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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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Pengembangan Fitur Pencarian dan Filter Produk pada Aplikasi E-Commerce Gallery Muslim Berbasis Android Mafazi, Luthfillah; Akhsani, Ziyat; Fadillah, Fauzan; Iskandar, Dadang Mulyana; Akbar, Yuma; Hidayat, Aditya Zakaria
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1587

Abstract

The primary challenge in inventory management for MSMEs like Gallery Muslim lies in the manual recording system using notebooks and Excel spreadsheets, which is prone to errors and data loss. Yet, structured offline mobile solutions for micro-scale fashion MSMEs with fragmented recording practices remain limited. This research aims to design and develop an Android-based stock management application utilizing a local Room Database for efficient and accurate digital recording. The study focuses on Gallery Muslim, a retail shop specializing in Muslim clothing and school uniforms. Data were collected through interviews, direct observation, and focus group discussions (FGD) with store owners and warehouse staff. Instruments included documentation of recording activities and analysis of feature requirements. The results demonstrate that the application accelerates the stock recording process by up to 50% compared to manual methods (based on initial simulations), enhances data accuracy, and enables offline access without an internet connection. The study concludes that this Android-based local application is highly suitable for MSMEs not yet integrated with online systems, offering a practical tool for small business owners to embark on digital transformation and improve operational efficiency.
Strategi Digital Marketing dalam Meningkatkan Efektivitas Media di IDN Boarding School Fadlan, Muhammad; Putra, Mohammad Royger Febriansyah; Khanif, Abror; Iskandar, Dadang Mulyana
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1588

Abstract

In the era of the Industrial Revolution 4.0, digital marketing strategies are essential. Therefore, the author aims to enhance the effectiveness of digital marketing strategies at the IDN Boarding School Jonggol Media Team, with the output being a web-based application. The main issues identified include a lack of structure in workflows, delays in task execution, and irregularities in progress reporting. Utilizing the Waterfall model of the Software Development Life Cycle (SDLC), the application is designed to manage task distribution, monitor progress in real-time, and ensure consistency in content publication across various social media platforms such as Instagram, YouTube, TikTok, and the school's official website. Data collection methods include observation, interviews with the Media Team Coordinator, and literature studies. The implementation results demonstrate that the application successfully improves transparency, collaboration efficiency, and reporting accuracy, thereby supporting the optimization of digital marketing strategies. This research provides a relevant technological solution to support media team task management and enhance the competitiveness of educational institutions in attracting public interest.
Pengaruh Terpaan Konten Instagram @pemimpin.indonesia terhadap Sikap Kepemimpinan Positif pada Followers Aisah, Nur; Sutarso, Joko
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1589

Abstract

Advances in technology and social media have opened up vast opportunities for individuals and organizations to participate in media content production. However, research on the influence of social media on the formation of leadership attitudes is still minimal, especially in the context of the use of leadership accounts on Instagram. This study aims to determine whether there is an influence of the content published through the Instagram account @pemimpin.indonesia on the leadership attitudes of its followers and to measure the extent of this influence. The study uses the SOR (stimulus-organism-response) theory as the basis for testing the research. The research approach used is quantitative, with purposive sampling as the sampling technique. The Slovin formula was applied to calculate the research sample. Based on the calculations, 100 respondents who follow the @pemimpin.indonesia account were obtained. The R-square coefficient test result was 71.4%, while the remaining 28.6% was influenced by other variables. The regression test showed that the value Y = 9.133 + 0.683 X had a positive value between variables. Recommendations that can be used as a reference for further research include comparing the influence of other leadership accounts on Instagram or utilizing other platforms such as TikTok, which also provide similar content. This step aims to assess how effective the media is in conveying information that can motivate leadership.
Implementasi Semantic Web Untuk Sistem Penilaian Kelulusan Santri Kelas Akhir Berbasis Ontologi di Ponpes Bintang Sehati Mulyana, Dadang Iskandar; Azzahra, Salma Latifa
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1592

Abstract

The determination of student graduation at Islamic boarding schools is an essential process that is often still carried out manually and subjectively, potentially leading to inconsistencies between student data and graduation decisions. This study aims to develop a graduation assessment system for final-year students using a Semantic Web approach based on ontology. This method is used to represent knowledge in the form of an ontology that includes graduation indicators such as academic scores, character (akhlaq), discipline, Qur'an memorization and arabic language. This study uses a case study at Ponpes Bintang Sehati, where the system is designed to assist the school in making student graduation decisions more objectively and systematically. Ontology development is carried out using the Protégé application, and inference is performed using a reasoner to determine student graduation status based on the input data. The results are expected to show that the system can assist the assessment process objectively and produce a graduation classification that is consistent and accountable. This system can also be further developed to be more adaptive to various academic and administrative needs within the boarding school environment.
Analisis Pola Penyakit Kronis pada Lansia Menggunakan K-Means Clustering di Puskesmas Kelurahan Semper Barat Ardini, Dea Zerlinda; Rhodiyah, Rhodiyah
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1595

Abstract

Chronic diseases have become a major health problem as well as the leading cause of death worldwide. The main chronic diseases causing death globally are cardiovascular diseases, chronic respiratory diseases, and metabolic diseases such as diabetes (WHO, 2018). Semper Barat Subdistrict is an area with a significant number of elderly residents, with healthcare services centered at the Semper Barat Community Health Center (Puskesmas). However, so far, there has been no study that specifically analyzes the patterns of chronic diseases among the elderly in this area using a data mining approach. This study presents a novelty in the form of a case study on clustering chronic diseases within the community of the subdistrict using data mining with the K-Means algorithm. The results show that this model is capable of providing precise values in clustering chronic diseases. The clustering results can be utilized by the Semper Barat Community Health Center as a basis for decision-making in conducting targeted outreach and treatment, thereby facilitating better access to elderly individuals who already have a history of chronic diseases according to their disease group. The testing results from the previous Cluster Distance Performance showed an evaluation value of 0.579 for two clusters, which was the closest to zero compared to other numbers of clusters. In the context of the K-Means algorithm, values closer to zero indicate that the data within a cluster have greater similarity, and the distance between clusters is sufficiently distinct.
Implementasi Sistem Informasi E-Booking Lapangan Bulu Tangkis di GOR Kemayoran Berbasis Web Sutisna, Sutisna; Adnan, Kemal
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1596

Abstract

The advancement of information technology is currently encouraging various service sectors to adapt, including in the management of sports facilities. GOR Kemayoran faces problems in the badminton court booking system which is still done manually, leading to irregular schedules, recording errors, and inconvenience for users. This study aims to design and implement a website-based badminton court e-booking information system that can simplify the booking process for the public and increase the efficiency of managing the field schedule at GOR Kemayoran. The method used in this study is the waterfall development model, which includes the stages of needs analysis, system design, implementation, testing, and maintenance. The result is a web-based e-booking application that provides online booking features and schedule availability checks. It is expected that this system will provide convenience for customers in making reservations and assist management in arranging schedules and recording transactions more effectively and in a structured manner.
Klasifikasi Tingkat Kepuasan Masyarakat terhadap Pelayanan Pembuatan KTP Elektronik di Dinas Dukcapil Semper Barat Menggunakan Metode Naïve Bayes Lestari, Dinny Amalia; Sugiyono, Sugiyono; Akbar, Yuma; Hidayat, Aditya Zakaria
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1598

Abstract

Population administration plays an important role in Indonesia as it is involved in various activities at the government agency level. Based on data from 2020, the population in Jakarta reached 2,343,511 people. This indicates that the government in every region must provide the best service in managing population administration, especially in the issuance of electronic ID cards (e-KTP). However, various issues have been found that lead to public dissatisfaction, such as the lengthy service process, lack of information, and limited number of service personnel. Therefore, it is necessary to conduct an analysis of the level of public satisfaction to evaluate and improve service quality. This research aims to classify the level of satisfaction of the community regarding the service of e-KTP issuance. The object of this study is the community members who are applying for electronic ID cards at the Dukcapil Semper Barat. The method used in this research is a quantitative approach, with data collection through questionnaires distributed to 100 respondents. Data is obtained using questionnaires distributed to the public, and subsequently analyzed through classification performance evaluation processes. The results of this study indicate that the Naïve Bayes method is capable of classifying the level of public satisfaction with a fairly good accuracy rate. These findings are expected to serve as a reference for the Dukcapil in improving the quality of public services sustainably.
Optimasi Sistem Rekomendasi Musik Berbasis Naïve Bayes: Studi Kasus pada Pengguna Musik di Spotify Lestari, Sri; Wardana, Shabrina Sukma
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1600

Abstract

This study aims to develop a music recommendation system based on the Naïve Bayes algorithm, using Spotify users in Indonesia as a case study. The dataset was obtained from a questionnaire involving 473 respondents, covering variables such as gender, age, and frequency of Spotify usage. Music genres were grouped into two categories: Majority Favorites (Pop, K-Pop, Jazz, R&B, Indie) and Minority Favorites (Hip Hop, Rock, Religious, Dangdut, EDM, Regional). The research process included data cleaning and transformation, splitting the dataset into 80% training and 20% testing, applying the Naïve Bayes algorithm, and evaluating the model using accuracy, precision, recall, and F1-score metrics. The experimental results showed that the model achieved an accuracy of 95.82%, with 100% precision for the Majority Favorites category and 85.51% for the Minority Favorites category, along with recall values of 94.44% and 100%, respectively. The average F1-score was in the “very good” category, indicating that the model can reliably predict music genre preferences. These findings suggest that the resulting recommendation system is suitable for implementation to help users discover music aligned with their demographic characteristics and listening behavior, while also contributing to the development of recommendation systems based on primary data.
Penerapan Metode Naive Bayes untuk Klasifikasi Produk Kurang Diminati Berdasarkan Data Penjualan di Toko Laris Eksis Rhodiyah, Rhodiyah; Rahmawati, Dwita
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1601

Abstract

This study aims to apply the Naïve Bayes algorithm to classify in-demand and less in-demand products at Toko Laris Eksis based on sales data, including attributes such as the number of product page views (view), the number of products added to the cart (cart), and the number of products sold (sales). The dataset consists of 245 products from 516 sales transactions after data cleaning. The results show that, despite the class imbalance, the Naïve Bayes algorithm achieved an accuracy of 97.26%, with 100% precision and 96.8% recall for the Less In-Demand class, and 84.6% precision and 100% recall for the In-Demand class. This model outperforms the majority baseline accuracy of 89%. These findings indicate that the Naïve Bayes method is highly effective in detecting in-demand products, even with imbalanced data. Practically, this model can support decisions related to promotions, bundling, and stock clearance in retail. Future research is recommended to use k-fold stratification for evaluation, test adaptive thresholds, and integrate the model into an interactive visual dashboard.
Penerapan Metode Naïve Bayes untuk Klasifikasi Produk Berdasarkan Kategori Penjualan di Toko Artemist Akbar, Yuma; Qibthiyah, Mariyatul
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1603

Abstract

The implementation of this model offers practical benefits for stock management, promotional planning, and data-driven product strategy decisions, thereby improving operational efficiency for medium-scale retail businesses. The application of data analysis in the retail sector is essential to support accurate and efficient decision-making. This study aims to classify products at Artemist Store into two categories: high demand and low demand, using the Naïve Bayes method. The data used are sales records for one year with a total of 8,106 transactions, which after preprocessing resulted in 148 products. Class labels are determined based on the average sales threshold. The dataset is divided using a stratification scheme of 70% training data (103 products) and 30% test data (45 products). The Naïve Bayes algorithm is implemented in RapidMiner Studio software. The evaluation results on the test data show an accuracy of 93.33%, with 89.29% precision and 100% recall in the high demand class, and 100% precision and 85% recall in the low demand class. These findings prove that Naïve Bayes is effective in identifying products with different levels of consumer interest, while also providing practical benefits in the form of stock management recommendations, promotional planning, and data-driven marketing strategies for medium-scale retailers.

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