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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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Perancangan Aplikasi Terapi Musik untuk Penderita Anxiety Menggunakan Pendekatan Human Centered Design (HCD), Persona, dan Minimum Viable Product (MVP) Dyah Utami, Kartika; Kusuma, Wahyu Teja; Anshori, Mochammad
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.v6i3.1453

Abstract

Anxiety represents a prevalent mental disorder among individuals in their productive years, significantly affecting quality of life and psychological well-being. The present study aimed to design a music therapy application as a non-pharmacological intervention for alleviating anxiety symptoms. Nineteen respondents aged 20–24 years with diagnosed anxiety disorders in the Malang region participated in the study. The application was developed using Human-Centered Design (HCD) approaches, persona methodology, and Minimum Viable Product (MVP) principles. Therapeutic music categories included guided meditation tracks, nature sounds, and 432Hz frequency compositions, all validated by a hypnotherapy specialist. Prototype evaluation was conducted through user needs mapping (persona goals) and expert validation procedures. Results demonstrate that the prototype successfully addressed three core indicators: PG.1 (access to therapeutic music catalog), PG.2 (music search functionality), and PG.3 (playback interface design). These features were engineered to deliver accessible relaxation experiences for independent use. The research establishes that integrating HCD, persona, and MVP methodologies can generate solutions grounded in authentic user requirements. Study limitations include the restricted sample size and absence of long-term effectiveness assessment. Future research should investigate emotion-based music personalization features to enhance therapeutic outcomes.
Efektivitas Logistic Regression dalam Analisis Sentimen Berbahasa Indonesia pada Komentar YouTube tentang Isu Ketenagakerjaan Mulyono, Hamdan Santani; Saprudin, Usep
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.v6i3.1481

Abstract

This study examines the development of a sentiment classification system for Indonesian-language YouTube comments addressing employment issues through the implementation of Logistic Regression algorithm. The research dataset comprises 2,755 comments extracted from a video themed "Job Seeker Stories," with 1,020 comments manually labeled into three sentiment categories: positive, neutral, and negative. The research methodology includes text preprocessing stages, feature transformation using TF-IDF, data splitting with stratified sampling, class imbalance handling through SMOTE, and hyperparameter optimization using GridSearchCV. Model evaluation yielded 44% accuracy with varying performance distribution across classes. The negative class demonstrated optimal performance with an F1-score of 0.55, while neutral and positive classes achieved scores of 0.34 and 0.29, respectively. Class distribution imbalance and implicit characteristics of positive comments became primary obstacles in the classification process. Research findings indicate that the combination of Logistic Regression, TF-IDF, and SMOTE has potential as a baseline method for sentiment analysis of Indonesian social media comments. Nevertheless, deep learning-based model development is necessary to improve accuracy and linguistic nuance interpretation capabilities. The analysis also identified negative sentiment dominance in public responses, reflecting societal concerns regarding the national employment situation.
Aplikasi Chatbot Rekomendasi Laptop Menggunakan Natural Language Processing Fauzi, Fikri; Aji, Adam Sekti
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.v6i3.1483

Abstract

The problem of selecting laptops that match user needs often becomes a challenge for many users, especially for those who are less familiar with technical specifications. To address this problem, this research develops a Natural Language Processing (NLP)-based chatbot application capable of providing automatic laptop recommendations based on user needs. This application implements the TF-IDF algorithm to extract features from user input in natural language, then calculates cosine similarity with laptop specification datasets stored in a MySQL database to generate the most relevant recommendations. The results of black box testing show that the system is capable of providing recommendations with a precision rate of 87.5%, recall of 83.2%, and F1-score of 85.3% in understanding user preferences based on criteria such as price range, weight, and usage type. This research contributes to the development of NLP-based chatbot technology by integrating the TF-IDF approach for more accurate natural language understanding compared to conventional rule-based chatbots, as well as providing interactive solutions that facilitate ordinary users in obtaining laptop recommendations without requiring in-depth technical knowledge.
Model Klasifikasi Citra Penyakit Monkeypox Berbasis Ekstraksi Fitur GLCM dan Algoritma SVM Hutagaol, LeonHoss; Prami Swari, Made Hanindia; Akbar, Fawwaz Ali
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.v6i3.1485

Abstract

Monkeypox disease is an infectious disease that requires early detection to support effective and rapid treatment. This study aims to develop a Monkeypox disease image classification model with a texture-based approach using the Gray Level Co-occurrence Matrix (GLCM) method and the Support Vector Machine (SVM) classification algorithm. The dataset used is the Monkeypox Skin Images Dataset (MSID) with a total of 3,200 images, consisting of 1,600 Monkeypox infected images and 1,600 normal skin images. All images go through preprocessing stages such as resizing, converting to grayscale, normalization, and median filtering. Furthermore, GLCM texture feature extraction (contrast, energy, correlation, homogeneity) is carried out and the results are used as input for classification using SVM. The evaluation was carried out by testing four SVM kernels: linear, polynomial, RBF, and sigmoid. The test results showed that the RBF kernel gave the best performance with an accuracy of 80%, followed by the linear kernel (73%), sigmoid (68%), and polynomial (65%). These findings prove that the combination of GLCM texture features with SVM algorithm, especially RBF kernel, has strong potential to support automatic diagnosis of Monkeypox disease based on medical images.
Resepsi Penonton terhadap Representasi Maskulinitas Hegemoni dalam Tokoh Utama Film Argylle Dewanto, Muhammad Rizki Fauzan; Sanjaya, Andika
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.v6i3.1517

Abstract

This study aims to analyze audience reception of the representation of hegemonic masculinity in the main character of the film Argylle. The research employs a descriptive qualitative approach using the encoding/decoding reception analysis model. Data were collected through online interviews and literature review. Surveys were distributed randomly to informants to examine audience responses to gender stereotypes in Argylle. Thematic analysis was conducted in four stages: data reduction, data presentation, conclusion drawing, and critical interpretation. The findings reveal that audience perceptions of Elly Conway's character are divided into three reading positions. Some informants occupy the negotiated reading position, appreciating the portrayal of a strong and independent female character, yet questioning the consistency of the masculine traits depicted. Other informants are in the dominant reading position, accepting Elly’s representation positively as a symbol of women’s empowerment in a spy genre typically dominated by men. Meanwhile, one informant adopts an oppositional reading, considering Elly’s representation less realistic and overly divergent from traditional gender norms. These results indicate that gender is understood as a social construction negotiated based on audience experience and background. The film Argylle serves not only as entertainment, but also as a space for discussion and critical reflection on masculinity and gender representation in popular media.
Pendekatan Ekologi Media Solo Radio FM: Upaya Mempertahankan Eksistensi di Tengah Transformasi Digital di Surakarta Salwa, Akrimy Naila; Triyono, Agus
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.v6i3.1519

Abstract

The rapid advancement of technology has led to the emergence of new media, such as the internet with various platforms, making it easier for people to access information and entertainment. This has resulted in a decline in interest in radio. Nevertheless, Solo Radio FM continues to strive to maintain its existence. The purpose of this study is to analyze the application of Ecology Media theory to Solo Radio FM in sustaining its presence. This research employs a qualitative method with a descriptive approach and utilizes the Ecology Media theory introduced by Dimmick and Rouhtenbuhler, which involves three main elements: type of content, type of audience, and capital. The findings show that Solo Radio FM maintains its existence by producing broadcast programs divided into information and entertainment categories favored by listeners. In terms of audience, Solo Radio FM segments its listeners and expands its reach through social media. Lastly, regarding capital, Solo Radio FM pays attention to the financial aspect by optimizing revenue from advertising.
Strategi Konten Media Sosial PT Numex Teknologi Indonesia untuk Meningkatkan Brand Awareness Shelycia, Shelycia; Winata, Angeline
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.v6i3.1541

Abstract

Brand awareness is a crucial aspect for a brand to be recognized by the public. This research aims to identify the social media content strategy of PT Numex Teknologi Indonesia in enhancing brand awareness. The study refers to the concept of content marketing by Karr and Moran, as well as brand awareness according to Durianto. This research adopts a descriptive qualitative approach with a case study method. Data were collected through interviews and observation. The results indicate that LandX applies content marketing on social media based on the principles outlined by Karr and Moran. Moreover, these strategies have proven effective in increasing LandX brand awareness. Content analysis of LandX social media was also conducted to support the findings.
Analisis Sentimen Pemecatan Shin Tae-yong pada Media Sosial X untuk Monitoring Opini Publik Menggunakan Naïve Bayes dan Support Vector Machines Arisenja, Ni Luh Bumi; Mulyana, Dadang Iskandar
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.v6i3.1561

Abstract

Social media has become a primary platform for people to voice their opinions on national issues, including in the field of sports. One of the hotly discussed issues is the dismissal of the Indonesian National Team coach, Shin Tae-Yong. This study aims to analyze public sentiment towards the dismissal through social media platform X (formerly known as Twitter) using two machine learning algorithms, namely Naïve Bayes and Support Vector Machines (SVM). Data was obtained through a crawling process using the keyword pecat shin tae-yong, then carried out pre-processing stages such as cleaning, tokenizing, stopword removal, and stemming. The evaluation process was carried out using a confusion matrix to measure accuracy, precision, recall, and F1-score. The classification results show that the Naïve Bayes model produces an accuracy of 92.91%, while the positive precision value is 81.33%, and the negative precision is 100%. Meanwhile, the SVM (Support Vector Machine) model provided more optimal results with an accuracy of 97.97%, a positive precision of 96.72%, a negative precision of 98.53%, and a positive recall of 96.72% and a negative recall of 98.53%. Based on these results, it can be concluded that the SVM algorithm performed better in analyzing public opinion regarding the coach's dismissal issue. This research is expected to contribute as a reference data-based public opinion monitoring system for more transparent public policymaking.
Implementasi Algoritma Clustering K-Means untuk Segmentasi Pelanggan di E-Commerce Mado, Priscianus Mikael Kia; Hendry, Hendry
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.v6i3.1563

Abstract

In the increasingly advanced digital era, competition in the e-commerce world requires companies to understand customer behavior in depth in order to maintain loyalty and increase sales. This study aims to segment e-commerce customers by applying the K-means clustering algorithm using RFM (Recency, Frequency, Monetary) analysis. Customer transaction data is processed through pre-processing stages such as data cleaning and normalization, then the K-means algorithm is applied to group customers into homogeneous segments based on their purchasing behavior characteristics. Optimal grouping is obtained using the Silhouette Score evaluation metric, resulting in three main customer segments. The results of this segmentation can help companies design more effective and focused marketing strategies according to the needs of each customer segment.
Peran Instagram dalam Pembentukan Identitas Remaja di Era Digital Fauzan, Jeje; Harahap, Halomoan
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.v6i3.1564

Abstract

This study aims to examine the role of Instagram in shaping and expressing adolescent self-identity in the digital era, with a focus on Cilegon City. Adolescence is a pivotal stage of identity development, where social media functions as a space for self-presentation, social validation, and relationship-building. Employing a qualitative approach with a phenomenological method, this research involved five adolescents aged 16–20 who were purposively selected based on their active Instagram use and engagement in digital interactions. Data were collected through account observation, in-depth interviews, and documentation of Instagram activities. The findings indicate that Instagram is utilized to construct an ideal self-image, express values and emotions, and gain social acknowledgment. However, the pressure to maintain a perfect appearance also triggers psychological risks such as anxiety and a disconnect between online and offline identity. These results demonstrate that Instagram serves not only as a medium for expression but also as a complex social arena in adolescent identity formation. The study underscores the necessity of digital guidance and adaptive media literacy to support adolescent mental health.

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