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All Journal Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Bulletin of Computer Science Research KOMMAS: Jurnal Pengabdian Kepada Masyarakat OKTAL : Jurnal Ilmu Komputer dan Sains
Bobi Agustian
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Astronomy Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

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Perancangan Sitem Pendukung Keputusan Menggunakan Metode SAW (Simple Additive Weighting) Menentukan Guru Terbaik Berbasis Web Di SMK Ki Hajar Dewantoro Rofi Kamdani; Bobi Agustian
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol 3, No 2 (2022): MAY
Publisher : Journal of Artificial Intelligence and Innovative Applications (JOAIIA)

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Abstract

Pengambilan keputusan adalah suatu pendekatan pada suatu masalah, pengumpulan fakta-fakta, penentuan yang matang dari alternatif yang dihadapi dan pengambilan tindakan berdasarkan perhitungan yang paling tepat. Penilaian guru terbaik menjadi salah satu cara untuk menentukan guru yang terbaik diantara beberapa guru. SMK KI Hajar Dewantoro masih menggunakan cara yang subjektif atau manual sehingga proses penilaian guru menjadi lambat dan tidak akurat dalam pengambilan keputusan untuk menentukan guru terbaik. Untuk membantu dan memberikan solusi dalam permasalahan diatas, maka diperlukan suatu sistem yang memudahkan untuk penilaian kinerja guru.Proses yang dilakukan untuk menentukan guru terbaik aladah dengan kriteria yang ditentukan oleh pihak sekolah tersebut. Kriteria yang digunakan harus bersifat objektif dan kuantitatif agar hasilnya dapat dihitung dan dapat dirangkingkan. Pada penelitian ini penulis menggunakan metode  Simple Additive Weighting (SAW) untuk menentukan keputusan pemilihan guru terbaik. Metode Simple Additive Weighting (SAW) dapat menentukan nilai bobot untuk setiap atribut, lalu menentukan proses perangkingan dengan cara menyeleksi alternatif terbaik dari beberapa alternatif yang ada berdasarkan kriteria-kriteria yang telah ditentukan dan medapatkan hasil akhir yaitu perangkingan. Dengan proses perangkingan tersebut diharapkan penilaian akan lebih akurat dan efesien.
IMPLEMENTASI DAN SOSIALISASI PENGGUNAAN GOOGLE CLASSROOM UNTUK MEDIA PEMBELAJARAN ONLINE DIMASA PANDEMI PADA SMK NUFA CITRA MANDIRI Muhamad Meky Frindo; Petricia Oktavia; Fajar Agung Nugroho; Bobi Agustian; Muhamad Yasser Arafat
KOMMAS: Jurnal Pengabdian Kepada Masyarakat Vol 2, No 2 (2021): KOMMAS: JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : KOMMAS: Jurnal Pengabdian Kepada Masyarakat

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Abstract

Berdasarkan dalam perkembangan teknologi informasi dan internet yang sangat pesat,  menjadikan   perkembangan di bidang pendidikan pun ikut mengalami perkembangan. Terutama metode pembelajaran yang dilakukan secara online yang biasa disebut dengan e-learning. Salah satunya dengan pemanfaatan aplikasi google classroom. Dalam  pemanfaatan aplikasi google classroom menjadikan pembelajaran lebih efektif dan efesien dikarnakan guru dan siswa bisa setiap saat bertatap muka secara online di aplikasi google classroom, dan juga siswa nantinya dapat belajar, menyimak, membaca, mengirim tugas, dari jarak  jauh dimasa pendemi seperti saat ini. Oleh karena dalam pengabdian kepada masyarakat ini  bertujuan  untuk memberikan  edukasi mengenai pembelajaran dan serta workshop tentang optimalisasi dalam pembelajaran dengan menggunakan  google classroom di lingkungan SMK Nufa Citra Mandiri. Diharapkan dengan adanya pengabdian kepada masyarakat ini dapat membantu guru dan siswa dalam belajar mengajar menggunakan media aplikasi google  classroom.Kata kunci: Teknologi, Google Classroom, Pengabdian, SMK Nufa Citra Mandiri
Pengenalan Lingkungan Kampus Universitas Pamulang Secara Interactive Menggunakan Virtual Tour (VR) Berbasis Website Muhamad Abdul Aziz; Bobi Agustian
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 2 No 08 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

This study aims to create a website-based virtual tour application that aims to facilitate the introduction of the Pamulang university campus, especially the Viktor campus to prospective students who want to know the location of the campus without having to come to the location. This development research adapts the MDLC (Multimedia Development Life Cycle) development model where this development model has six main stages, namely (1) Concept, is conceptualizing and looking for initial needs for making virtual tour applications, (2) design, is the stage of making a mochup or User Interface that later it will be used in virtual tour applications, (3) collecting material, is stage of collecting datas needed for making this virtual tour application which includes taking 360 pictures and several other assets, (4) assembly is development stage, in this case focusing on Pano2VR application and the Ionic Framework, (5) testing this stage using the Blackbox Testing method, (6) distribution to make it easier for users later, distribution is done by uploading HTML5 files to Hosting.
Penerapan Kombinasi Metode AHP MOORA Pada Sistem Pemilihan Wedding Organizer (WO) di Daerah Bogor Arif Maulana; Bobi Agustian
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 2 No 10 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Wedding Organizer is one of the media that can help the bride and groom in solving problems related to the wedding, and can provide solutions or suggestions about the problems being faced by the bride and groom it can give satisfaction to the bride and groom who will hold a wedding, because it can provide rational consideration. Many people in the Bogor area have difficulty in making choices in using the services of a wedding organizer in accordance with the desired needs, with considerations such as the budget of the bride and groom, the concept of the wedding and so forth. From the problems that occur required a system that can provide decisions and is able to assist the public in determining the selection of wedding organizer services as needed. In this study applied a combination of two methods of SPK is AHP (Analityc Hierarchy Process) and MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis). Based on the test results obtained by the percentage of UAT 73%, so the system is feasible to use. The system successfully implemented SPK by combining AHP and MOORA methods, and obtained a consistency index value of 0.1 and a consistency ratio of 0.08 so that it can be concluded that the criteria used are consistent.
SISTEM INFORMASI INVENTORY ALAT KESEHATAN PADA PT TAISHAN ALKES INDONESIA BERBASIS WEB Hari Gunawan; Bobi Agustian
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 01 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Information system inventory Medical deviceat PT. Taishan Alkes Indonesia is currently still using it manually, namely by recording books and copied using Microsoft Excel. thus causing errors in recording medical device data, both incoming and outgoing medical devices causing difficulties in finding available stock data. The purpose of this study is to provide convenience in processingdata inventory medical deviceso as to minimize errors in data input, data loss, save time and make it easier to find available stock data. With the existence of this web-based application, it can overcome problems in processing data on the safety equipment at PT. Taishan Alkes Indonesia because the data is well organized. This system is designed using the codeigniter framework and MySQL programming as the database.
Server Dengan NodeMCU ESP8266 Berbasis Internet Of Things (IoT) Pada PT PLN Batam Ferianto; Bobi Agustian
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 01 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

The development of technology and science is currently growing rapidly. This is done with the aim of simplifying daily human work. Creating tools to be able to help and facilitate humans in carrying out their duties or lighten the human burden. This technology will involve microcontrollers and sensors. So the purpose of doing this research is to create a server room temperature control system based on the Internet of Things (IoT). The temperature controller automatically uses the DS18B20 sensor as a temperature gauge and a fan, as well as a buzzer as a sound notification if the temperature is more than the set temperature. The method used in the server room temperature monitoring system is using ADDIE. By specifying membership and rules in ESP8266 as the brain, it can set the temperature value. In the blynk system, it can produce output in the form of a graph of the server room temperature. The expected result is that if the temperature exceeds the set limit, the fan will spin and there will be a notification.  
Klasifikasi Citra Medis Penyakit Pneumonia dengan Metode Convotional Neural Network Khairudin; Bobi Agustian; Nursakinah, Badriah
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.576

Abstract

Pneumonia is a pulmonary infection that remains one of the leading causes of death among children under five, especially in developing countries. Early detection and rapid diagnosis are critical in managing this disease, particularly in regions with limited access to medical professionals. This study aims to develop an automatic classification system for pediatric chest X-ray images using the Convolutional Neural Network (CNN) method to detect pneumonia. The dataset used consists of 5,863 pediatric chest X-ray images categorized into two classes: Pneumonia and Normal. The images underwent preprocessing stages including resizing, normalization, augmentation, and noise removal. The CNN architecture includes stacked convolutional layers, max pooling, dropout, and a fully connected layer with sigmoid activation. The model was trained using 80% of the data for training, 10% for validation, and 10% for testing. Performance was evaluated using accuracy, precision, recall, and F1-score metrics. Evaluation results showed that the model achieved over 93% accuracy, with 92.5% precision, 94.2% recall, and an F1-score of 93.3%. Transfer learning using pretrained models (VGG16 and ResNet50) further improved performance. These findings demonstrate that CNN is an effective tool for medical image classification and has strong potential to support fast and accurate pneumonia diagnosis, especially in resource-limited healthcare settings.
Klasifikasi Gender Berbasis Citra Wajah Menggunakan Clustering Dan Deep Learning Okky Prasetia; Syaeful Machfud; Rosyani, Perani; Bobi Agustian
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.581

Abstract

Gender classification based on facial images is a significant challenge in the field of computer vision, especially when dealing with unstructured data sourced from social media platforms. This study proposes an integrated approach combining facial image preprocessing, clustering methods, and deep learning to enhance the accuracy of gender classification. The dataset used was obtained from a Big Data Competition and consists of male and female face images sourced from Instagram. Preprocessing was performed using OpenCV for face detection and cropping. Subsequently, the data were clustered using K-Means and DBSCAN algorithms to reduce noise and redundancy. Gender classification was then conducted using a sequential learning model based on Inception_v3, enhanced with Agglomerative Clustering for feature refinement. The evaluation of the system demonstrated strong performance with an accuracy of 92.97%, F1-score of 0.89556, precision of 0.97727, and recall of 0.83069. These results confirm that the integration of clustering techniques and deep learning significantly improves the effectiveness of gender classification based on facial images, especially for open-source and non-curated datasets.
Co-Authors Arif Maulana Fajar Agung Nugroho Ferianto Hari Gunawan Khairudin Muhamad Abdul Aziz Muhamad Meky Frindo Muhamad Yasser Arafat Nursakinah, Badriah Okky Prasetia Perani Rosyani Petricia Oktavia Rofi Kamdani Syaeful Machfud