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Evangs Mailoa

Universitas Kristen Satya Wacana

Author-ID : 2489987

Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Neuroscience Social Sciences Other

Published : 58 Documents Claim Missing Document

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Visualisasi Pemetaan Penyebaran Gempa Bumi Di Indonesia Krisetianto, Wijaya Yoga; Mailoa, Evangs
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.820

Earthquakes are natural disasters that can have devastating impacts on society. Indonesia needs education about areas that often experience natural disasters. This research was conducted to produce a visualization dashboard regarding mapping of earthquake areas in Indonesia, by applying the Business Intelligence method. This research resulted in the areas with the most earthquakes being the Minahasa Peninsula with 9,408 events with an average of 3.3 Mg, the island of Java with 6,772 events with an average of 3.4 Mg and North Sumatra with 5,920 events with an average of 3.3 Mg.

Time Series Implementation for Sales Forecasting of Furniture Products at PT XYZ Pramastya, Pragnanta Yopie; Mailoa, Evangs
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.818

PT XYZ is an importer, distributor, and seller of furniture. The company operates in two business lines: B2B (Business to Business) and B2C (Business to Consumer). The B2B segment is divided into Agents/Local Distributors, Modern Trade, and Partner Retail Stores, while the B2C segment is divided into Direct Sales and Online Intermediaries. This study applies the Time Series method to forecast future furniture sales using the SARIMA (Seasonal Autoregressive Integrated Moving Average) model. The results of the study using the SARIMA model provide sales forecasts from 2024 to 2026.

PERBANDINGAN IMPLEMENTASI METODE SMOTE PADA ALGORITMA SUPPORT VECTOR MACHINE (SVM) DALAM ANALISIS SENTIMEN OPINI MASYARAKAT TENTANG MIXUE Dewi, Teresia Ardika; Mailoa, Evangs
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 3 (2023): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i3.289

In December 2022, the development of a franchise for an ice cream and tea outlet from China named Mixue became the talk of the Indonesian people, especially on social media Twitter, giving rise to various opinions from the public regarding the Mixue outlet which is growing so rapidly. So from that, sentiment analysis will be carried out by classifying using the implementation of the Support Vector Machine (SVM) algorithm. From the results of research that has been done, the SMOTE-based Support Vector Machine (SVM) algorithm results in an increase in the accuracy value to 73.67% and precision to 75.40%, and for the results of Support Vector Machine (SVM) without using SMOTE, the accuracy value is 69.40% and the precision value is 68.12%. But on the contrary there was a decrease in the recall value to 70.83% and the F1-Score value to 72.79%. So from the evaluation results it can be concluded that SMOTE has an effect on increasing the accuracy and precision values, but there is a decrease in the recall value and F1-Score.

ADOPSI DEVSECOPS UNTUK MENDUKUNG METODE AGILE MENGGUNAKAN TRIVY SEBAGAI SECURITY SCANNER DOCKER IMAGE DAN DOCKERFILE Perkasa, Panca Rizki; Mailoa, Evangs
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 3 (2023): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i3.291

Compliance with personal data protection laws requires electronic system operators to pay more attention to security in applications. Security testing which is usually done at the end of the SDLC makes Agile principles incompatible with advantages that prioritize acceleration, adaptability and responsiveness to change. DevSecOps implementation using Trivy will insert a security scanner process for applications that are deployed in containerized form. The continuous process of security scanning integrated in CI/CD will increase the awareness of developers in terms of application security, so that developers will more quickly fix these problems and avoid security problems at the end of the SDLC.

Pengembangan Sistem Oracle Forms untuk Optimisasi Proses Penjualan di PT.XYZ G.A, Ambrosius Ludang; Mailoa, Evangs
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 2 (2024): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i2.711

This research focuses on the development of an efficient sales system for PT. XYZ a retail company in Indonesia. The company faces challenges in its sales processes due to the lack of efficiency in the manual system, which is susceptible to errors. The research aims to optimize the sales process by utilizing Oracle Forms 10g and implementing the Rapid Application Development (RAD) methodology to ensure timely solutions. The developed system demonstrates a significant improvement in efficiency, accuracy, and speed. The use of Oracle Forms and SQL Developer simplifies data entry and management processes, while the implementation of List of Values (LOV) reduces errors and enhances data consistency. Furthermore, the system provides real-time insights into sales performance, enabling better decision-making and strategic planning for the company.

Pembuatan Website REST API Ensiklopedia Tumbuhan dengan Kombinasi Framework Spring Boot dan MyBatis Generator Hartono, Michael Antonius; Mailoa, Evangs
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 2 (2024): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i2.712

This research focuses on the development of the Plant Encyclopedia REST API, a website application designed using Java, HTML, Spring Boot, MyBatis Generator, and Swagger technologies, with PostgreSQL as the database used to store plant data from the API. This study highlights the declining abilities of the younger generation, especially in mathematics, literacy, and science. Statistical data from PISA test scores from 2003 to 2022 on 15-year-olds worldwide show a peak decline in 2022. The applied research methods include needs analysis, problem identification, system design, application design, implementation, and system testing. This research aims to overcome the lack of knowledge about plants that can have a negative impact on the ecosystem and provide various other benefits. The result of this research is a plant encyclopedia website application that can be accessed by various users to find information related to plants and a swagger website for administrators to manage plant data.

Pembuatan REST API Manajemen Data Karyawan Berbasis Website Menggunakan Spring Boot Adji, Leonard Surya Adji; Mailoa, Evangs
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 2 (2024): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i2.713

This study explores the implementation of REST API with Spring Boot in managing employee data in an E-commerce company. With a focus on efficiency, accuracy, and data security, the application utilizes Java, Spring Boot, and MyBatis as the main foundations. System testing demonstrates success in searching, creating, updating, and deleting employee data. Through the Model View Control (MVC) structure, the application ensures clear task separation. This success affirms the application as an effective solution for employee data management, particularly in the dynamic E-commerce industry.

Pendekatan Data Science terhadap Pemilu 2024: Memahami Persepsi Publik dan Tren Opini Politik Madika, Fiwi Fishinsky; Mailoa, Evangs
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.437

In this study, Twitter is used as a data source to analyze sentiment and public opinion related to the 2024 General Election. The sentiment analysis method is employed to understand how public views are reflected in tweets containing relevant hashtags. The research aims to identify trends in political opinion and public perception that emerge on Twitter during a specific period before, during, and after the election. By analyzing relevant tweet data, this study will provide in-depth understanding of how public opinion evolves and changes over time, as well as identifying the most influential and popular accounts in political discussions on Twitter. The results show that the majority of public opinion about the 2024 General Election on Twitter is positive, with dominant support and sympathy for presidential candidates. Social network analysis reveals a well-structured network with @eternaciumentaa being the most influential and @geloraco being the most popular

Perbandingan Beberapa Algoritma Machine Learning Dalam Analisis Sentimen Terkait Pemilihan Presiden RI 2024 Nopan, Nopan; Mailoa, Evangs
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 13, No 2: Agustus 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v13i2.1980

The 2024 Presidential Election has become a hot topic among the Indonesian community. People often share their opinions and criticisms openly on social media, such as Twitter or X, leading to debates among the public in supporting a presidential candidate. These debates often result in various public comments that are positive, neutral, or negative. Sentiment analysis is used as a method to analyze public opinions and comments using machine learning algorithms. The purpose of this research is to compare the accuracy levels of the Support Vector Machine, Naive Bayes, and Decision Tree algorithms. This research uses a dataset from Twitter, which will go through stages of data merging, text preprocessing, translation, labeling, and algorithm classification. The results of this research show that the Support Vector Machine algorithm has a higher accuracy rate than the other two algorithms, with an accuracy rate of 81.49%.Keywords: Election 2024; Sentiment Analysis; Support Vector Machine; Naive Bayes; Decision Tree.AbstrakPemilihan Presiden 2024 menjadi topik yang hangat dikalangan masyarakat indonesia, masyarakat sering membagikan pendapat dan kritik secara terbuka dimedia sosial twitter atau X, yang menyebabkan subjek perdebatan bagi masyarakat dalam mendukung salah satu kandidat presiden, dampak dari perdebatan ini sering memunculkan berbagai komentar masyarakat yang bersifat positif, netral maupun negatif. Analisis sentimen digunakan sebagai metode untuk menganalisis tentang pendapat dan komentar masyarakat dengan penggunaan algoritma machine learning. Tujuan dari penelitian ini dilakukan untuk membandingkan tingkat akurasi dari algoritma Support Vector Machine, Naive Bayes dan Decision Tree, penelitian ini menggunakan dataset dari twitter yang akan diproses melalui tahapan penggabungan data, preprocessing text, translate, pelabelan dan klasifikasi algoritma. Hasil dari penelitian ini menunjukan bahwa algoritma Support Vector Machine memiliki tingkat akurasi yang lebih tinggi dari kedua algoritma lainnya dengan nilai akurasi 81.49%.Â

Analisis Sentimen terhadap RSUD Salatiga Menggunakan SVM dan TF-IDF Azzahra, Windy Livia; Mailoa, Evangs
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1208

The Salatiga Regional General Hospital (RSUD) plays an important role in providing healthcare services. This research analyzes public sentiment towards RSUD Salatiga using the SVM method with a linear kernel for sentiment analysis and TF-IDF for feature extraction. The dataset consists of 414 processed reviews, including case folding, data cleaning, tokenization, normalization, stopword removal, and stemming. Evaluation shows that the model achieved an accuracy of 84.00%; precision of 84.00%; recall of 83.25%; and an F1-score of 83.53%. A total of 55.8% of reviews indicated positive sentiment and 44.2% negative sentiment, highlighting the need for improvements in the queue system, waiting times, and parking facilities. The SVM and TF-IDF methods were chosen for their ability to handle large text data with high accuracy. This research provides practical contributions in the form of recommendations such as the implementation of a technology-based queue system. Limitations include the limited amount of data and platform bias, so exploring other algorithms, such as Naive Bayes and Random Forest, is recommended.

Co-Authors Ade Iriani Ade Kresna Dewantara Adeline Debby Christiana Adilla, Denise Sheryl Adinda Setya Oktami Adji, Leonard Surya Adji Antonia .M, Hutami Jane Anugramidah Limbong Madika Arbitra Satria Perdana Arief Wijanarko Azzahra, Windy Livia Bernardus Redika Westama Putra Bintang Samasto, Revo Budhi Kristianto Candrawira Wicaksana, Gede Abdi Danny Manongga Dewi, Teresia Ardika Dhinora, Monica Yoshe Dondan, Christofael Natalio Dwi Hosanna Bangkalang Epliani Limbong Rara Fairiani, Ayuquinn Astuticein Faqih, Muhammad Faiq Adhitya Fredrik Landjamara Ndjurumana G.A, Ambrosius Ludang Gede Abdi Candrawira Wicaksana Gilang Agung Saputra Harnanda, Elifas Gavra Hartono, Michael Antonius Harun B S O. Mosioi Hendry, - Hindriyanto Dwi Purnomo Irwan Sembiring Jacob Daan Engel Joseph Triwin Subarjo Juan Rondor Jonathan Sumakul Krisetianto, Wijaya Yoga Krisna Setiawan Luhukay, Priscila Karen Madika, Fiwi Fishinsky Muhammad Arifin Muhammad Rizky Pribadi Natacia, Fanny Nawawi, Arif Hasan Nina Setiyawati Nopan, Nopan Panca Rizki Perkasa Perkasa, Panca Rizki Pramastya, Pragnanta Yopie Putri, Tiara Syah Indra Santoso, Fian Julio Saputra, Krisna Adi Sugeng Ariyadi, Faisal Nuryawan Susanti, Era Syahreza Triadhana Marsudi Tad Gonsalves Teresia Ardika Dewi Tesalonika, Ribka Tetikay, Aprillia Stefvani Ventje Jeremias Lewi Engel Widyasari, Elvira Resti Widyastuti, Fransisca Sonia

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