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Tematik : Jurnal Teknologi Informasi Komunikasi

tematik
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Published by POLITEKNIK LP3I BANDUNG

ISSN : 23559055 EISSN : 24433640 DOI : 10.38204

Core Subject : Science,

Computer Science & IT

TEMATIK - Jurnal Teknologi Informasi Dan Komunikasi merupakan jurnal ilmiah sebagai bentuk pengabdian dalam hal pengembangan bidang Teknologi Informasi Dan Komunikasi serta bidang terkait lainnya. TEMATIK - Jurnal Teknologi Informasi Dan Komunikasi diterbitkan oleh LPPM dan Program Studi Manajemen Informatika di Politeknik LP3I Bandung. Redaksi mengundang para dosen, peneliti dan professional dari dunia industri dan kerja untuk menulis karya ilmiah dan pengalaman praktis di lapangan terkait implementasi Informatika dan Komputer.

Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi

Articles 252 Documents

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Penggunaan Algoritma K-Nearest Neighbors(KNN) dalam Klasifikasi Artikel Clickbait Berbahasa Indonesia Isyriyah, Laila; Adi Bayu Permadi; Maulidi, Rakhmad
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1872

Clickbait is a strategy commonly used to attract readers' attention with promising sensational or intriguing headlines. However, often these clickbait headlines do not correspond to the actual content of the news, resulting in disappointment for the readers. Therefore, this study aims to classify clickbait news headlines in the Indonesian language using the K-Nearest Neighbors (K-NN) method. The purpose of this research is to evaluate the ability of the K-NN method to classify clickbait news headlines in the Indonesian language. Thus, it is expected to provide a better understanding of the effectiveness of this method in identifying clickbait headlines. This study utilizes the K-NN method to classify clickbait news headlines. The data consists of 800 training data and 200 test data. The training and testing processes are conducted by varying the number of neighbors (k) and using various supporting features. The results show that the best performance of the K-NN method is achieved with a number of neighbors k=11, yielding an accuracy of 80.5%, Precision of 85%, Recall of 81%, and F-measure of 80%. Testing with 20 new data also resulted in an accuracy rate of 90%. Additionally, several unique words that frequently appear in clickbait headlines are identified, such as "apa" (what), "kenapa" (why), "nih" (here), "alasan" (reason), and "wow". This research contributes to identifying clickbait news headlines in the Indonesian language using the K-NN method. The findings of this study can serve as a reference for further research and provide better insights into how the K-NN method can be applied in classifying clickbait headlines.

Peningkatan kinerja arsitektur ResNet50 untuk Menangani Masalah Overfitting dalam Klasifikasi Penyakit Kulit Handoko Adji Pangestu; Kusrini
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1876

Skin diseases are a significant global health issue, affecting millions of people worldwide. Deep learning, particularly with the transfer learning approach, has shown great potential in improving the diagnosis of skin diseases. This study aims to evaluate various techniques in the context of skin disease classification using transfer learning, focusing on the utilization of the ResNet50 architecture. The steps include data preprocessing, model design with variations in dense layers, fine-tuning, and dropout, as well as model performance evaluation. The results indicate that adding dense layers and fine-tuning significantly improve classification accuracy. Models without additional dense layers achieved an accuracy of around 90%, while fine-tuned models achieved an accuracy of about 94%, and models with added dense layers and fine-tuning achieved an accuracy of about 92%. Overall, adding dense layers and fine-tuning are effective strategies for enhancing the performance of skin disease classification models.

Big Data Analytics for Optimizing Multimodal Supply Chains in the Maritime Industry Chanra Purnama; Marudut Bernadtua Simanjuntak; Malau, April Gunawan
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1879

This research investigates the integration of big data analytics in optimizing multimodal supply chains within the maritime industry. Focusing on efficiency, flexibility, reliability, and visibility, the study examines 100 cadets at a maritime institute, using qualitative research methods and descriptive analysis. Findings reveal a critical need for knowledge and skills, infrastructure and resources, organizational culture and support, and regulatory compliance. The research underscores the importance of investing in training and development, infrastructure, and fostering a culture that values innovation and data-driven decision-making. By addressing these needs, organizations can enhance their readiness to adopt and implement big data analytics, improving the efficiency and sustainability of their supply chains. The study contributes to the understanding of how big data analytics can be leveraged to enhance supply chain performance in the maritime industry.

Enhancing Multimodal Route Optimization in Maritime Transport: Integrating Real-Time Data and Professionalism Sijabat, Panderaja Soritua; Retno Sawitri Wulandari; Wardoyo Dwi Kurniawan; Meriyanti Agustinawati; Marudut Bernadtua Simanjuntak
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1880

This research investigates methods to enhance multimodal route optimization in the maritime sector through the integration of real-time traffic data and professionalism standards. Conducted by researchers and lecturers at the Maritime Institute, the study involves 100 cadets predominantly studying multimodal transportation, logistics, and port management. The research utilises qualitative methods to explore cadets' perspectives on route optimization and professionalism in the industry. Findings reveal a recognition of the significance of real-time traffic data for informed routing decisions, along with an emphasis on compliance with international standards, training, and ethical considerations. Furthermore, cadets perceive machine learning algorithms as effective tools to address the complexities of route optimization. These insights contribute to advancing knowledge in transportation management and education, highlighting the importance of integrating real-time data and professionalism in enhancing route optimization practices.

Enhancing Port Security and Predictive Maintenance with IoT: Cadets' Perspectives Susi Herawati; Rosna Yuherlina Siahaan; April Gunawan Malau; Derma Watty Sihombing; Boedojo Wiwoho Soetatmoko Jogo; Ronald Simanjuntak
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1881

This research explores the perspectives of 100 cadets studying multimodal transportation on integrating Internet of Things (IoT) to enhance port security and predictive maintenance. Using qualitative methods, including interviews and document analysis, the study investigates the effectiveness of IoT in real-time monitoring, data security, and predictive maintenance. The findings highlight cadets' recognition of IoT's potential to transform port operations, particularly in improving security measures and maintenance strategies. Cadets also emphasize the importance of professionalism and adherence to standards in IoT integration, valuing compliance with standards, understanding of IoT, training and education, and ethical considerations. The research underscores the need for continuous education and training programmes to prepare future industry professionals for the challenges and opportunities presented by IoT technologies. Overall, this study contributes to the advancement of knowledge in transportation management and education, offering insights for policymakers, industry practitioners, and educators on the integration of IoT in port operations.

Enhancing Maritime Cargo Documentation with Blockchain Technology Mudakir; Retno Sawitri Wulandari; Larsen Barasa; Dwiyani, Nurindah; Titis Ari Wibowo
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1882

This research explores the potential of blockchain technology to streamline multimodal cargo documentation in the maritime industry. Through qualitative analysis of 100 cadets at the Maritime Institute, key indicators including efficiency, security, interoperability, and readiness for adoption were identified and weighted. Findings show that security and efficiency are paramount, with participants highlighting the need for secure and streamlined documentation processes. Interoperability and readiness for adoption emerged as challenges, indicating the importance of industry-wide standards and training programs. The study underscores the critical role of standardisation in supporting the adoption of blockchain solutions and improving international transportation processes. By addressing these challenges, stakeholders can enhance the security, efficiency, and interoperability of cargo documentation processes, ultimately benefiting the maritime industry.

Enhancing Maritime Safety Standards through Advanced Technologies and Professional Education Wulandari, Retno Sawitri; Larsen Barasa; Marihot Simanjuntak; Mudakir; Rosna Yuherlina Siahaan
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1883

This research explores the integration of advanced technologies, such as machine learning and sensor data analysis, into maritime education to enhance safety standards. The study focuses on cadets' knowledge, attitudes, and perceptions of safety practices and examines incident data to predict and prevent maritime incidents. Findings reveal that while cadets have substantial knowledge of safety regulations, their attitudes towards safety culture need reinforcement. The alignment of education programs with industry requirements and adherence to international standards are emphasized. Additionally, the integration of technology into curricula is crucial for preparing future maritime professionals. The research underscores the need for a comprehensive approach combining technical knowledge, professional attitudes, and advanced technology to significantly improve safety standards and ensure the sustainability of the maritime industry.

Implementasi Metode Mobile D pada E-Posyandu berbasis Android sebagai Alat Literasi dalam Mencegah Stunting Anak Usia Dini Arifin, Rita Wahyuni; Nurul Alfian, Ari; Inayah Ainina Mawardi
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1886

Stunting is a worldwide health problem that impacts children's physical growth and development. According to the latest Indonesian Nutrition Status Survey (SSGI), the stunting rate in Indonesia will reach 21.6% by 2022. Due to its high prevalence, stunting is a major concern. This condition can affect the future of society, the quality of life and the productivity of children. Among the factors causing stunting are inadequate nutrition, unhealthy pregnancies, improper feeding methods, lack of hygiene and sanitation, economic and social factors, infections and chronic diseases, lack of access to health services, and lack of knowledge about the importance of maintaining health for growing children. To solve this problem, an Android-based application is needed that can be accessed anywhere. In this research, the method used is Mobile D consisting of five phases: exploration, Initialization, Production, Stabilization, and System Testing and Fix. It is hoped that the E-Posyandu Application can improve community access to basic health services. With this application, the danger of stunting can be avoided because pregnant women, mothers of toddlers, and other posyandu members can easily access information about child growth and development info, immunization info at each developmental period, info on the location of the nearest RSIA, and complementary food information for toddlers over the age of 6 (six).

Analisis Sentimen Larangan Impor Pakaian Bekas Menggunakan Metode Support Vectore Machine dan Lexicon Based Hendrawati, Theresia; Ginantra, Ni Luh Wiwik Sri Rahayu; Saiman, Clarita Mutiara
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1890

X as a social media platform, provides real-time tweets after the event, making it very relevant for sentiment analysis related to certain topics. This research discusses the prohibition on imports of used clothing in Indonesia using the SVM and Lexicon-based methods. The research aims to determine public sentiment regarding this government policy. The SVM method achieved 85.87% accuracy, with 93.83% recall for positive sentiment and 62.00% recall for negative sentiment. There were 76 wrong positive predictions with a precision of 88.11% and 37 wrong negative predictions with a precision of 77.02%. Meanwhile, the Lexicon Method achieved 60% accuracy, with a positive precision of 69% and a negative precision of 31%. Recall for the negative class is 25%, while for the positive class it is 75%. The results of sentiment analysis applying the Support Vector Machine method to build a classification model resulted in 753 data being successfully classified as positive sentiment, while 147 data were classified as negative sentiment. With different accuracies, it shows that sentiment analysis using the Support Vector Machine method has a higher level of accuracy than Lexicon.

Desain Antarmuka Pengguna Aplikasi Keamanan Pekerja Berbasis Ponsel Pintar Zen Munawar; Sri Sutjiningtyas; Novianti Indah Putri; Hernawati; Rita Komalasari; Herru Soerjono
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1893

Penelitian ini bertujuan mendesain mobile app untuk pekerja, dikarenakan adanya kemungkinan terjadinya kecelakaan di lokasi pekerjaan gas. Metode penelitian dengan melakukan analisis statistik, dan menggunakan investigasi serta analisis literatur, melakukan wawancara, melakukan pengumpulan data sosial tidak langsung. Adapun tahapannya yaitu menganalisis ciri dan karakteristik operasi pekerja lapangan gas, mengamati pada lokasi kerja serta melakukan ekstraksi analisis kebutuhannya, mengamati proses kerja dan serta kemungkinan terjadi insiden yang dapat terjadi pada kegiatan di lapangan. Membuat daftar asumsi untuk merancang aplikasi seluler. Melakukan survei gambar pilihan yang berkaitan dengan pekerjaan gas. Menyelesaikan pembuatan rancangan aplikasi. Mencari temuan sebagai bagian dari rancangan aplikasi seluler. Mendesain dengan tingkat keterbacaan tinggi. Melakukan penggunaan terhadap pengamanan aksesibilitas pengguna. Merencanakan penyampaian informasi yang efektif pada bagian kerja yang sulit untuk dioperasikan pada perangkat seluler. Melakukan aktivasi fungsi alarm di bagian dengan kesalahan kerja tinggi. Menyampaikan komunikasi dua arah yang cepat dan penerimaan materi pemeriksaan keselamatan yang diperlukan saat di tempat kerja. Memberikan pilihan gambar serta konten yang berguna sebagai panduan situasi pekerja jika terjadi kecelakaan. Mengaktifkan alarm tingkat bahaya di suatu area lokasi pekerja. Melakukan rancangan dasar penerapan keselamatan untuk pekerjaan terkait gas, untuk menjamin aksesibilitas pengguna. Hasil akhir merancang tampilan baru yang berfokus pada ikon dengan keterbacaan tinggi untuk memindahkan sistem utama ke layar seluler. Mengidentifikasi bagian yang sering terjadi kesalahan operasional.Terakhir melakukan sinkronisasi pada berbagai perangkat interaktif dengan Aplikasi seluler.

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Home Page

OAI Link

Editorial Team

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Reviewer

Google Scholar

Contact Name Hadiansyah

Contact Email kanghadiansyah@plb.ac.id

Phone +6285220199772

Journal Mail Official tematik@plb.ac.id

Editorial Address Program Studi Manajemen Informatika Politeknik LP3I Bandung Jl. Pahlawan No. 59 Bandung 40123 Telp. (022) 2506500, Fax. (022) 2512564 Email : tematik@plb.ac.id

Location Kota bandung, Jawa barat INDONESIA

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Contact Name
Hadiansyah

Contact Email
kanghadiansyah@plb.ac.id

Phone
+6285220199772

Journal Mail Official
tematik@plb.ac.id

Editorial Address
Program Studi Manajemen Informatika Politeknik LP3I Bandung Jl. Pahlawan No. 59 Bandung 40123 Telp. (022) 2506500, Fax. (022) 2512564 Email : tematik@plb.ac.id

Location
Kota bandung,

Jawa barat

INDONESIA