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All Journal Jurnal Simetris Register: Jurnal Ilmiah Teknologi Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika JTT (Jurnal Teknologi Terpadu) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Indonesian Journal of Artificial Intelligence and Data Mining JRST (Jurnal Riset Sains dan Teknologi) Jambura Geoscience Review Jambura Journal of Informatics JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Journal La Sociale Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Bureaucracy Journal : Indonesia Journal of Law and Social-Political Governance Jurnal Teknologi Informasi Cyberku Jurnal Ilmu Komputer Jurnal Sains dan Teknologi Prohealth Journal
Mohamad Ilyas Abas
Universitas Muhammadiyah Gorontalo
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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ANALYSIS OF COVID-19 GROWTH TRENDS THROUGH DATA MINING APPROACH AS DECISION SUPPORT Abas, Mohamad Ilyas; Ibrahim, Irawan; Syahrial, Syahrial; Lamusu, Rizal; Baderan, Umar Sako; Kango, Riklan
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.11861

Abstract

This study aims to analyze the growth trend of covid-19 using prediction algorithms in data mining for covid-19 data throughout Indonesia. This can be used as a decision support to analyze several government policies towards regulatory intervention so far. The method used is the best prediction method in time series data, including Neural Network, SVM, Linear Regression, K-Neirest Neighborn and optimizes it with optimization algorithms. This research is focused on the application of these applications. It is hoped that this research will produce an analysis of the growth trend of Covid cases every day, in addition to its contribution so that it can assist the government in determining the best policy direction and also as an education to the public. in addition, the research will contribute to science in the field of predictive analysis by finding the best RMSE formulation. The results of this study show that Neural Network-Particle Swarm Optimization has the smallest Roort Mean Square Error which is 265,326, and the two Neural Network Genetic Algorithm are 266.801, Neural Network Forward Selection is 275,372 and Neural Network without optimization has the largest RMSE which is 297.204. These results can be used as a reference for the use of similar algorithms in time series data, both Covid-19 data and other data.
OPTIMIZING PRODUCTION PROCESS BY INTEGRATING 3D MANUFACTURING TECHNOLOGY USING AUTODESK INVENTOR SOFTWARE TO IMPROVE EFFICIENCY Chandra, Muhammad Ali; Isminarti, Isminarti; Fauziah, Fauziah; Mulyadi, Yahya Bin; Abas, Mohamad Ilyas
Jurnal Ilmu Komputer (JUIK) Vol 4, No 3 (2024): October 2024
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v4i3.3460

Abstract

The concepts of efficiency and quality represent pivotal dimensions within contemporary manufacturing sectors. The amalgamation of manufacturing technology with design software, alongside the deployment of 3D scanning technology, is instrumental in the realization of these objectives, particularly within the framework of Industry 4.0. This investigation delves into the synthesis of manufacturing technology with design software and the utilization of 3D scanning technology in relation to Industry 4.0. More precisely, this research seeks to ascertain the most recent innovations in technology integration while assessing the advantages and obstacles associated with 3D scanning technology in the manufacturing domain. A methodological approach encompassing a literature review in conjunction with case studies is employed. Case studies were executed at PT. Metalindo Teknik Utama, a manufacturing entity, to examine the practical implications of technology integration.Qualitative analysis is used to identify patterns and critical findings. The study reveals significant advancements in technology integration, particularly in CAD, CAM, IoT, and IIoT, contributing to increased production efficiency and responsiveness to market changes. Additionally, Autodesk Inventor applications show potential in enhancing product design, evaluation, and production processes. These findings suggest that the integration of technology with design software and the adoption of 3D scanning technology have the potential to revolutionize the manufacturing process, improving efficiency and quality. This study emphasizes the importance of integrating manufacturing technology with design software and adopting 3D scanning technology in the manufacturing industry. Insights gained from this research provide valuable guidance for industry practitioners in optimizing production processes and remaining competitive in the era of Industry 4.0.
SISTEM INFORMASI PENCARIAN JASA TUKANG BANGUNAN Polapa, Risman; Abas, Mohamad Ilyas; Handayani, Tri Pratiwi; Lasarudin, Alter
Jurnal Ilmu Komputer (JUIK) Vol 4, No 3 (2024): October 2024
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v4i3.3477

Abstract

This research aims to design a Web-based Building Services Search Information System and implement a Web-Based Building Builder Services Search Information System. This research was developed using the Rapid Application Development (RAD) method. In RAD, users and analysts participate in three stages. The three stages are implementation, RAD design and requirements planning. With these stages, the application of the RAD method is very appropriate and suitable for developing website-based systems. The results of this research were that the researcher had previously conducted an interview with one of the head builders. Craftsmen in their profession as builders are to get work that suits their skills, only certain people know and understand the workman's performance, what field the craftsman is skilled in, so if there is a special job that must be done by a craftsman that suits his skills. So the employer must meet the craftsman directly and ask about the craftsman's skills. Conclusion: We have succeeded in designing a web-based information system for searching for construction services, able to make it easier for customers (employers) to search for construction services according to the skills required by customers (employers), as well as making it easier for builders to find work that suits the craftsman's skills. With this information system, it can help builders and customers (employers) in the process of searching for builders according to their expertise in the form of the Web or other web browsers.
KONSTRUKSI ALGORITMA PEWARNAAN TITIK PELANGI PADA GRAF POHON Pranata, Widya Eka; Abas, Mohamad Ilyas; Ibrahim, Irawan; Lamusu, Rizal; Syahrial, Syahrial
Jurnal Ilmu Komputer (JUIK) Vol 5, No 1 (2025): February 2025
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v5i1.3839

Abstract

This study constructs an algorithm for rainbow vertex coloring in tree graphs. A graph G is defined as a set pair G=(V,E), where V is the vertex set and E is the edge set. Rainbow dot coloring aims to assign a color to each vertex of a tree graph T, such that each path in the tree has vertices with unique colors. The rainbow dot coloring algorithm developed in this study is implemented in a programming language, and its performance is evaluated through simulations on various types of tree graphs. The results show that this algorithm can effectively color tree graphs with good optimality. This research contributes to graph coloring theory and its potential to be applied to computational problems involving tree graphs with complex structures.
RANCANG BANGUN PENGATURAN PAKAN IKAN NILA BERBASIS INTERNET OF THINGS Mahendra, Bachtiar Isra; Abas, Mohamad Ilyas; Syahrial, Syahrial; Pranata, Widya Eka
Jurnal Ilmu Komputer (JUIK) Vol 5, No 1 (2025): February 2025
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v5i1.3899

Abstract

Budidaya ikan, khususnya nila, adalah salah satu sektor penting dalam industri makanan Indonesia. Pakan ikan nila secara teratur dan akurat adalah cara terbaik untuk meningkatkan pertumbuhannya. Mengelola pemberian pakan secara teratur masih menjadi tantangan bagi banyak peternak ikan, terutama mereka yang sering bepergian atau tidak dapat mengakses kolam secara langsung. Oleh karena itu, tujuan proyek ini adalah untuk membuat sistem pemberian pakan ikan nila yang berbasis Internet of Things (IoT) dan dapat dikendalikan melalui aplikasi Android. Sistem ini akan menggunakan modul ESP8266 dan teknologi mikrokontroler untuk memantau kondisi kolam secara jarak jauh dan secara otomatis mengatur pemberian pakan. Penelitian ini juga berusaha mengoptimalkan jadwal pemberian pakan dan jumlah pakan yang tepat untuk meningkatkan keberlanjutan dan efisiensi budidaya ikan nila. Penelitian ini diharapkan akan membantu petani ikan meningkatkan kualitas dan produktivitas hasil panen mereka dengan cara yang lebih ekonomis dan bertanggung jawab secara ekologis. Teknologi otomatis ini memungkinkan petani ikan menghemat waktu dan tenaga sambil menjamin pertumbuhan ikan yang lebih baik dan mengurangi efek buruk dari pemberian pakan berlebihan.
KLASIFIKASI KUALITAS TELUR BERDASARKAN KERABANG MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Daulima, Mohamad Rizki; Syahrial, Syahrial; Abas, Mohamad Ilyas; Pranata, Widya Eka; Ibrahim, Irawan
Jurnal Ilmu Komputer (JUIK) Vol 5, No 1 (2025): February 2025
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v5i1.3953

Abstract

Telur ayam merupakan salah satu bahan pangan yang banyak digemari oleh masyarakat dan memiliki kandungan nutrisi yang sangat dibutuhkan tubuh. Kualitas telur sangat dipengaruhi oleh faktor internal dan eksternal, yang dapat memengaruhi kesegarannya. Penurunan kualitas telur sering disebabkan oleh kerusakan fisik, kontaminasi mikroba, serta kondisi penyimpanan yang tidak tepat. Salah satu bentuk kerusakan yang umum adalah keretakan pada kerabang telur, yang dapat membuka celah bagi masuknya bakteri berbahaya seperti Salmonella. Oleh karena itu, penting untuk melakukan identifikasi kualitas telur secara akurat, terutama untuk mencegah kerugian ekonomi pada peternak dan menjaga kesehatan konsumen. Salah satu metode yang efektif untuk mengidentifikasi kualitas telur adalah dengan menggunakan teknologi pengolahan citra digital, khususnya melalui penerapan Convolutional Neural Network (CNN). Penelitian ini bertujuan untuk mengembangkan dan menerapkan metode CNN dalam mengklasifikasikan kualitas telur ayam berdasarkan kondisi kerabangnya. Dengan menggunakan citra digital yang diambil melalui kamera handphone, diharapkan penelitian ini dapat memberikan solusi praktis dalam klasifikasi kualitas telur, baik untuk konsumsi maupun distribusi di pasar. Hasil yang diharapkan dari penelitian ini adalah tercapainya tingkat akurasi yang tinggi dalam identifikasi kualitas telur, yang dapat mempermudah proses seleksi telur oleh peternak dan konsumen.
Digital Library Universitas Muhammadiyah Gorontalo Antupetu, Rastin; Abas, Mohamad Ilyas; Lasarudin, Alter; Lamusu, Rizal
Jurnal Ilmu Komputer (JUIK) Vol 4, No 1 (2024): FEBRUARY 2024
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v4i1.2797

Abstract

This research was conducted at the Library of Universitas Muhammadiyah Gorontalo. The aim is to design a web-based library information system with a digital concept (Digital Library). The design of the Digital Library information system of Universitas Muhammadiyah Gorontalo, with a system design model using the prototyping model, provides a forum for students and lecturers, especially those on the campus of Universitas Muhammadiyah Gorontalo to publish research results in the form of theses, journals, and theses into this digital library system. With this digital library it will facilitate access for prospective graduates, both the academic community and academics outside the campus, who will take literature as a reference for the final report or thesis. Provide convenience in disseminating useful information or knowledge and help students conduct research.
Analisis Tingkat Kepuasan Pengguna Sistem Informasi Elektronik Kinerja Asn (SI – EKA) Di Kementerian Agama Menggunakan Metode Webqual Sulistyawati, Ni Kadek; Hasyim, Wahyudin; Maku, Rubiyanto; Abas, Mohamad Ilyas
Jurnal Ilmu Komputer (JUIK) Vol 4, No 1 (2024): FEBRUARY 2024
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v4i1.2804

Abstract

Penelitian ini bertujuan untuk mengetahui kepuasan pengguna terhadap kualitas sistem informasi SI – EKA di kementerian agama menggunakan metode webqual . Teknik analisis yang digunakan analisis adalah kuantitatif, Metode yang digunakan adalah webqual .Teknik yang digunakan dalam menentukan ukuran sampel dari suatu populasi yaitu teknik slovin .Sampel pada penelitian ini sebanyak 155 sampel penelitian ini adalah Pada hasil analisis deskriptif memperoleh nilai persentase untuk kategori setuju dengan persentase Sebesar 42,58% yang dapat disimpulkan berarti sebagian besar pegawai setuju dengan peryataan mengenai kepuasan pegawai terhadap sistem informasi SI – EKA. Dari hasil yang diperoleh dapat dilihat bahwa pengguna merasa sistem informasi SI – EKA mudah untuk digunakan dan sistem informasi SI – EKA mempunyai kualitas yang sangat baik.
Comparative Analysis of CNN-LSTM and LSTM Models for Cyberbullying Detection with Increasing Dataset Sizes Handayani, Tri Pratiwi; Abas, Mohamad Ilyas
Jurnal Ilmu Komputer (JUIK) Vol 4, No 2 (2024): JUNE 2024
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v4i2.3185

Abstract

This study compares the performance of two deep learning models, CNN-LSTM and LSTM, for identifying cyberbullying in social media text. Three distinct dataset sizes are used for our evaluation and comparison: 1,000, 5,000, and 10,000 samples. The results indicate that the CNN-LSTM model outperforms the LSTM-only model (Ablation model) for the largest dataset size, exhibiting substantial enhancements in accuracy, precision, recall, and F1-Score as the dataset size increases. The Ablation model exhibits competitive performance and slightly superior results on the mid-sized dataset. However, it inevitably falls behind the CNN-LSTM model when trained on 10,000 samples. These findings imply that increasing the complexity of the CNN layer in the CNN-LSTM model improves its ability to collect significant features in bigger datasets, making it more successful for cyberbullying detection. 
Comparison of Convolutional Neural Network Methods for the Classification of Maize Plant Diseases Abas, Mohamad Ilyas; Syafruddin Syarif; Ingrid Nurtanio; Zulkifli Tahir
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 10 No 1 (2024): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v10i1.3656

Abstract

The focus of this study is the classification of maize images with common rust, gray leaf spot, blight, and healthy diseases. Various models, including ResNet50, ResNet101, Xception, VGG16, and ENet, were tested for this purpose. The dataset used for corn plant diseases is publicly available, and the data were split into separate sets for training, validation, and testing. After processing the data, the following models were identified: the Xception model epoch with an accuracy of 83.74%, the ResNet model with an accuracy of 97.19% at epoch 8/10, the ResNet101 model with an accuracy of 97.55% at epoch 10/10, and the ENet model with an accuracy of 98.69% at epoch 9/1000. ENet exhibited the highest accuracy among the five models at 98.69%. Additionally, ENet achieved an average accuracy of 95.45%, the highest among all tested models, based on the average accuracy in the confusion matrix. This research indicates that ENet performs best at processing data related to maize plant diseases. Consequently, the analysis of maize plant diseases is expected to evolve as a result of this research. Following the implementation of the system's generated model, this research will continue to explore its impact. The intention is to provide a summary of the comparative classification performance of CNN algorithms.
Co-Authors Abdul Syukur Alter Lasarudin Antupetu, Rastin Asminar Asminar Chandra, Muhammad Ali Daulima, Mohamad Rizki Deny Wiria Nugraha Dewa Oka Suparwata Fauziah Fauziah Gani, Hilmansyah Handayani, Tri Pratiwi Hasto Finanto Hasyim, Wahyudin Hidayat, Rahmat Rian Hiola, Fidya Ibrahim, Irawan Ingrid Nurtanio Ismet Hadi Isminarti, Isminarti Kango, Riklan Kiayi, Verliana Koto, Arthur Gani Lamusu, Rizal Lasarudin, Alter Lasarudin, Alter Mahendra, Bachtiar Isra Maku, Rubiyanto Masri, Muhamad Moch Arief Soeleman Moh. Nasrul Arief Setiawan Adam Mohamad, Irwansyah Reza Muhammad Raidinoor Pasha Mulyadi, Yahya Bin Muslim Panigoro Noor Fatmawanti Ahmad Noviyanti, Upik Dyah Eka Nur Azhary Iriawan Eka Putra Nurhikmah Fajar Nursetiawati Nursetiawati Nurwahidah Jamal Panigoro, Muslim Polapa, Risman Pranata, Widya Eka Rahmatia Mohi Rizal Lamusu Rizal Lamusu Rizal Lamusu Salahudin Pakaya Silvana Yusuf Sulistyawati, Ni Kadek Syafruddin Syarif SYAHRIAL SYAHRIAL Syahrial Syahrial Tri Pratiwi Handayani Umar Sako, Umar Umar, Siskawati Wahyudin Hasyim Yulanda Yunus Yulianita, Fani Zulkarnain Suronoto Zulkifli Tahir