrong customer / segment that market It is expected that before hand or can be said to change and have an effect which makes Foodendez's turn over change insignificantly, and until recently Foodendez has not had a customer / market segment that is truly significant or as expected, for example is the sale of Krispi Patin Fish Skin that is predicted by the customer. the segment is more people > 18 years old but it turns out that < 18 years old people also like Krispi Patin Fish Skin products and offline and online sales where it is predicted that online sales will get a significant gain, which turns out to be more income in offline sales. So the authors provide a solution with the design / scheme of Decision Support Systems that will determine the customer segment and market segment which will later find out which market segment and customer segment are more significant and know which targets are suitable for products from Foodendez so that Foodendez UMKM can know what steps must be taken to set clear and significant targets by looking at the results of the percentage of enthusiasts and the turnover given by the Decision Tree method. The method of activities carried out is taken by collecting data with the interview method. The result of this activity is a Decision Support System design / scheme where the design / scheme is the result of determining a more detailed and significant customer segment / market segment and according to what the owner of Foodendez UMKM wants. Keywords : Foodendez , Uthi & Mies, Decision Tree , Customer Segment , Market Segment
PREDIKSI JUMLAH PRODUKSI AIR PDAM MENGGUNAKAN METODE ANN DENGAN OPTIMASI PSO ahmad akrom; R.A. Pramunendar; D.P. Prabowo
Jurnal Informatika Upgris Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.10065

Abstract

Perusahaan Daerah Air Minum (PDAM) merupakan perusahaan milik daerah yang begerak di bidang penyedia, pengolahan, dan pendistribusian air bersih. Sebuah sistem yang akurat untuk prediksi jumlah produksi air untuk masa depan dibutuhkan oleh PDAM untuk menentukan kebijakan dalam bidang produksi air. Penelitian ini menghasilkan sebuah model prediksi untuk  volume produksi air PDAM Kota Semarang. Data yang diolah adalah jumlah penduduk, jumlah pelanggan berdasarkan jenis pelanggan, total volume produksi, kontribusi daerah sumber, volume distribusi, air terjual, dan kehilangan air. Data diperoleh dari laporan bulanan perusahaan selama 6tahun terakhir yaitu mulai tahun 2008-2013. Pendekatan yang digunakan untuk prediksi volume produksi air adalah dengan menggunakan metode Artificial Neural Network dengan optimasi Particle Swarm Optimation. Berdasarkan hasilpenelitian, diperoleh hasil prediksi menggunakanneural network dan particle swarm optimization lebih bagus jika dibandingkan dengan menggunakan neural network saja. Hal ini dibuktikan dengan nilai RMSE menggunakan neural network dan particle swarm optimization sebesar 3,797 sedangkan nilai RMSE dengan neural network saja sebesar 4,943.

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