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Analisis Prediksi Jangka Panjang COVID 19 Fase ke 3 di Indonesia menggunakan Deep Learning Herferry, Ibrahim Ade; Ferdiansyah, F; Kunang, Yesi Novaria; Purnamasari, Susan Dian
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.474

This research is motivated by the ongoing impact of the COVID-19 pandemic, which continues to pose challenges for Indonesia, affecting both the economy and daily life. Therefore, this study will discuss long-term predictions for the third phase of COVID-19 in Indonesia using a Deep Learning model. The analysis aims to assist various stakeholders in developing better planning strategies to address COVID-19 in Indonesia. In conducting this research, the author employs neural networks to create a hybrid model combining GRU and LSTM algorithms. Utilizing RMSE and MAPE values, it can be concluded that the model's performance in predicting COVID-19 cases is influenced by the number of epochs used. Furthermore, the model demonstrates optimal performance at 150 epochs for predicting the number of COVID-19 cases in the next 7 days

Intern Placement and Monitoring System at SMK YP Gajah Mada Palembang Faridiansyah, M.Faridiansyah; Irawan, Dedi; Purnamasari, Susan Dian; Suyanto, Suyanto
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4473

In today's technological era, web-based solutions are essential for optimizing the distribution of internship placements. The current manual processes can lead to issues such as placement delays and difficulties in data collection. This research proposes the implementation of a web-based system to streamline the internship program at SMK YP Gajah Mada, focusing on developing an efficient and user-friendly platform. The objective of this research is to build a web-based internship placement and monitoring system at SMK YP Gajah Mada Palembang. The methodology used in this study is Rapid Application Development (RAD), an alternative to traditional system life cycles. The implementation of this system is expected to improve placement processes, enhance data management, and provide a more effective way to monitor and support interns throughout their program. The results of the research indicate that the web-based system significantly reduces placement delays, facilitates data collection, and offers a structured approach to monitoring and managing internship activities.

Clustering Data Penyakit Pasien Pada Puskesmas Mulyaguna Menggunakan Algoritma K-Means Ziqrullah, Muhammad Hafiz; Andri, Andri; Purnamasari, Susan Dian; Yadi, Ilman Zuhri
Jurnal Media Informatika Vol. 6 No. 1 (2024): Jurnal Media Informatika Edisi September - Desember
Publisher : Lembaga Dongan Dosen

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

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Besemah Language Translation Machine Model Based on Machine Learning with Recurrent Neural Network (RNN) Model Algorithm Andika, Muhamad; Kunang, Yesi Novaria; Yadi, Ilman Zuhri; Purnamasari, Susan Dian
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 1 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i1.2614

Indonesia consists of various tribes with their respective regional languages, one of which is the Besemah tribe in South Sumatra Province with its language culture, namely the Besemah Language. Until now, the Besemah Language is still used by the Besemah tribe, but over time the number of Besemah Language speakers has decreased, plus most of the wider community does not know what the Besemah Language is. Machine Learning is a part of artificial intelligence that is often used to solve various problems. Machine Learning involves the use of computers and mathematical algorithms that use data to make predictions in the future. Machine translation is a tool that can convert one language to another. This study aims to collect datasets in the form of sentences and words from the Besemah Language, then create a Besemah Language translation machine to Indonesian and vice versa. In the research conducted, the approach used is Experimental Research in Machine Learning. Experimental research in machine learning for language translation is a research approach that involves designing and implementing a series of experiments to test and validate the performance of the language translation model. In this study, Neural Machine Translation (NMT) technology was applied with the Recurrent Neural Network (RNN) approach. The results of the study showed that the val_accuracy value for the Besemah-Indonesian translation was 0.8469 and for Indonesia-Besemah was 0.8492, in the translation trial conducted using the RNN model, 100 epochs, batch size 64, and validation split of 0.2.

Clustering OKU Timur Script Images using VGG Feature extraction and K-Means Toriko, Liu; Purnamasari, Susan Dian; Kunang, Yesi Novaria; Yadi, Ilman Zuhri; Andri, Andri
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 1 (2025): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i1.2292

This study focuses on the utilization of clustering models to group manuscript images from the OKU Timur region based on specific characteristics. OKU Timur is rich in cultural heritage, including a unique writing system known as the OKU Timur script. The development of intelligent systems technology can be employed to recognize the OKU Timur script. For this purpose, a dataset of OKU Timur script is needed, which will later be used for classifying script images. One of the challenges in preparing the dataset is grouping a large number of script image samples according to the number of characters. A proposed solution in this research is to automatically group script images by applying the K-Means algorithm. The dataset comprises 2,280 images, representing 19 characters and 228 variations with different diacritics. Features are extracted using the VGG16 model, which are then clustered with the K-Means algorithm. Clustering performance is evaluated based on the percentage of correctly grouped characters. For 19 groups (character count), the model achieves an accuracy of 82.6%. For 228 groups (variations and diacritics), it correctly groups 48.16% of characters. Despite the challenges, the results demonstrate the model’s potential for further refinement. This study’s contribution lies in introducing an efficient clustering approach for cultural manuscripts, supporting digital preservation, and advancing automatic recognition of the OKU Timur script. These efforts aim to preserve the script for future generations.

Pelatihan Service Attitude dan Psikologi Sosial untuk Meningkatkan Interaksi Pelayanan di Dinas Kependudukan dan Pencatatan Sipil Kota Palembang Ningsih, Erda Surya; Mawardah, Mutia; Purnamasari, Susan Dian; Fatmasari, Fatmasari
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 4 (2025): Juni
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i4.2551

Pelayanan administrasi kependudukan berperan penting dalam membangun kepercayaan masyarakat terhadap pemerintah. Kegiatan pengabdian di Disdukcapil Kota Palembang ini bertujuan meningkatkan kualitas layanan publik melalui pelatihan “Service Attitude dan Psikologi Sosial” bagi petugas loket. Menggunakan metode observasi partisipatif dan workshop selama magang Februari–Mei 2025, pelatihan ini menunjukkan peningkatan empati, komunikasi dua arah, dan pengelolaan emosi petugas. Selain itu, kerja sama tim dan inisiatif kolektif juga semakin kuat. Analisis tematik dan normatif-kritis menunjukkan bahwa pelatihan ini turut mentransformasi budaya layanan publik menjadi lebih inklusif, manusiawi, dan berfokus pada kebutuhan warga.

Dampak Penggunaan Teknologi Wearable terhadap Gaya Hidup dan Perilaku Kesehatan Mahasiswa di Universitas Bina Darma Mawardah, Mutia; Purnamasari, Susan Dian; Oktaviani, Nia
Jurnal Ilmiah Psyche Vol. 19 No. 1 (2025): Jurnal Ilmiah Psyche : Ilmu Psikologi
Publisher : Direktorat Riset dan Pengabdian Masyarakat Universitas Bina Darma Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/3qvecg20

Dampak Penggunaan Teknologi Wearable terhadap Gaya Hidup dan Perilaku Kesehatan Mahasiswa di Universitas Bina Darma

Segmentasi Citra Formulir Menggunakan Bounding box untuk Pengambilan Objek Gambar Alhafiz, Alhafiz; Purnamasari, Susan Dian; Novaria Kunang, Yesi; Zuhri Yadi, Ilman; Effendy, Irman
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 9 (2025): JPTI - September 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.1071

Penelitian ini bertujuan mengembangkan metode segmentasi citra berbasis bounding box dan teknik cropping untuk mengisolasi karakter aksara OKU Timur sebagai upaya pelestarian budaya lokal. Data dikumpulkan melalui kuesioner yang melibatkan 102 responden, masing-masing menulis karakter aksara pada lembar khusus. Eksperimen dilakukan pada lima sampel gambar yang berisi karakter serupa, namun ditulis oleh individu berbeda, guna menguji konsistensi dan ketahanan metode terhadap variasi tulisan tangan. Proses segmentasi dievaluasi menggunakan metrik kuantitatif, yaitu precision, recall, F1-score dan akurasi, dengan hasil rata-rata precision 71,76%, recall 78,33%, F1-score 74,9%, dan akurasi 78,33%. Hasil terbaik mencapai akurasi 100%, sedangkan hasil terendah 33,33%, menunjukkan adanya variasi tingkat keberhasilan segmentasi. Temuan ini menegaskan bahwa pendekatan yang diusulkan cukup efektif dalam mengidentifikasi karakter aksara meskipun terdapat perbedaan gaya penulisan. Kontribusi utama penelitian ini adalah menyediakan solusi digitalisasi aksara tradisional berbasis pengolahan citra, yang dapat mendukung upaya pelestarian dan pengembangan teknologi pengenalan karakter untuk aksara daerah.

Intern Placement and Monitoring System at SMK YP Gajah Mada Palembang Faridiansyah, M.Faridiansyah; Irawan, Dedi; Purnamasari, Susan Dian; Suyanto, Suyanto
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4473

In today's technological era, web-based solutions are essential for optimizing the distribution of internship placements. The current manual processes can lead to issues such as placement delays and difficulties in data collection. This research proposes the implementation of a web-based system to streamline the internship program at SMK YP Gajah Mada, focusing on developing an efficient and user-friendly platform. The objective of this research is to build a web-based internship placement and monitoring system at SMK YP Gajah Mada Palembang. The methodology used in this study is Rapid Application Development (RAD), an alternative to traditional system life cycles. The implementation of this system is expected to improve placement processes, enhance data management, and provide a more effective way to monitor and support interns throughout their program. The results of the research indicate that the web-based system significantly reduces placement delays, facilitates data collection, and offers a structured approach to monitoring and managing internship activities.

Besemah Language Translation Machine Model Based on Machine Learning with Recurrent Neural Network (RNN) Model Algorithm Andika, Muhamad; Kunang, Yesi Novaria; Yadi, Ilman Zuhri; Purnamasari, Susan Dian
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 1 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i1.2614

Indonesia consists of various tribes with their respective regional languages, one of which is the Besemah tribe in South Sumatra Province with its language culture, namely the Besemah Language. Until now, the Besemah Language is still used by the Besemah tribe, but over time the number of Besemah Language speakers has decreased, plus most of the wider community does not know what the Besemah Language is. Machine Learning is a part of artificial intelligence that is often used to solve various problems. Machine Learning involves the use of computers and mathematical algorithms that use data to make predictions in the future. Machine translation is a tool that can convert one language to another. This study aims to collect datasets in the form of sentences and words from the Besemah Language, then create a Besemah Language translation machine to Indonesian and vice versa. In the research conducted, the approach used is Experimental Research in Machine Learning. Experimental research in machine learning for language translation is a research approach that involves designing and implementing a series of experiments to test and validate the performance of the language translation model. In this study, Neural Machine Translation (NMT) technology was applied with the Recurrent Neural Network (RNN) approach. The results of the study showed that the val_accuracy value for the Besemah-Indonesian translation was 0.8469 and for Indonesia-Besemah was 0.8492, in the translation trial conducted using the RNN model, 100 epochs, batch size 64, and validation split of 0.2.

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