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Logarithm Decreasing Inertia Weight Particle Swarm Optimization Algorithms for Convolutional Neural Network Murinto Murinto; Miftahurrahma Rosyda
JUITA : Jurnal Informatika JUITA Vol. 10 No. 1, May 2022
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1285.081 KB) | DOI: 10.30595/juita.v10i1.12573


The convolutional neural network (CNN) is a technique that is often used in deep learning. Various models have been proposed and improved for learning on CNN. When learning with CNN, it is important to determine the optimal parameters. This paper proposes an optimization of CNN parameters using logarithm decreasing inertia weight (LogDIW). This paper is used two datasets, i.e., MNIST and CIFAR-10 dataset. The MNIST learning experiment, the CIFAR-10 dataset, compared its accuracy with the CNN standard based on the LeNet-5 architectural model. When using the MNIST dataset, CNN's baseline was 94.02% at the 5th epoch, compared to CNN's LogDIWPSO, which improves accuracy. When using the CIFAR-10 dataset, the CNN baseline was 28.07% at the 10th epoch, compared to the LogDIWPSO CNN accuracy of 69.3%, which increased the accuracy.
Prototype e-Report PAUD 1.0 untuk Menyusun Laporan Perkembangan Anak Usia Dini Prima Suci Rohmadheny; Intan Puspitasari; Miftahurrahma Rosyda; Avanti Vera Risti Pramudyani
Jurnal Obsesi : Jurnal Pendidikan Anak Usia Dini Vol 6, No 4 (2022)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/obsesi.v6i4.1643


Seiring dengan perkembangan teknologi, laporan perkembangan anak disusun dengan menggunakan aplikasi komputer. Namun, kesiapan guru PAUD dalam hal literasi komputer terbatas pada penggunaan Ms. Office (Ms. Word, Ms. Excel, dan Ms. Power Point) secara sederhana. Oleh karena itu, penelitian ini dilakukan untuk merancang prototype laporan perkembangan anak menggunakan Ms.Excel untuk menunjang pekerjaan guru PAUD. Penelitian dilakukan dengan metode RD modifikasi model Borg Gall sampai pada tahap validasi ahli uji coba terbatas terhadap pengguna. Sebanyak 24 guru PAUD Aisyiyah terlibat dalam uji coba terbatas. Data dikumpulkan menggunakan kuesioner respon pengguna dan dianalisis secara deskriptif. Hasil penelitian ini adalah prototype produk e-Report PAUD Aisyiyah Versi 1.0 berbasis Ms. Excel memiliki kelayakan segi materi 0,833-1,000 dan 0,5 – 1,000 dari segi teknologi komputer berdasarkan penilaian validasi ahli, sedangkan hasil ujicoba terbatas menunjukkan bahwa produk ini diterima dengan baik, mudah, pratis, dan efisien. Namun, beberapa perbaikan teknis masih terus dilakukan untuk menyempurnakannya
Sentiment Analysis Tweet Pilkada 2020 Saat Pandemik COVID-19 di Media Sosial Twitter Menggunakan Metode 1D Convolutional Neural Network Ganjar Tata Pangestu; Miftahurrahma Rosyda
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3765


Pilkada 2020 is a debate since it takes place in the midst of the COVID-19 pandemic. The emergence of comments from several social media such as Twitter. There are various public opinions that agree that the Pilkada will still be held, there are also other public opinions that support the postponement of the Pilkada until the COVID-19 pandemic ends. These different opinions require Sentiment Analysis which aims to obtain or find out the general opinion of the 2020 Regional Head Election during the Coronavirus pandemic. A total of 200 data in the form of tweets which are divided into 2 data, namely 20% test data and 80% training data obtained by retrieving data from Twitter using the twint library, based on predetermined keywords. The resulting data set is classified into three classes namely positive, neutral, and negative. In this test or research, deep learning uses the Convolutional Neural Network classification, because it has been proven effective in the case of natural language processing and can get good results in grouping sentences. From this research, the accuracy result is 72.50% with the epoch used is 25 epoch. From the increase in epochs, there is an increase in accuracy of 7-12% from the previous epoch variations.
Sistem Pendukung Keputusan Penentuan Profesi Mahasiswa Informatika Menggunakan Metode WP-RIASEC Raihan Aqila Taufik; Miftahurrahma Rosyda
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i3.4312


Informatic Program in Ahmad Dahlan University engaged in the field of informatics/computer science. At the Informatic Program in Ahmad Dahlan University, there are still many students who are confused when they want to decide which profession to pursue when they graduate. This is based on a questionnaire distributed to final semester students from the Informatics Program in Ahmad Dahlan University. From the distributed questionnaires, the results of the questionnaire were obtained, namely more than 50 percent of respondents were still confused in determining the professional field to be occupied when they graduated. In addition, in an interview conducted with a psychologist, he said that personality is very influential on a person's work. To help Ahmad Dahlan University Informatics Students in determining a profession, a decision support system was created that can help students of the department in determining the appropriate professional field based on the value of the course and their personality. The method used in this research is WP and RIASEC. The WP method plays a role in calculating the weight of each course value. While the RIASEC method plays a role in determining a person's personality which is the basis for determining appropriate professional alternatives based on their personality. The results of system testing that have been carried out on 10 respondents consisting of 7 students and 3 alumni from the Informatics Program in Ahmad Dahlan University have obtained test results with a value of 84.5, which means the system is running well and meets the existing standards.
Sistem Pakar Skrining Gejala Gangguan Kepribadian Ambang Menggunakan Metode Certainty Factor MIftahurrahma Rosyda; Tri Suryo Wahyu Aji
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5150


Borderline Personality Disorder is a type of personality disorder characterized by an overall unstable personality pattern, excessive impulsivity, which often confuses sufferers with their own identity. An expert system is a system developed to assist in making decisions on a particular problem. This expert system aims to help screen symptoms of borderline personality disorder and provide solutions to relieve these symptoms. The method used by the expert system is the certainty factor. The expert system development stage uses the waterfall method and uses the PHP programming language. The results of this study are in the form of an accuracy value of 80% with test data of 10 people, these results are obtained by comparing the results of experts with the results of the system that has been designed