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All Journal Teika SISFOTENIKA Jurnal Komputer Terapan CogITo Smart Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) CSRID (Computer Science Research and Its Development Journal) SENSITEK JUSTIN (Jurnal Sistem dan Teknologi Informasi) Klabat Journal of Management SmartComp Servitium Smart Journal Jurnal Pengabdian Kepada Masyarakat Indonesia
Green Arther Sandag
Fakultas Ilmu Komputer - Universitas Klabat
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences

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Pengenalan Dan Pelatihan Pemrograman Bahasa Python Pada Smk Negeri 1 Sorong Sandag, Green Arther; Mambu, Joe Yuan; Mandias, Green; Waworundeng, Jacquline
Servitium Smart Journal Vol 2 No 2 (2024): Servitium Smart Journal
Publisher : Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/servitium.v2i2.26

Abstract

The world of education today cannot be separated from the influence of the development of information technology. Many students today get information related to technological developments from smartphones, websites, and video games. Learning at school also uses technology such as power point, zoom, and so on. Lately many schools and parents are encouraging children to learn programming. Programming is a way of giving commands to the computer to do something. There are several benefits in learning programming for students, such as sharpening the ability to communicate thoughts in a structured and logical manner, encouraging creativity, solving problems on their own, practicing communication skills, and teaching perseverance. Therefore, we introduce python programming at SMK Negeri 1 Sorong. The methods used during the programming training are the introduction of the python programming language, the practice of making simple programs, and the evaluation of students' abilities in programming the python programming language. During the training, it was found that the students had programmed before, but still had problems in writing the program. This training discusses programming syntax, variables, input, process, and output in python programming. The results of the evaluation in this activity students have understood the basic concepts of python programming with an average result of 80%.
Sentiment Analysis and Topic Detection on Post-Pandemic Healthcare Challenges: A Comparative Study of Twitter Data in the US and Indonesia Tangka, George Morris William; Chrisanti, Ibrena Reghuella; Waworundeng, Jacquline; Maringka, Raissa Camilla; Sandag, Green Arther
CogITo Smart Journal Vol. 10 No. 2 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i2.819.561-579

Abstract

This study examines public sentiment and key topics in Twitter discussions regarding the COVID-19 vaccine and the Omicron variant in the US and Indonesia. The importance of this research lies in understanding people's changing views on vaccination, especially in light of new virus variants. Using sentiment analysis with VADER and topic modeling with Latent Dirichlet Allocation (LDA), this research analyzes 637,367 tweets from the US and 91,679 tweets from Indonesia collected over two months from January 21 to February 21, 2022. The results reveal that US discussions on vaccines are predominantly positive, while those on Omicron are mostly negative. In contrast, discussions in Indonesia are largely neutral, followed by positive sentiment. Additionally, five main topics were identified for each country, with the US showing a broader range of vaccine-related discussions. These findings suggest that while the vaccine is seen as a source of hope in both countries, factors such as literacy, socioeconomic status, and education contribute to negative sentiment and vaccine resistance.
MRI Image Analysis for Alzheimer’s Disease Detection Using Transfer Learning: VGGNet vs. EfficientNet Sandag, Green Arther; Djamal, Eleonora; Tangka, George Morris William; Taju, Semmy Wellem
CogITo Smart Journal Vol. 10 No. 2 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i2.836.580-592

Abstract

This study focuses on developing an effective Alzheimer's disease (AD) classification model using MRI images and transfer learning. This research targets individuals aged 65 and above who are affected by the predominant form of dementia and utilizes an Alzheimer's Disease MRI Image dataset from Kaggle. Model selection involved options like EfficientNetB1, B3, B5, B7, VGG16, and VGG19. Two scenarios with distinct batch sizes (10 and 20) were explored in the model creation process. Evaluation, using a confusion matrix, determined that the EfficientNetB5 model yielded the highest accuracy at 99.22%, surpassing other models such as EfficientNetB1, B3, B7, VGG16, and VGG19. Notably, this research highlights the superior performance of EfficientNet over VGGNet in transfer learning for analyzing Alzheimer's disease MRI images. The study concludes with the implementation of a simple web system for testing model outcomes. Overall, the investigation underscores the efficacy of Convolutional Neural Network (CNN) modeling in Alzheimer's disease analysis and identifies EfficientNetB5 as the optimal model for accurate classification.
Pelatihan Penggunaan Content Management System dengan Wordpress untuk Website Umum dan Bisnis pada Siswa SMK Negeri 1 Sorong Joe Yuan Mambu; Green Sandag; Erienika Lompoliu; Green Mandias; Marchel Tombeng
Jurnal Pengabdian kepada Masyarakat Indonesia (JPKMI) Vol. 2 No. 3 (2022): Desember : Jurnal Pengabdian Kepada Masyarakat Indonesia (JPKMI)
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jpkmi.v2i3.676

Abstract

Website is one of the main components of the Internet, therefore those who are able to create website may able to influence, share, sell, advertise their or their company/organization content or products. Especially during the Covid-19 era everything information or business has become available online. This community service aimed to teach and bring awareness of CMS, a non coding method and system that can help user to create website quite fast. One of the advantages of WordPress is that it can be used for various websites and applications. For example, you can use WordPress to create a simple website, to a business website. For business websites, one of the plugin modules provided by WordPress is Woocommerce. With Woocommerce users can make WordPress display into an online store or online store quite easily. According to the questionnaire the training gave user a new perspective that creating and publishing website is isn’t that complicated after all when using Wordpress.
Prediksi Kelulusan Mahasiswa Dalam Memilih Program Magister Menggunakan Algoritma K-NN Mananta, Aldo Sabathos; Sandag, Green Arther
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 10, No 2 (2021): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v10i2.2488

Abstract

Kinerja akademik siswa didasarkan pada berbagai faktor seperti variabel pribadi, sosial, psikologis, dan lingkungan lainnya.  Banyaknya jumlah data yang dimiliki oleh pihak universitas mengenai mahasiswa lulusan mereka dapat membantu dalam proses pengambilan keputusan ke jenjang pendidikan yang lebih tinggi. Data akademik mahasiswa dapat diolah untuk membantu pengambilan keputusan dalam penentuan masuk ke jenjang perguruan tinggi selanjutnya. Untuk melakukan proses pengolahan data tersebut di butuhkan metode data mining yaitu klasifikasi. Aspek yang dilihat yaitu dari sisi accuracy, precision dan recall. Software yang digunakan untuk mengetahui kinerja dari algoritma tersebut adalah Rapid Miner Studio versi 9.2. Hasil pengujian menunjukkan bahwa algoritma K-NN dengan menggunakan independent test memiliki accuracy terbaik yaitu sebesar 96.25%, precision 98.08%, dan recall 70.00%. Sedangkan pada test yang menggunakan cross-validation, algoritma K-NN juga memiliki accuracy terbaik yaitu sebesar 91.88%, precision 81.29, dan recall 61.15%.Kata kunci: Prediksi, Kelulusan Mahasiswa, K-NN
Co-Authors Aldo Sabathos Mananta Andrew Tanny Liem Anggreiny Rolangon arlius lalong Aror, Megalita Axcel Weku Chrisanti, Ibrena Reghuella Deo Timothy Kabo Diaprilia Sondakh Djamal, Eleonora Djimesha, Enrico S. Edson Yahuda Putra Erienika Meiling Lompoliu Fini Keni Celsia George Morris William Tangka Godlife Davidson Rellely Grady Wantah Green Ferry Mandias, Green Ferry Haryanto Reza Musak Jacquline Waworundeng Jebriella Bororing Joe Yuan Mambu Jonathan Leopold Kaunang, Fergie Joanda Lidya Chitra Laoh Makapedua, Marlivye Mananta, Aldo Sabathos Marchel Thimoty Tombeng Marcviero Patresse Matauseya Maringka, Raissa Raymond Sambur Reynoldus Andrias Sahulata Semmy Wellem Taju stevanlee ngeloh Susi Susanti Tompunu, Alexander Valentine Lumingkewas Vinky Fransiscus Ong Wungkana, Cindy