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All Journal Jurnal Simetris Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah KOMPUTASI Format : Jurnal Imiah Teknik Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika Jurnal Komputasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) IKRA-ITH Informatika : Jurnal Komputer dan Informatika Sebatik Jiko (Jurnal Informatika dan komputer) Astonjadro Simtek : Jurnal Sistem Informasi dan Teknik Komputer CCIT (Creative Communication and Innovative Technology) Journal Journal of Information System, Applied, Management, Accounting and Research Informatika IJITEE (International Journal of Information Technology and Electrical Engineering) Journal of Applied Science, Engineering, Technology, and Education JUKI : Jurnal Komputer dan Informatika Jurnal Abdidas International Journal of Industrial Optimization (IJIO) Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Teknik Informatika (JUTIF) International Journal Of Science, Technology & Management (IJSTM) Journal of Technology and Informatics (JoTI) Indonesian Journal of Multidisciplinary Science Journal Of World Science Buletin Sistem Informasi dan Teknologi Islam Jurnal Locus Penelitian dan Pengabdian Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Jurnal Indonesia Sosial Sains Journal Research of Social Science, Economics, and Management Eduvest - Journal of Universal Studies Kohesi: Jurnal Sains dan Teknologi SmartComp Jurnal Informatika Polinema (JIP) Asian Journal of Social and Humanities Paradigma: Jurnal Filsafat, Sains, Teknologi, dan Sosial Budaya
Akbar, Habibullah
Universitas Esa Unggul
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Utilization of LSTM (Long Short Term Memory) Based Sentiment Analysis for Stock Price Prediction Muhammad Fajrul Aslim; Gerry Firmansyah; Budi Tjahjono; Habibullah Akbar; Agung Mulyo Widodo
Asian Journal of Social and Humanities Vol. 1 No. 12 (2023): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v1i12.141

Abstract

This study aims to utilize sentiment analysis in predicting stock price movements. Sentiment analysis can provide information to investors to understand market sentiment. This study uses a text-based approach by pre-processing data, constructing a sentiment analysis model and evaluating model performance. The collected data is analyzed to identify the text's positive, negative, or neutral sentiments. The approach used in scoring sentiment analysis is the Text blob approach and the Lexicon approach. Differences in the results of the accuracy of the two Sentiment Analysis approaches with the LSTM model have an influence on the prediction results with a better increase in accuracy using the Lexicon Sentiment Analysis approach. Then the LSTM model is implemented to classify texts into the desired sentiment categories. The results of this study are insight into the use of sentiment analysis in predicting stock price movements. The implemented sentiment analysis model can be a useful predictive tool for investors and stock practitioners in making investment decisions.
DETEKSI BANJIR AREA PERKOTAAN BERBASIS CITRA DIGITAL CONVOLUTIONAL NEURAL NETWORK (VGG19) Habibullah Akbar; Diah Aryani; Muhamad Bahrul Ulum
Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 2 No. 3 (2022): November : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (992.245 KB) | DOI: 10.55606/teknik.v2i3.798

Abstract

Geographically and demographically, Indonesia has natural conditions that have the potential for floods disaster. There are at least 16,771 islands and 65,017 rivers that fill the archipelago. Unfortunately, the ever-increasing urban population accompanied by a lack of awareness and preparation for protecting the environment has resulted in a higher risk of flooding in urban areas. This study utilizes digital imagery to detect flood conditions in urban areas. In terms of access, digital images are available in urban CCTV monitoring systems as well as office areas, housing, and from people who have smartphones. The detection method used in this study is the VGG19 model which consists of 16 convolution layers and 3 standard classification layers. All convolution layers are divided into 5 blocks followed by a MaxPooling layer for each block to reduce the resolution of the input image. In the last layer, SoftMax layer is used to estimate the probability between flood labels and normal conditions. There are 4 parameters that were optimized during the VGG19 model training process, namely Batch Size, Learning Rate, Dropout and Epoch (training repetition). To test the proposed model, public datasets are used, namely the Roadway Flooding Image Dataset and Road Vehicle Images Dataset. The best flood detection results (or normal conditions) achieve the accuracy of 98.78%. As for the other three performance metrics, namely precision, recall and F1-score, they reach 99%. These results are generated by the VGG19 model with a Batch Size parameter of 20, a Learning Rate of 1e-5 (0.00001), 50% Dropout and 100 Epoch. The achievement values of the four metrics can be considered quite good, so that the VGG19 model has the opportunity to be developed for flood detection applications in order to monitor urban flood conditions.
Fraud Detection in Credit Card Transactions Using HDBSCAN, UMAP and SMOTE Methods Setiawan, Rudy; Tjahjono, Budi; Firmansyah, Gerry; Akbar, Habibullah
International Journal of Science, Technology & Management Vol. 4 No. 5 (2023): September 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i5.929

Abstract

Credit card abuse and fraud in credit card transactions pose a serious threat to financial companies and consumers. To overcome this problem, accurate and effective fraud detection is essential. In this study, we propose an approach that combines HDBSCAN (Hierarchical Density-Based Spatial Clustering of Applications with Noise), UMAP (Uniform Manifold Approximation and Projection), and SMOTE (Synthetic Minority Over-sampling Technique) methods to detect fraud in credit card transactions. The HDBSCAN method is used to group transactions based on their spatial density, allowing identification of suspicious groups of transactions. UMAP is used to reduce the dimension of transaction data, thus enabling better visualization and more efficient data analysis. In addition, we use SMOTE to overcome class imbalances, namely differences in the number of fraudulent and non-fraudulent transactions. In our experiments, we used. In this experiment, we used a dataset of credit card transactions that included both fraudulent and non-fraudulent transactions. The experimental results show that the proposed approach is able to detect fraud with high accuracy. The HDBSCAN method is able to effectively identify suspicious groups of transactions, while UMAP helps in better understanding and visualization of data. The use of SMOTE has successfully overcome class imbalances, resulting in more balanced fraud detection results between fraud and non-fraud. The results of this study show that the combination of HDBSCAN, UMAP, and SMOTE methods is effective in detecting fraud in credit card transactions. This approach can help financial companies identify suspicious transactions with high accuracy, reduce fraud losses, and improve the security of credit card transactions.
Implementation of the Multimedia Development Life Cycle (MDLC) in Solar System Application Design Aryani, Diah; Noviandi, Noviandi; Siti Fatonah, Nenden; Akbar, Habibullah
International Journal of Science, Technology & Management Vol. 5 No. 4 (2024): July 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i4.1123

Abstract

Augmented Reality (AR) technology has had an impact on changes in the world of education, especially improving the quality of education which has positively influenced the learning and teaching process, with the use of tools in education it has proven effective in improving the learning and teaching environment in the classroom and even changing the way we view education. This research aims to design a solar system application as an alternative AR-based learning media by integrating 3D models, animation and video to improve the learning experience of students, especially students of SDN Larangan 5 Tangerang. This is based on the lack of student learning experience, especially regarding the solar system material which is still lacking and not yet varied because so far SDN Larangan 5 has not used technology, especially AR technology in the learning process and still uses book texts and videos. This research used the Multimedia Development Life Cycle (MDLC) method and usability testing was carried out using the System Usability Scale (SUS) method with a total of 33 respondents with a test result of 78 which indicates the level of user satisfaction with the solar system application that has been tested on the respondents.
Optimization of Delay Using Killer Whale Algorithm (KWA) on NB-IoT Hadi, Muhammad Abdullah; Widodo, Agung Mulyo; Firmansyah, Gerry; Akbar, Habibullah
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12933

Abstract

Abstract: NB-IoT is designed to connect IoT devices with low-power, wide-area coverage and efficient costs. Ensuring optimal data transmission delay is a challenge in NB-IoT implementation. Inadequate coverage can hinder IoT adoption. Optimization balances energy saving and delay trade-off. The Killer Whale Algorithm (KWA) optimizes delay by adjusting repetition variables. KWA addresses dimensions, variable limits. Applying KWA in NB-IoT optimizes transmission, enhancing QoS. Optimizing delay involves reducing latency in uplink data transmission using repetition variables. This study applies KWA to optimize NB-IoT delay. Analysis in Table 4 shows non-linear repetition-distance correlation. Interestingly, delay outcomes exhibit a contrasting relationship. Still, delay remains advantageous, remaining under 1 second even at 10 km, specifically 9.2674 ms (0.0092674 seconds). This thesis aims to optimize delay in NB-IoT network transmission using the Killer Whale Algorithm (KWA), crucial for modern communication networks and IoT applications. Leveraging KWA, the research identifies solutions to reduce transmission delay, enhancing efficiency and meeting IoT communication demands for speed and timeliness
EVALUASI KINERJA TATA KELOLA TEKNOLOGI INFORMASI TERHADAP TOOLS INTERNAL FRAMEWORK COBIT 2019 Akbar, Habibullah; Saputra, Rahdian
Sebatik Vol. 27 No. 2 (2023): Desember 2023
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v27i2.2336

Abstract

Di era ini, teknologi informasi dan layanan transportasi terintegrasi untuk meningkatkan produktivitas dan menunjang kebutuhan masyarakat didasari dengan tujuan yang jelas pada perencanaan tata kelola teknologi informasi. Salah satu BUMN yang diberikan kebijakan oleh pemerintah untuk mengelola teknologi informasi adalah PT Telkom Akses. PT Telkom Akses telah menerapkan tata kelola teknologi informasi berdasarkan ISO 270001, ISO 20000-1, dan COBIT dengan membentuk prosedur tata kelola teknologi informasi di Unit Information System serta peraturan, kebijakan, implementasi, monitoring, dan audit teknologi informasi. Agar tujuan yang telah ditetapkan dapat tercapai dan berlaku sesuai rencana, maka perlu dilakukan kegiatan evaluasi terhadap operasional tata kelola teknologi informasi tersebut. Framework COBIT 2019 adalah jenis framework yang sifatnya lebih fleksibel dan bisa dimodifikasi untuk tujuan ataupun konteks tertentu. Berdasarkan pada uraian diatas, maka penelitian ini ditujukan untuk mengetahui hasil evaluasi capability level pada proses teknologi informasi saat ini (as-is) dan yang diharapkan (to-be), serta merangkai usulan yang bisa dijabarkan dari hasil evaluasi. Penelitian ini dilakukan dengan metode pengumpulan data yang berupa observasi, wawancara dan kuesioner serta pengolahan data dengan COBIT 2019. Hasil yang ditemukan dari penelitian ini yaitu PT Telkom Akses memiliki capability level senilai level 3. Kesimpulan yang bisa diambil yaitu domain objektif DSS memiliki kriteria yang sesuai dengan pembahasan pada nilai capability level dan maturity level-nya. Tiap domain proses memberikan resultan tingkat kesenjangan sesuai dengan domain objektif pilihan dari desain faktor.
PENGEMBANGAN APLIKASI MENTALFIRST BERBASIS ANDROID SEBAGAI MEDIA DETEKSI AWAL PTSD DAN MEDIA INFORMASI SEPUTAR PTSD Chiuman, Felix; Akbar, Habibullah
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 14, No 1 (2023): JURNAL SIMETRIS VOLUME 14 NO 1 TAHUN 2023
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v14i1.9491

Abstract

Trauma merupakan tekanan emosional dan psikologis yang pada umumnya karena kejadian yang tidak menyenangkan atau pengalaman yang berkaitan dengan kekerasan. Secara umum, ada banyak faktor yang bisa menyebabkan seseorang mengalami trauma, termasuk peristiwa menyedihkan, mengguncang jiwa, hingga mengancam nyawa. Ini karena kejadian traumatis dapat menyebabkan gangguan streess pasca trauma (PTSD). Untuk mengatasi kesulitan ini, peneliti melakukan pengembangan sebuah aplikasi berbasis Android yang berfungsi sebagai media deteksi awal PTSD dan juga sebagai media informasi yang berkaitan dengan penanganan PTSD. Aplikasi ini dikembangkan menggunakan metode Test Driven Development dan menggunakan Kotlin dan XML sebagai bahasa pemograman dan layouting aplikasi serta, menggunakan Firebase sebagai back end nya. Test Driven Development sendiri merupakan pengembangan perangkat lunak yang menekankan testing sebelum coding  yang dimana menggunakan pendekatan Agile dan Extreme Programming.Dengan pengujian Black Box Testing aplikasi dapat berjalan dengan baik dan aplikasi ini memiliki nilai SUS (System Usability Scale) rata-rata sebesar 89.75. Aplikasi telah dipublikasi ke dalam Play Store dengan status pengujian terbuka. Dengan demikian, aplikasi “MentalFirst” ini diharapkan dapat membantu masyarakat dapat melakukan deteksi awal dan mendapatkan informasi yang berkaitan dengan PTSD.
Pengembangan Aplikasi Mobile Klasifikasi Penyakit Kulit Berbasis EfficientNet-B0, Arsitektur MVVM dan CI/CD Pipeline Astamar Putra, Ichlasul Fikri; Akbar, Habibullah
Jurnal Ilmiah Komputasi Vol. 23 No. 4 (2024): Jurnal Ilmiah Komputasi : Vol. 23 No 4, Desember 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.23.4.3676

Abstract

Penyakit kulit sering dianggap sebagai hal yang normal, tetapi dalam beberapa kasus, penyakit kulit dapat berbahaya dan mematikan dan seringkali dianggap abaikan oleh masyarakat luas. Disisi lain, saat ini teknologi berperan penting dalam kehidupan manusia sehari – hari sehingga aplikasi pada smartphone menjadi kebutuhan harian. Penelitian ini akan menjelasakan mengenai pengembangan aplikasi kesehatan kulit yang mengintegrasikan model machine learning dalam penggunaan aplikasi mobile berbasis Android menggunakan metode pengembangan Extreme Programming yang mengedepankan fleksibilitas dan responsif tergantung kebutuhan pengguna juga menekankan komunikasi yang erat antara tim pengembang. Selain itu penelitian ini juga berfokus dalam penerapan pada arsitektur aplikasi yang di rekomendasi oleh Android yaitu menggunakan Model-View-ViewModel (MVVM) dengan tingkat pengujian Black-Box Testing yang memuaskan dan nilai System Usability Scale 92 menandakan aplikasi yang dibuat harapannya dapat diterima dan membantu masyarakat sebagai penanganan tahap awal atau para profesional kesehatan, termasuk dermatologis dalam memberikan perawatan yang lebih baik dan lebih tepat bagi pasien yang mengalami masalah kulit.
Game Edukasi Berbasis Augmented Reality (AR) Menggunakan Metode Marker-Based Tracking dalam Perancangan Aplikasi Tata Surya Aryani, Diah; Noviandi, Noviandi; Fatonah, Nenden Siti; Akbar, Habibullah
JUKI : Jurnal Komputer dan Informatika Vol. 6 No. 2 (2024): JUKI : Jurnal Komputer dan Informatika, Edisi Nopember 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Augmented Reality (AR) technology has had a positive impact on education, particularly in improving the quality of learning and creating an interactive learning environment. This research aims to design a solar system application based on AR as an alternative learning media that integrates 3D models, animations, and videos to enhance the learning experience of students, especially at SDN Larangan 5 Tangerang. The background of this research is the lack of variety in teaching the solar system material at the school, which still relies on textbooks and videos without utilizing AR technology. The method used in this study is Marker-Based Tracking, which involves the use of specific markers to detect objects and display information as well as 3D models of the planets in the Solar System on the device screen. By using this method, the application provides a more interactive and immersive learning experience. For usability testing, the System Usability Scale (SUS) method was used, involving 33 respondents, including teachers, students, and parents. The test results yielded a score of 78, indicating a high level of user satisfaction with the application. This study is expected to be a first step in the application of AR technology to support learning innovation, particularly in enhancing students' understanding of the solar system concept
IMPLEMENTASI DEEP LEARNING TERHADAP PRESENSI MAHASISWA MENGGUNAKAN METODE MTCNN DAN FACENET : (STUDI KASUS: KAMPUS ESA UNGGUL BEKASI) Latumapayahu, Febrian Firmansyah; Herwanto, Agus; Akbar, Habibullah; Prabowo, Ary
Kohesi: Jurnal Sains dan Teknologi Vol. 7 No. 3 (2025): Kohesi: Jurnal Sains dan Teknologi
Publisher : CV SWA Anugerah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.3785/kohesi.v7i3.11681

Abstract

The development of digital technology has opened opportunities for educational institutions to improve the efficiency and accuracy of administrative systems, including student attendance recording. The current attendance system, which relies on RFID cards, often encounters issues such as damaged, lost, or unreadable cards, leading to long queues and the need for manual administration. This study aims to address these problems by developing an automatic attendance system based on facial recognition using deep learning technology. The proposed system integrates the Multi-task Cascaded Convolutional Neural Networks (MTCNN) algorithm for face detection and FaceNet for face recognition. Data collection is conducted by acquiring student facial images as the dataset for model training. The data is processed through normalization, face detection, and feature extraction using FaceNet embeddings. The system is integrated with a MySQL database to record student attendance in real time. Testing results show that the system performs well in detecting and recognizing student faces with satisfactory accuracy levels, despite variations in lighting conditions. By reducing dependency on physical cards, this system can streamline the attendance process and provide ease of use for users. This study demonstrates that the application of deep learning technology has the potential to improve the efficiency of attendance management in higher education institutions.
Co-Authors Adi Widiantono Agus Satriawan Aisyah, Zhavira Alexander Alexander, Alexander Alvin Barata Amelia Sholikhaq Andini, Ketrin Vani Andriana, Dian Andriyanti Asianto Anwar Nasihin Ardiansyah, Miri Ari Pambudi Arif Pami Setiaji Asianto, Andriyanti Astamar Putra, Ichlasul Fikri Azizah, Anik Hanifatul Bob Tjahjono Budi Tjahjono Calvin Ramadhani Alfahrezi Chiuman, Felix Delio, Ferdinand Defin Deni Pamungkas Gelantoro Putra Diah Aryani Diah Aryani, Diah Dodo, La Dudy Fathan Ali Dwi Pamungkas, Eric Dwiputra, Dedy Elvaret Eric Dwi Pamungkas Fathan Ali, Dudy Fatonah, Nenden Siti Franky Leonard Gerry Firmansyah Gilang Banuaji Hadi, Muhammad Abdullah Hafizah Safira Kaurani Hani Dewi Ariessanti Haryoto, Iin Sahuri Hendy Hendy Herwanto, Agus Husni Sastra Mihardja Husni Satra Mihardja Husni Satra Mihardja Indri Handayani, Indri Intan Setya Palupi La Dodo Latumapayahu, Febrian Firmansyah Mahmudin, Hajon Mahdy Martin Saputra, Martin Marwan Kadhim Mohammed Al-shammari Marzuki Pilliang Mochamad Wahyudi Mohamad Yusuf Mohammed Al-shammari, Marwan Kadhim Muhamad Bahrul Ulum Muhamad Bahrul Ulum Muhammad Fajrul Aslim Muhammad Yusuf Morais Mukhamad Abduh MUNAWAR Munawar Munawar Nainggolan, Restamauli br Nanna Suryana Herman Narul Sakron Nasihin, Anwar Nenden Siti Fatonah Nenden Siti Fatonah Nila Rusiardi Jayanti Nizirwan Anwar Noviandi Noviandi Noviandi Noviandi, Noviandi Nugroho Budhisantosa Nugroho, Irfan Hari Pilliang, Marzuki Prabowo, Ary Pramesty, Feranti Destina Puryanto, Jonathan Aditya Putra, Sipky Jaya Rachman, Riyandi Patu Ramadhan, Noval Rizky Randy Swandy Reyhan, Athallah Rifqi Adi Prasetya Rizky Yananda Rosnanto, Imam Rudi Heri Marwan Rudy Setiawan Sabri Alim Sakron, Narul Sandfreni, Sandfreni Saputra, Rahdian Sea, Rona Aulia Wangsa Sejati, Puteri Setiawati, Popong Sfenrianto Sfenrianto Sinaga, Matius Eliezer Suardana, Made Aka Suhandi Junaedi Supriyade Supriyade Supriyade, Supriyade Sutanto, Imam Syahrizal Dwi Putra Syahrizal Dwi Putra Tantrisna, Ellen Tardiana, Arisandi Langgeng Tartila, Gilang Romadhanu Ulum, M. Bahrul Widodo , Agung Mulyo Widodo, Agung Mulyo Wijaya, Jacob S Yaya Sudarya Triana