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INDONESIA
Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Published by STMIK Indonesia Banda Aceh
ISSN : 27768074     EISSN : 27237079     DOI : https://doi.org/10.35870/jimik
Core Subject : Science, Education,
Computer Science & IT Languange, Linguistic, Communication & Media Library & Information Science
Jurnal Indonesia: Manajemen Informatika dan Komunikasi is a scholarly publication dedicated to advancing the fields of information technology and communication management in Indonesia. The journal serves as a platform for researchers, academicians, practitioners, and policymakers to share their insights, knowledge, and expertise in these domains. This journal is a peer-reviewed online journal dedicated to high-quality research publications focused on research, implementation. Jurnal Indonesia: Manajemen Informatika dan Komunikasi is a scholarly publication dedicated to advancing the fields of information technology and communication management in Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Jaringan Komputer dan Komunikasi
Articles 684 Documents
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Analisis Penerimaan Pengguna Aplikasi Kipin School Menggunakan Metode Technology Acceptance Model (TAM) Akbar, Yuma; Bachtiar, Yuliana
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): 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.v5i3.1013

Abstract

This study aims to analyze user acceptance of the Kipin School application in educational settings using the Technology Acceptance Model (TAM) approach. In the era of digital transformation, educational applications like Kipin School play a crucial role in enhancing the effectiveness, efficiency, and quality of learning. This application provides advanced features such as student management, lesson scheduling, academic reporting, and communication between teachers, students, and parents. The study evaluates perceived usefulness and perceived ease of use as the main dimensions influencing user attitude, behavioral intention to use, and actual system use of the application. The results of this research are expected to provide valuable insights for application developers to design more effective, innovative solutions that support the improvement of learning quality and educational management in the future. Additionally, this research is also expected to serve as a foundation for further studies in the field of technology acceptance in education.
Pemodelan Teknologi dalam Aplikasi KitaLulus untuk Lowongan Pekerjaan Menggunakan Metode Technology Acceptance Model (TAM) Sugiyono; Hidayah, Vara Maulidyah
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): 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.v5i3.1014

Abstract

Technological advancements have increased the need for job vacancy information, while the unemployment rate in Indonesia remains high. The KitaLulus application is designed to facilitate job seekers in finding opportunities that match their qualifications and preferences. This study adopts the Technology Acceptance Model (TAM) to analyze user acceptance of this application, focusing on perceived usefulness and perceived ease of use. The objective of this research is to evaluate users' perceptions of the KitaLulus application and analyze the influence of perceived usefulness, perceived ease of use, and behavioral intention on actual system usage. The results indicate that perceived usefulness and perceived ease of use significantly influence the acceptance and use of the KitaLulus application. These findings emphasize the importance of intuitive and beneficial application design to enhance technology adoption, while contributing to the development of job search applications and the academic literature on technology acceptance.
Analisis Sentimen Pada Media Sosial X (Twitter) Terhadap Tumor Jinak Payudara Menggunakan Metode Naïve Bayes Lestari, Syntha Agung; Sugiyono
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): 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.v5i3.1015

Abstract

Benign breast tumors are a medical condition that often raises concerns among the public. This research aims to analyze public sentiment towards benign breast tumors via social media Twitter (X) using the Naïve Bayes algorithm. Data was collected from tweets containing keywords related to benign breast tumors within a certain time period. After data pre-processing, including text cleaning and duplication removal, the data was then classified into positive and negative sentiments using the Naïve Bayes algorithm. This research provides insight into public perceptions of benign breast tumors on social media, and emphasizes the importance of more in-depth health education and disseminating accurate information about the condition. It is hoped that the results of this research can become a reference for health practitioners and policy makers in designing more effective health communication strategies.
Analisa Sentimen Pada Media Sosial “X” Pencarian Keyword ChatGPT Menggunakan Algoritma K-Nearest Neighbors (KNN) Akbar, Yuma; Regita, Anggit Nur Hannaa; Sugiyono; Wahyudi, Tri
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): 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.v5i3.1016

Abstract

Sentiment analysis of the use of Artificial Intelligence (AI) is becoming increasingly important in public understanding of today's rapidly evolving technology, as it helps facilitate human activities. One of the key applications is the presence of ChatGPT, an AI capable of interacting with users through user input, such as answering various questions posed. This topic generates a lot of pros and cons, as widely discussed on social media. Research is needed to evaluate how wisely people use this AI. This study proposes an approach using the K-Nearest Neighbors (KNN) algorithm to analyze AI-related sentiment. The KNN algorithm is used to classify sentiment into positive, negative, or neutral, based on the similarity with the closest word in the feature space derived from text data. This method allows for efficient sentiment grouping without the need for complex models. Researchers chose sentiment analysis because it is an appropriate technique for data processing. Of the 1000 reviews collected from social media users on “X,” 853 were positive, and 147 were negative. The data was classified using the KNN algorithm, followed by an accuracy evaluation yielding 84.80%. The results of this sentiment analysis are expected to guide decision-makers in developing and applying AI technology more intelligently, in line with societal needs and expectations.
Implementasi Algoritma You Only Look Once (YOLOv8) untuk Mendeteksi Pelanggaran Lalu Lintas Berupa Tidak Menggunakan Helm (Studi Kasus di Jatiasih, Bekasi) Poerwandono, Edhy; Barronzoeputra, Gaoeng Qalbun
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): 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.v5i3.1017

Abstract

This research aims to implement the You Only Look Once (YOLO) algorithm in detecting traffic violations in the form of riders who do not use helmets in Jatiasih, Bekasi. The problem studied is the high number of violations in the form of riders who do not use helmets which play a vital role in protecting riders from danger. The expected solution is the development of an automatic detection system that is able to identify this offence with a high level of accuracy. The object of the research is motorcyclists in Jatiasih, Bekasi. The research method used includes applying the YOLO algorithm to video recordings from surveillance cameras at several monitoring points. Video data processing is done by a laptop and YOLO algorithm-based software. The results of this research are expected to support law enforcement efforts, increase awareness of helmet use, and improve road safety by building an automatic detection system that can identify offences such as not wearing a helmet. The results of this research will show how effective the YOLO algorithm is for spotting traffic offences.
Strategi Perencanaan Prasarana Sekolah dengan Enterprise Architecture dan Framework TOGAF Paramida, Feti; Mulyana, Dadang Iskandar
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): 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.v5i3.1020

Abstract

The planning and management of school infrastructure are critical for ensuring the effective delivery of educational services. This study explores the application of Enterprise Architecture (EA) using the TOGAF (The Open Group Architecture Framework) to improve the management of infrastructure at SMK IDN, an IT-focused boarding school. The research involves identifying current issues with the manual system used for infrastructure management, collecting data through observations, interviews, and document analysis, and developing a comprehensive information system that integrates and automates these processes. The TOGAF-ADM framework is employed to map the required architectural solutions, including business, application, and technology architectures. Implementation of this system aims to enhance efficiency, data consistency, and ease of asset tracking. The expected outcome is a robust, integrated information system that supports better infrastructure management, aligning with the school's mission to provide high-quality, technologically advanced education.
Implementasi Algoritma A* (A-Star) untuk Mencari Rute Terpendek dari Kelurahan Cibubur ke Perpustakaan Nasional Republik Indonesia Damayanti, Yulia; Akbar, Yuma
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): 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.v5i3.1022

Abstract

Traffic congestion is a major challenge in Indonesia's big cities, including Jakarta, causing unpredictable travel times, increased pollution and reduced quality of life. The causes of traffic jams in Jakarta include limited road infrastructure, an increase in the number of vehicles, and disorderly driver behavior. One solution is to utilize available alternative routes to reduce congestion and provide more efficient travel options. The National Library of the Republic of Indonesia in Jakarta, although it provides complete facilities to support learning and research activities, is often difficult to access due to traffic jams. Travel from the outskirts of cities such as Cibubur to the city center can be hampered by traffic jams at certain points. Therefore, an effective method is needed to find the closest and fastest route. The A* algorithm is an optimal and efficient route finding algorithm, often used in navigation and route planning. Implementation of the A* algorithm can help drivers find the fastest and shortest routes, reduce travel time, save fuel, and increase transportation efficiency. The research results show that of the three routes studied (Jl. Raya Bogor, Jl. DI Pandjaitan, and Jl. H.R. Rasuna Said), the DI Pandjaitan route is the fastest route with a distance of 1,561.5 km. The implementation of the A* method is expected to help find community routes quickly and overcome congestion problems and lack of knowledge about alternative routes.
Analisis Sentimen Naturalisasi Tim Nasional Indonesia U-23 di Era Shin Tae-yong Menggunakan Algoritma Naïve Bayes dan K-Nearest Neighbors Jaya, Dava Rizky Perwira; Lestari, Sri
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): 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.v5i3.1024

Abstract

In the Shin Tae-yong era, the naturalization of players has become a controversial topic within the Indonesian U-23 national football team. This research aims to analyze public sentiment related to the naturalization of players in the team using two classification algorithms, namely Naive Bayes and K-Nearest Neighbor. Sentiment data is obtained from news sources, social media, and online discussion forums related to matches and team management decisions. First, data processing is carried out, including text cleaning, tokenization, and word weighting. Next, Naive Bayes and KNN models are trained using the processed dataset. The results of the sentiment analysis will provide valuable insight into the public's perception of the naturalization of players in the Indonesian U-23 national team under the control of Shin Tae-yong, as well as a comparison of the effectiveness between the Naive Bayes and KNN algorithms in sentiment classification. It is hoped that this research will provide a more in-depth view of the dynamics within the Indonesian national football team and its contribution to Indonesian football as a whole
Penerapan Sistem Simple Additive Weighting (SAW) dalam Pendukung Keputusan Sistem Kontrak Kerja pada PT. Chia Jiann Furniture Indonesia Yatusifa, Cecilia; Wibowo, Gentur Wahyu Nyipto; Sarwido
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): 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.v5i3.1026

Abstract

Pengambilan keputusan terkait kontrak kerja merupakan aspek yang krusial dalam operasional manajemen perusahaan seringkali terjadi di berbagai sistem penilaian dan kriteria penilaian perusahaan masih banyak dilakukan secara subyektif ataupun manual hal ini dapat dicegah dengan mengingat perkembangan informasi yang semakin berkembang. Dalam upaya untuk meningkatkan proses pengambilan keputusan yang efektif dan efisien, penerapan metode Simple Addative Weighting (SAW) telah menjadi pendekatan yang digunakan dalam sistem pengambilan keputusan (SPK) dalam menajemen. Penelitian ini bertujuan untuk menerapkan SAW dalam konteks pengambilan keputusan sistem kontrak kerja di PT. Furnitur Chia Jiann Indonesia. Dengan melakukan penilaian kinerja karyawan. Perusahaan akan mengetahui apakah target karyawan yang dipertahankan selama ini tercapai atau belum. Pada PT. Chia Jiann masih dilakukan secara manual , maka penulis membuat aplikasi sistem pendukung keputusan kontrak kerja menggunakan metode Simple Addative Weighting (SAW) , konsep dasar metode ini adalah mencari jumlahan terbobot dari rating kinerja pada setiap alternatife pada semua atribut. Metode SAW akan melakukan perangkingan terhdapan atribut dengan bobot yang berbeda-beda secara optimal dan efektif. Adapun hasil perhitungan menunjukkan bahwa karyawan dengan nilai preferensi tertinggi adalah A4 (0,96), diikuti oleh A1 (0,76), A3 (0,748), A5 (0,59), dan A2 (0,529). Berdasarkan nilai preferensi, karyawan dengan nilai tertinggi, yaitu A4, A1, dan A3, direkomendasikan untuk memperpanjang kontraknya, sedangkan A5 dan A2 tidak memperpanjang kontraknya
Teknologi Artificial Intelligence (AI) Vision Swift dalam Sistem Pemantauan Latihan Bulu Tangkis dengan Algoritma Optical Flow Siregar, Mora Hakim; Mulyana, Dadang Iskandar
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): 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.v5i3.1027

Abstract

Badminton is one of the most popular sports in Indonesia. In fact, Indonesia often wins various badminton competitions at the international level. Many people enjoy playing badminton, but many of them do not know whether their shots are good or whether they understand the basic techniques of badminton correctly. Additionally, many of them want to improve their skills but do not have enough time to train with a professional coach. This research aims to develop a badminton training monitoring system based on AI Vision technology using the Swift programming language. This system is expected to help badminton players evaluate and improve the quality of their shots independently. The main focus of this research is to optimize computational accuracy by using the Optical Flow algorithm to track the movement of the shuttlecock during training. In developing this system, the Optical Flow algorithm is used to analyze the shuttlecock's trajectory and its drop points. The results of this research show that testing 20 shots using shuttlecock trajectory can be accurately detected by the system with an accuracy of 97.22%. Meanwhile, the system's accuracy in tracking the placement of the shuttlecock in the opponent's service area is 94.50%.

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