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All Journal International Journal of Evaluation and Research in Education (IJERE) Jurnal Kependidikan: Penelitian Inovasi Pembelajaran Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Cyberspace: Jurnal Pendidikan Teknologi Informasi INOVTEK Polbeng - Seri Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL PENDIDIKAN TAMBUSAI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Antivirus : Jurnal Ilmiah Teknik Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer JUKANTI (Jurnal Pendidikan Teknologi Informasi) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Mnemonic INFORMASI (Jurnal Informatika dan Sistem Informasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Abdimasku : Jurnal Pengabdian Masyarakat Aiti: Jurnal Teknologi Informasi Jurnal Teknologi Informasi dan Komunikasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Business and Audit Information System (JBASE) Jurnal Indonesia : Manajemen Informatika dan Komunikasi DECODE: Jurnal Pendidikan Teknologi Informasi Jurnal Minfo Polgan (JMP) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Eduvest - Journal of Universal Studies SmartComp Jurnal Pendidikan Teknologi Informasi (JUKANTI) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
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PENGEMBANGAN SISTEM INFORMASI PENJUALAN MENGGUNAKAN FRAMEWORK LARAVEL: STUDI KASUS : BUTIK FANTHY MODESTE Luhukay, Priscila Karen; Mailoa, Evangs
Jurnal Mnemonic Vol 7 No 2 (2024): Mnemonic Vol. 7 No. 2
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v7i2.9741

Abstract

Perkembangan teknologi mengalami percepatan yang signifikan dalam beberapa tahun terakhir, menyebabkan banyak perubahan pada berbagai perangkat, seperti ponsel pintar, TV, dan perangkat elektronik di rumah. Kemajuan tersebut semakin memudahkan pengguna dalam mengakses dan mengelola informasi, khususnya dibidang manajemen inventaris. Butik Fanthy Modeste merupakan butik populer di Kota Jayapura yang membutuhkan suatu sistem untuk mengatur informasi dan memberikan informasi kepada pengguna. Namun sistem tersebut masih kurang, sehingga diperlukan adanya sistem inventaris website dan sistem informasi untuk memudahkan aktivitas pengguna dan pihak dari Butik Fanthy Modeste. Metode waterfall digunakan dalam proyek ini agar lebih mudah dan efektif. Framework Laravel yang digunakan merupakan framework PHP open source yang dikembangkan oleh Taylor Otwell untuk mengembangkan aplikasi web menggunakan Model-View-Controller (MVC) atau arsitektur. Metode waterfall melibatkan beberapa langkah: pengumpulan dan analisis kebutuhan, perancangan sistem (desain), implementasi (pengujian), penerapan sistem (penerapan), dan pemeliharaan (maintenance). Metode Waterfall didasarkan pada "Model Sekuensial Linier", yang merupakan pendekatan sistematis yang melibatkan perencanaan, pemodelan, konstruksi, dan penerapan yang meliputi pengumpulan dan analisis kebutuhan, perancangan sistem, penerapan sistem, pengujian sistem dan pemeliharaan sistem. Hasil pada penelitian ialah terciptanya website fanthymodste.biz.id untuk Butik Fanthy Modeste agar dapat digunakan dalam mengelola pendataan produk, laporan penjualan dan transaksi penjualan. Website ini tentunya memiliki dampak pada pengguna karena dapat memberikan kemudahan bagi pengguna ketika mencari produk sesuai kebutuhan dan dapat di akses di semua browser. Website ini juga memudahkan transaksi karena tersedia pilihan pembayaran yaitu transfer bank dan cash on delivery
ANALISIS POLA MINAT KONSUMEN DENGAN ALGORITMA APRIORI Sugeng Ariyadi, Faisal Nuryawan; Mailoa, Evangs
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol 15 No 2 (2024): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v15i2.873

Abstract

Gunthem Coffee is a cafe located in Semarang as well as a foodtruck when there is an event. Gunthem Coffee provides 20 coffee menus. The large number of coffee menus that spoil consumers, Gunthem Coffee decided to make policies for marketing strategies. Based on the problems experienced by Gunthem Coffee, it is necessary to conduct research on consumer interest patterns so that it will benefit both Gunthem Coffee and consumers. This research uses the a priori algorithm based on field data that can be calculated objectively. The results obtained from the apriori algorithm calculation are to get two (2) association rules with a minimum support of 30% and a minimum confidence of 60%, namely if you buy Black Pink, you will buy Kopi Susu Sanger with a support value of 50% and a confidence value of 67% and if you buy Sanger Milk Coffee, you will buy Black Pink with a support value of 50% and a confidence value of 87%.
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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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