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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Generic Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Klik - Jurnal Ilmu Komputer Jurnal Indonesia Sosial Sains ILTEK : Jurnal Teknologi Ekasakti Matua Jurnal Manajemen JT-IBSI (Jurnal Teknik Ibnu Sina) Jurnal Ekonomi dan Bisnis
Saputra, Tommy
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Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Neuroscience Physics Social Sciences

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Heart Chamber Segmentation in Cardiomegaly Conditions Using the CNN Method with U-Net Architecture Saputra, Tommy; Nurmaini, Siti; Roseno, Muhammad Taufik; Syaputra, Hadi
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 12 No. 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1976

Abstract

Cardiomegaly is a disease in which sufferers show no symptoms and have symptoms such as shortness of breath, abnormal heartbeat and edema. Cardiomegaly will cause the sufferer's heart to pump harder than usual. Early diagnosis of cardiomegaly can help make decisions about whether the heart is abnormal or normal. In addition, due to the problem that manual examination takes time and requires human interpretation and experience, tools are needed to automatically develop and identify normal and abnormal hearts. Therefore, this study proposes cardiac chamber segmentation using 2D (two-dimensional) ultrasound convolutional neural networks for rapid cardiomegaly screening in clinical applications based on heart ultrasound examination. The proposed approach uses a CNN with a U-Net architecture model with abnormal and normal heart data. The research results obtained used the pixel matrix evaluation Avg_accuracy of 99.50%, Val_accuracy of 97.98% and Mean_IoU of 90.01%.
Pengaruh Influencer Marketing Terhadap Niat Beli Produk Virtual Skin pada Game Mobile Legends Bang-Bang Yuritanto, Yuritanto; Sofian, Hocky; Armansyah, Armansyah; Saputra, Tommy
Surplus: Jurnal Ekonomi dan Bisnis Vol. 3 No. 2 (2025): Januari-Juni 2025
Publisher : Yayasan Pendidikan Tanggui Baimbaian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71456/sur.v3i2.1156

Abstract

Penelitian ini bertujuan mengkaji pengaruh Influencer Marketing terhadap niat beli produk virtual skin secara simultan pada mahasiswa STIE Tanjungpinang dengan pendekatan kuantitatif. Sampel penelitian melibatkan 51 mahasiswa yang dipilih menggunakan teknik purposive sampling. Data diperoleh melalui kuesioner dan studi pustaka, lalu dianalisis menggunakan uji kualitas data, asumsi klasik, regresi linear berganda, dan hipotesis dengan SPSS 22. Hasil menunjukkan nilai t hitung Influencer Marketing sebesar 9,891 (t tabel 2,008, sig. 0,000), sehingga H1 diterima. Pengaruh variabel ini terhadap niat beli adalah 66%, sisanya dipengaruhi faktor lain. Influencer Marketing efektif dalam membangun citra merek dan merangsang respons positif konsumen melalui platform online, memberikan kesempatan bagi influencer untuk memengaruhi sikap dan perilaku konsumen. Pemasaran melalui influencer berdampak signifikan pada niat beli produk Virtual Skin dalam game Mobile Legends Bang-Bang, dengan nilai uji statistik menunjukkan pengaruh yang positif dan signifikan.
Sistem Informasi Pengelolaan Manajemen Hotel pada Hotel Planet Holiday Berbasis Web Mobile Dwiputri Permatasari, Ririt; Paulina Suri, Ghea; Marchiano, Herli; Saputra, Tommy
Jurnal Indonesia Sosial Sains Vol. 3 No. 05 (2022): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v3i05.599

Abstract

This study aims to design a mobile web-based hotel management information system at Planet Holiday Hotels, the background of this research is for problems that often occur in the management structure of Planet Holiday Hotels, namely the placement and compilation of data collection that is less than optimal at the time of the recap of employee data collection in position or department data so that the positions that are already full are entered into the Planet Holiday Hotel data collection which has various departments where there will be a data crosscheck process, they have to wait for the next data collection which will take a long time. The stages are literature study, data collection, data processing, system design, implementation, testing and deployment. Meanwhile, the method and modeling used is the Rational Unfield Process (RUP) and the modeling is using the Unfield Modeling Language (UML). This information system is designed based on a mobile web made with Process Hypertext Preprocessor (PHP), Cascading Style Sheet (CSS) technology, which was built using Xampp as a web server. With the existence of a management structure information system at Hotel Planet Holiday, it is hoped that the results of the research carried out can be concluded that it can help media information management become easier, system managers such as Human Resources can easily manage data collection and also employee data can be viewed in a timely manner. The management structure information system at Planet Holiday Hotel is expected to be able to collect data on the employee structure of the mobile web-based management structure information system so that it has a wider coverage and can help employees for efficient work programs.
Deteksi Lesi Pra-Kanker Serviks Pada Citra Kolposkopi Menggunakan Convolutional Neural Network dengan Arsitektur YOLOv7 Nurqolbiah, Fatihani; Nurmaini, Siti; Saputra, Tommy
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.7152

Abstract

Pre-cancerous cervical lesions detection is crucial in the diagnosis and analysis of medical images. Because visual observations are weak, computer-based detection is needed. This research proposes a pre-cancerous cervical lesion detection model using a Convolutional Neural Network with the YOLOv7 architecture, capable of accurately detecting these lesions. The data used was 913 colposcopy image data from 200 cases. The dataset is divided into training and testing data, resulting in a detection model for pre-cancerous cervical lesions. The model achieves an mAP of 91.9%, precision of 87.7%, recall of 96%, and an F1-score of 93%. The study demonstrates that the performance of YOLOv7 indicates the model's ability to accurately detect pre-cancerous lesions in the cervix.
Klasifikasi Sinyal EEG Untuk Mengenali Jenis Emosi Menggunakan Recurrent Neural Network Utari, Aspirani; Rini, Dian Palupi; Sari, Winda Kurnia; Saputra, Tommy
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.7162

Abstract

This research focuses on in-depth exploration and analysis of the application of two types of Recurrent Neural Network (RNN), namely Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The two models are drilled with the same parameters, consist of three layer, use the relu activation function, and apply 1 dropout level. In order to compare the performance of the two, experiments were carried out using five groups of datasets for training and performance evaluation purposes. The evaluation includes metrics such as accuracy, recall, F1-score, and area under the curve (AUC). The dataset used is Eeg Emotion which contains 2458 unique variables. In terms of performance, LSTM succeeded in outperforming GRU in the task of classifying emotional data based on EEG signals. On the other hand, GRU shows advantages in accelerating the training process compared to LSTM. Although the accuracy of both methods is almost similar in all data divisions, in the evaluation of the ROC curve, the LSTM model demonstrates superiority with a more optimal curve compared to GRU.
Klasifikasi Kanker Payudara Menggunakan Metode Convolutional Neural Network (CNN) dengan Arsitektur VGG-16 Idawati, Idawati; Rini, Dian Palupi; Primanita, Anggina; Saputra, Tommy
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 3 (2024): Maret 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.7553

Abstract

Breast cancer classification is a process to determine the type and characteristics of breast cancer based on the characteristics of cancer cells. In this research, a system is designed to classify breast cancer using ultrasound images which are then processed using the Convolutional Neural Network method with the VGG-16 architecture. The aim of the research is to develop a breast cancer classification system using Convolutional Neural Network (CNN) and evaluate the classification results using Convolutional Neural Network (CNN) with the VGG-16 architecture. In breast cancer classification, three classes are considered: normal, benign, and malignant. The steps in the classification process include image input, filtering, resizing, data augmentation, and data digitization. The best results were obtained in this test using the SGD optimizer hyperparameter, learning rate 0.001, epoch 20 and batch size 32 producing an accuracy value of 78.87%, a precision value of 75.69%, an AUC value of 79.85% and an f1 score value of 74.67%.
PENENTUAN INDIKATOR PENGUKURAN KINERJA PEGAWAI BIDANG PERLINDUNGAN LINGKUNGAN HIDUP DI DINAS LINGKUNGAN HIDUP KOTA BATAM Bora, M. Ansyar; Saputra, Tommy; Haslindah, Andi
ILTEK : Jurnal Teknologi Vol. 15 No. 02 (2020): ILTEK : Jurnal Teknologi
Publisher : Fakultas Teknik Universitas Islam Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47398/iltek.v15i02.26

Abstract

Instrumen penilaian kinerja dapat digunakan untuk mereview kinerja, peringkat kerja, penilaian kinerja, penilaian pegawai, dan sekaligus evaluasi pegawai sehingga dapat diketahui mana pegawai yang mampu melaksanakan pekerjaan secara baik, efisien, efektif dan produktif sesuai dengan tujuan. Kinerja pegawai merupakan suatu hal yang sangat penting dalam upaya perusahaan untuk mencapai tujuannya. Indikator kinerja merupakan kriteria yang digunakan untuk menilai keberhasilan pencapaian tujuan organisasi yang diwujudkan dalam ukuran-ukuran tertentu. Penelitian ini ditujukan untuk menentukan indikator pengukuran kinerja pegawai Bidang Perlindungan Lingkungan Hidup Kota Batam. Hasil dari penelitian ini adalah bahwa penentuan indikator kinerja Bidang Perlindungan Lingkungan Hidup pada Dinas Lingkungan Hidup Kota Batam diukur dengan menggunakan metode AHP (Analytical Hierarchy Process). Terdapat 12 (dua belas) indikator pengukuran kinerja Bidang Perlindungan Hidup berdasarkan visi dan misi yang ditetapkan oleh institusi. Dari pembobotan indikator kinerja tersebut didapatkan bahwa tersedianya data kualitas lingkungan menjadi skala prioritas terpenting yang harus dicapai oleh bidang lingkungan hidup yaitu 19,56%. Setelah itu pengolahan data menjadi informasi menjadi skala terpenting berikutnya, yaitu sebesar 18,18%. Pembinaan sektor formal maupun informal menjadi skala terpenting selanjutnya yaitu 12,42%.
Co-Authors Anita Desiani Armansyah Armansyah Darmawahyuni, Annisa Dian Palupi Rini Erwin Erwin Fachry Abda El Rahman Fauzan, Haidil Febriady, Mukhlis Haslindah, Andi Hernando, Luki Hidayat, Hendri Idawati Idawati M. Ansyar Bora Marchiano, Herli Muhammad Naufal Rachmatullah Muhammad Taufik Roseno, Muhammad Taufik Nurqolbiah, Fatihani Paulina Suri, Ghea Primanita, Anggina Putri Mirani Ririt Dwiputri Permatasari Salsabila, Tia Andini Sanusi Sapitri, Ade Iriani Shilah, Nur Sinta Bella Agustina Siti Nurmaini Sofian, Hocky Syaputra, Hadi Teisnajaya, Usep Twenty Agustine, Grace Ubaidillah Ubaidillah Utari, Aspirani Winda Kurnia Sari Yudha Pratomo Yuritanto, Yuritanto