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Muhammad Wali
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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 46 Documents
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Search results for , issue "Vol. 6 No. 3 (2025): September" : 46 Documents clear
Rancang Bangun Aplikasi “Unifiction” dengan Pendekatan Design Thinking untuk Memudahkan Akses Membaca dan Mengunggah Karya Novel Digital Putra, Anak Agung Adi Wiryya; Frakasa, Meizaluna Aurelia; Darmawan, Pramudya Figo
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.v6i3.1165

Abstract

The development of the digital novel application "UniFiction" aims to enhance reading interest among Indonesian citizens, which remains relatively low. Statistical data reveals that only 10% of the population regularly engages in book reading. Factors contributing to low reading interest include difficulties locating books in libraries, inadequate infrastructure, and high costs associated with physical books. The application features a minimalist interface that facilitates access to diverse reading sources while serving as a platform for users to express their creativity through writing. The design approach employed Design Thinking methodology involving ten respondents in the usability testing process. The application design achieved a SUS score of 85.5. The expected outcome of the UniFiction application is to enhance reading and writing interest within the community while supporting literacy improvement efforts and reading culture development in Indonesia.
Klasifikasi Kemampuan Mahasiswa Berdasarkan Automatic Essay Scoring terhadap Jawaban Essay Ujian Kompetensi dengan Metode Machine Learning Hakiki, Muhammad; Fatichah, Chastine
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.v6i3.1325

Abstract

Manually assessing student answers and grouping student abilities is very time-consuming. Therefore, a system is needed that can automatically assess student essay answers and group student abilities. This study proposes a method for classifying student abilities based on the Automatic Essay Scoring value using the LSTM method and several classification methods. The number of datasets used in this study was 98 students, while the questions tested in this competency exam were 200 questions. The parameters used for LSTM are student answers. The benefit of this study is to find out which students have mastered the lecture and which students have not mastered the lecture. The results of this study indicate that the LSTM method successfully provides automatic essay assessment with an accuracy value of 0.9, while the most superior classification method is the Decision Tree method with the ROS oversampling method, which is 0.654.
Kontradiksi Agitasi Hizbut Tahrir Indonesia terhadap Konsep Politik Islam dalam Pembentukan Pandangan Bernegara Marpaung, Hery Wahyudi; Katimin, Katimin; Samosir, Hasrat Efendi
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.v6i3.1444

Abstract

Penelitian ini mengkaji kontradiksi antara ideologi HTI dan prinsip politik Islam, khususnya penolakan terhadap demokrasi dan negara-bangsa. Dengan analisis wacana kritis, penelitian menelaah narasi HTI dalam teks resmi, publikasi digital, dan pernyataan tokohnya mengenai konsep khilafah. Hasil penelitian menunjukkan bahwa pandangan politik HTI bersifat rigid, eksklusif, dan mengabaikan nilai-nilai keislaman yang inklusif seperti musyawarah, keadilan, dan toleransi. Pandangan tersebut tidak sejalan dengan prinsip politik Islam yang tercermin dalam Piagam Madinah, yang menekankan kerja sama lintas kelompok dan pengakuan terhadap keberagaman. Agitasi HTI juga berdampak pada pembentukan kesadaran ideologis yang sempit dan polarisasi dalam masyarakat. Penelitian ini menyimpulkan bahwa ideologi HTI tidak hanya bertentangan dengan realitas sosial-politik Indonesia yang demokratis dan plural, tetapi juga menyalahi semangat politik Islam yang bersifat adaptif dan kontekstual. Oleh karena itu, diperlukan upaya akademik dan kebijakan yang responsif dan kritis terhadap penyebaran, maupun indikasi penyebaran, ideologi eksklusif yang bertentangan dengan nilai demokrasi Indonesia dan prinsip politik Islam demi menjaga kohesi sosial dan keutuhan bangsa.
Analisis Faktor Risiko Stunting pada Balita di Desa Kesetnana Menggunakan Metode Random Forest Kase, Celomitha Putri Welhelmina; Prasetyo, Sri Yulianto 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.v6i3.1449

Abstract

Stunting is a growth disorder triggered by chronic malnutrition, impacting the physical and cognitive development of young children. Kesetnana Village in South Central Timor Regency records a high prevalence of stunting. This study aims to classify stunting status using the Random Forest Classifier algorithm and assess its performance. The quantitative analysis was conducted on secondary data from 1,451 toddlers obtained through total sampling from the Health Center and Kesetnana Village Office in 2023. The variables analyzed include birth weight and height, measurement age, as well as Z-scores for Height/Age, Weight/Age, and Weight/Height. Data were processed using Python on the Google Colaboratory platform, with 75% allocated for training and 25% for testing. The findings indicate that birth weight, measurement age, and height are the primary factors in stunting classification. The model achieved 97% accuracy, with high precision and recall values, demonstrating its effectiveness in classifying stunting. This model can be utilized by health professionals and policymakers to identify stunting risk at an early stage and design targeted nutritional interventions in high-prevalence areas.
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.

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