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Puspita, Heni
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Rancang Bangun Content Management System Pada Website Riset Fakultas Teknik Universitas Nurtanio Menggunakan Bahasa Pemrograman PHP Dan MySQL Ali, Abdul Latif; Satyawan, Arief Suryadi; Wulandari, Ike Yuni; Puspita, Heni
Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (SENASTINDO) Vol. 4 (2022): Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo)
Publisher : Akademi Angkatan Udara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54706/senastindo.v4.2022.168

Abstract

The development of information and communication technology has had a major impact on human life along with the easier it is to obtain information through the internet. The need for the internet is very high, especially in the world of education and especially universities. The emergence of internet technology that exists today has become a tool used to ease human work, especially in the field of websites. Website is a form of implementation of a programming language. Hypertext Preprocessor (PHP) is a web-based programming language that has the ability to process and process website data that is run by the MySQL server as a database. One that can be used for dynamic website creation is content management system (CMS) technology. This website design aims to make it easier for admin managers and kontributors to provide more interactive information to research students and lecturers in developing an autonomous electric vehicle website. This study uses a system development method in the form of a Software Development Life Cycle (SDLC) with a prototype model, namely software development in the form of a physical system work model and functions as an initial version of the system. In testing the CMS using black-box testing with boundary value analysis techniques that focus on input and output data. Based on the research and testing process that has been carried out successfully, the CMS dashboard page on the engineering faculty research website is able to process data dynamically and provide convenience for admin managers and kontributors in the development of autonomous electric vehicles.
SEGMENTASI OBJEK BERBASIS GAMBAR TERMAL MENGGUNAKAN DEEP LEARNING (PRE-TRAINED RESNEXT 50) Fauzan, R. Aldam Dwi; Satyawan, Arief Suryadi; Siswanti, Sri Desy; Puspita, Heni
Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (SENASTINDO) Vol. 4 (2022): Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo)
Publisher : Akademi Angkatan Udara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54706/senastindo.v4.2022.207

Abstract

The transportation sector at this time has experienced many technological developments which have been well receifed by the public, especially the people of Indonesia. Along with the development of transportation technology has undergone many developments, with sophistication and increased comfort and better security. So Autonomus Car technology was created that can help drivers to maintain safety while driving. Autonomus car was built using the Neural Network control method, and also Image Processing as signal processing with image input, and with a flip camera used for vehicle input data. Autonomous cars have many positive impacts on human life today, so humans can minimize time properly. Travel safety is maintained, and can be more productive when driving. The method that is currently developing rapidly is automatic extraction using deep learning. In this final project, automatic extraction method with deep learning technology used is Fully Convolutional Network (FCN) with Residual Neural Network Next (ResNext) architecture. In this study, the extraction accuracy for automatic vehicle function training reached 98% for ResNext 50 with a resolution of 640x540 pixels. Semantic segmentation will then test with 34030 image frames offline. In ResNext 50 architecture contains 20512 frames in good category, 7883 in adequate category and 5605 in poor category.
SEGMENTASI OBJEK BERBASIS GAMBAR THERMAL MENGGUNAKAN DEEP LEARNING (PRE-TRAINED RESNET101 Harahap, Taufiq Hidayat; Satyawan, Arief Suryadi; Wulandari, Ike Yuni; Puspita, Heni
Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (SENASTINDO) Vol. 4 (2022): Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo)
Publisher : Akademi Angkatan Udara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54706/senastindo.v4.2022.211

Abstract

Currently, the car is one of the means of transportation that is widely used by many people and it has become a necessity to have a car to help users move more easily. Car technology continues to be developed by experts, including steering aid systems and safety for car users, such as automatic reading of objects and road boundaries that can be useful for both things. This system was built using the Fully Convolutional Network (FCN) method with Residual Neural Network (ResNet) architecture, and also Image Processing as signal processing with image input, and with a thermal Flir camera as vehicle input data. The data generated by this thermal camera is labeled first and then trained so that it can segment objects correctly according to their classification. In this study, the extraction accuracy of the training generated by the autonomous vehicle feature can reach 96.27% for ResNet 101 with a resolution of 640x480 pixels. As for suggestions for development to be even better in terms of segmentation, namely by using more training data than is used now and shooting locations for datasets in different places from the current research.
SEGMENTASI OBJEK BERBASIS GAMBAR THERMAL MENGGUNAKAN DEEP LEARNING (PRE-TRAINED RESNET 152) Noviely, Isra Fanliv; Satyawan, Arief Suryadi; Puspita, Heni
Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (SENASTINDO) Vol. 4 (2022): Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo)
Publisher : Akademi Angkatan Udara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54706/senastindo.v4.2022.215

Abstract

The latest technological developments in the field of Artificial Intelligence have very rapid capabilities and are able to produce systems that facilitate human activities, especially in the field of transportation, especially driving cars or autonomous electric cars. Artificial Intelligence technology itself is able to support success for object detection by detecting objects using semantic segmentation. Neural Network and Image processing are methods used to detect objects semantically as input signal processing in the form of images, and the FLIR thermal camera is used as input from the vehicle. The deep learning method uses a Fully Convolutional Network (FCN) with a Residual Network (ResNet) architectural model as its feature extraction. ResNet is an architectural model from FCN that works from this architectural model not to decline even though the architecture is getting deeper, so it can help humans to drive more productively. The method used in this final project is automatic extraction using deep learning technology with Residual Neural Network 152 (ResNet) architecture. The performance of the semantic segmentation system was tested with 3040 image frames offline using 800 labeled data sets. This method has an extraction accuracy for autonomous vehicle function training reaching 96% with a resolution of 640x512 pixels. The performance of the segmentation system resulted in 18576 image frames in good category, 9333 image frames in sufficient category and 6121 image frames in poor category.
Analisis Penokohan Novel "Iavanna Van Dijk" Karya Risa Saraswati melalui Pendekatan Psikologi Sastra Puspita, Heni
Kajian Sastra Nusantara Linggau Vol. 1 No. 1 (2021): Jurnal Kastral
Publisher : LP3MKIL

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (88.151 KB)

Abstract

Penelitian ini bertujuan untuk mendeskripsikan psikologi sastra dengan aspek id, ego,dan superego pada penokohan protagonis, antagonis dan tritagonis dalam novel Ivanna Van Dijk karya Risa Saraswati. Penelitian ini termasuk jenis penelitian deskriptif kualitatif dengan metode content analysis. Pengumpulan data dalam penelitian ini menggunakan teknik pustaka catat. Pengambilan data dilakukan dengan cara membaca dan selanjutnya diteliti dengan aspek psikologi dalam penokohan protagonis, antagonis dan tritagonis. Hasil penelitian menunjukkan penokohan protagonis terdapat pada tokoh Ivanna, Suzie dan Charles yang memiliki karakter penyayang, toleransi yang tinggi, dan menunjukkan kebenaran. Selanjutnya penokohan protagonis terdapat pada tokoh Rudolf Brouwer dan tokoh Ivanna yang memiliki perubahan karakter yang mana ditunjukkan ketika Ivanna membalasakan dendamnya pada semua bangsa Netherland. Dan selanjutnya penokohan tritagonis pada tokoh Peeter, Dimas, Syaiful, Elizabeth, Nyonya Sari dan Matsuya merupakan tokoh penghubung dan pelerai tokoh protagonis dan tokoh antagonis. Kemudian dilihat dari segi psikologi sastra yang meliputi aspek id (Das Es) yang mencangkup berbagai luapan emosi, kepercayaan diri, dan kesenangan. Selanjutnya pada aspek ego (Das-Ich) yang mencakup rasa mengalah, dan keyakinan. Sedangkan pada aspek superego (Uber-Ich) yang mencakup rasa penyesalan, dan rasa mencintai. Kata kunci: Penokohan, psikologi sastra
PENINGKATAN KEMAMPUAN MENULIS PARAGRAF DESKRIPTIF SISWA KELAS X SMA NEGERI 02 BENGKULU TENGAH DENGAN MENGGUNAKAN METODE MENULIS BERANTAI (ESTAFET WRITING) Puspita, Heni
Diksa : Jurnal Pendidikan Bahasa dan Sastra Indonesia Vol. 2 No. 2 (2016): Diksa : Jurnal Pendidikan Bahasa dan Sastra Indonesia
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (672.63 KB) | DOI: 10.33369/diksa.v2i2.3456

Abstract

The purpose of this study for improve the students class X1 skill of SMAN 2 Central Bengkulu Tengah in write descriptive paragraph with estafet writing method. This study design is the design of classroom action research conducted in two cycles, the first cycle and the second cycle. Collecting data on the first cycle and the second cycle using test technique and nontest. The test used is a test action in the form of assignment to write a description, whereas nontest techniques used in the form of guidelines for observation, the journal guidelines, interview guides, and photo documentation guidelines. Data analysis technique of this research is qualitative and quantitative. Quantitative techniques are used to analyze and compare test results pre-cycle, the first cycle, the second cycle, and qualitative techniques used to analyze and compare the results nontest in the first cycle and the second cycle. Based on the analysis of research data, in class X1 totaling 30 students can be concluded that by using the estafet writing method can increase the skill of writing a paragraph descriptive. In the first cycle, the value of an average of 71.65% in the second cycle, the average value of 88.73%, an increase of 17.08%. This means that there is an increase in the skill of writing a paragraph descriptive of the students with estafet writing method. This increase can be seen from the results of tests conducted students in class X SMAN 2 Central Bengkulu 2016/2017 school year that includes the end of the test cycle test cycle I and II.  
SYNTHESIS AND CHARACTERIZATION OF SnO2/ZnO COMPOSITE USING JAPANESE PAPAYA LEAF EXTRACT (Cnidoscolus aconitifolius) WITH HYDROTHERMAL METHOD Puspita, Heni; Agustin, Rika; Asdim; Angasa, Eka; Maryanti, Evi; Martono Hadi Putranto, Agus
SPIN JURNAL KIMIA & PENDIDIKAN KIMIA Vol. 6 No. 2 (2024): July - December 2024
Publisher : UIN Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20414/spin.v6i2.10997

Abstract

SnO2/ZnO composites were synthesized using the hydrothermal method using Japanese papaya (Cnidoscolus aconitifolius) leaf extract. This study aims to determine the effect of using Japanese papaya leaf extract (Cnidoscolus aconitifolius) on the formation of crystallinity and morphology in synthesizing SnO2/ZnO composites. Synthesis was carried out with variations in mass of 5, 10, and 15 grams using the hydrothermal method for 12 hours at 160°C. The results of X-Ray Diffraction (XRD) characterization show that wide diffractogram peaks are identified as the peaks of the SnO2 compound with a tetragonal structure and sharp peaks are identified as the peaks of the ZnO compound. The Fourier Transform Infrared (FTIR) characterization shows the peak wave number of 665 cm-1 which is the Sn-O-Sn strain and the peaks at wave numbers 598 cm-1 and 501 cm-1 which are the Zn-O strain. Characterization of Scanning Electron Microscopy (SEM) in the synthesis of SnO2/ZnO composites after adding Japanese papaya (Cnidoscolus aconitifolius) leaf extract had relatively reduced particle size and aggregate formation compared to no extract. The best effective mass of Japanese papaya leaf extract (Cnidoscolus aconitifolius) is the mass variation of 15 grams with 28.49 nm crystals.
A literature review and analysis of aviation training Puspita, Heni; Gaffar A, Ade; Setiawan, Agus; Widiaty, Isma; Wulandari, Ike Yuni; Andriana, Andriana
JPPI (Jurnal Penelitian Pendidikan Indonesia) Vol 10, No 3 (2024): JPPI (Jurnal Penelitian Pendidikan Indonesia)
Publisher : Indonesian Institute for Counseling, Education and Theraphy (IICET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/020243853

Abstract

Pelatihan penerbangan aspek yang sangat penting untuk memastikan keselamatan, efisiensi, dan kecakapan dalam industri penerbangan. Seiring dengan perkembangan industri penerbangan, program pelatihan akan terus memanfaatkan pendekatan inovatif untuk memastikan standar profesionalisme dan keselamatan tertinggi dalam operasi penerbangan. Pandangan komprehensif tentang pelatihan penerbangan melibatkan pemahaman mendalam tentang aspek-aspek kritis yang melibatkan persiapan individu untuk berbagai peran dalam industri penerbangan. Penelitian di bidang pelatihan penerbangan cenderung berfokus pada beberapa area kunci yang mempengaruhi keselamatan, efisiensi, dan kecakapan dalam operasi penerbangan. Penelitian ini bertujuan untuk melakukan evaluasi penelitian-penelitian bidang Aviation Training dengan menggunakan metode bibliometrik dengan jumlah artikel yang dikumpulkan sebanyak 1.421 dokumen dalam periode 1943 hingga 2021. Hasil penelitian menunjukkan bahwa dalam 10 tahun terakhir jumlah publikasi tentang Aviation Training mengalami peningkatan secara signifikan. United States merupakan negara yang paling banyak melakukan penelitian tentang Aviation Training dengan jumlah 561 artikel (39.5%) dan China adalah negara asia menduduki urutan kedua dalam penelitian Aviation Training sebanyak 125 artikel (12.8%).
Deteksi Wajah Tersamar Menggunakan Metode VGGFace dan SVM Siswanti, Sri Desy; Puspita, Heni; Ubaya, Huda; Selly, Selly; Herdiana, Dina
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 9 No. 2 (2025): Volume 9 Nomor 2 April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v9i2.14620

Abstract

Wajah adalah salah satu bagian dari manusia yang memiliki ciri-ciri berbeda. Teknologi pengenalan wajah merupakan suatu teknologi yang dapat mengidentifikasi atau memverifikasi seseorang dari sebuah gambar atau video. Teknologi pengenalan wajah bermanfaat untuk bidang keamanan, pengawasan, verifikasi identitas umum, sistem peradilan pidana, investigasi basis data gambar. Mungkin saja seorang DPO menggunakan penyamaran, baik secara sengaja maupun tidak sengaja, untuk menyembunyikan diri atau berpura-pura menjadi orang lain, misalnya menggunakan jenggot, kumis, dan gaya rambut yang diubah yang menyebabkan kebingungan dalam mengenali orang. Selain itu, aksesori penyamaran seperti wig, topi, syal, helm, kerudung, kacamata hitam, atau masker dapat membuat bagian wajah terlihat berbeda. Riasan tebal atau prosedur eksternal seperti operasi plastik juga dapat mengubah bentuk, tekstur, dan warna wajah, sehingga menyulitkan mengenali seseorang. Dalam makalah ini, mengusulkan sebuah algoritma pengenalan wajah tersamar,dimana algoritma ini mengubah arsitektur VGG pada tahap klasifikasi. Perubahan ini mencakup penambahan lapisan flatten yang disatukan dengan metode SVM. Tujuan dari modifikasi ini adalah untuk meningkatkan nilai akurasi dalam pengenalan wajah tersamar. Dalam penelitian ini memanfaatkan arsitektur VGG untuk ekstraksi fitur, SVM digunakan sebagai metode klasifikasi dalam pengenalan wajah. Sistem pengenalan wajah yang dikembangkan terdiri dari empat tahap utama: pengambilan data, pengolahan data, ekstraksi fitur, dan klasifikasi. Data wajah diambil secara langsung di depan kamera berupa wajah tanpa tersamar dan wajah tersamar dengan lima posisi wajah yaitu wajah menghadap ke kanan, ke kiri, ke depan,ke atas dan ke bawah. Sistem ini diimplementasikan menggunakan library Keras, Sklearn, dan Numpy untuk mengolah data. Untuk meningkatkan nilai akurasi diperlukan pengaturan parameter dari klasifikasi SVM yaitu Cost (C) dan gamma (ℽ). Hasil dari pengujian menunjukkan bahwa metode yang diterapkan dalam sistem pengenalan wajah tersamar ini menghasilkan nilai akurasi yang lebih baik dibandingkan dengan penelitian yang lain, walaupun masih ada beberapa kekurangan dari metode yang diterapkan dalam penelitian ini
360-degree Image Processing on NVIDIA Jetson Nano Satyawan, Arief Suryadi; Utomo, Prio Adjie; Puspita, Heni; Wulandari, Ike Yuni
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i2.722

Abstract

A wide field of vision is required for autonomous electric vehicles to operate object-detecting systems. By identifying objects, it is possible to imbue the car with human intelligence, similar to that of a driver, so that it can recognize items and make decisions to prevent collisions with them. Using a 360-degree camera is a wonderful idea because it can record events surrounding the car in a single shot. Nevertheless, 360º cameras produce naturally skewed images. To make the image appear normal but have a bigger capture area, it is required to normalize it. In this study, NVIDIA Jetson Nano is used to construct software for 360-degree image normalization processing using Python. To process an image in real-time, first choose the image shape mapping that can give information about the entire item that the camera collected. Then, choose and apply the mapping. Using Python on an NVIDIA Jetson Nano, the author of this research has successfully processed 360-degree images for local and real-time video as well as image geometry modifications.
Co-Authors Agus Setiawan Agustianti, Rifka Ali, Abdul Latif Alti, Rahmi Mudia Andriana Andriana Asdim Banowati, Lies Budiarto, Samsul Candra, Abel Bima Desi Arsita Eka Angasa Evi Maryanti Fauzan, R. Aldam Dwi Finasari, Sinta Nurul Gaffar A, Ade Harahap, Taufiq Hidayat Herdiana, Dina Hidayat Hidayat Huda Ubaya Isma Widiaty Iswarawati, N.K.E. Jaladhara, Aryo Paksi Kusumawijayanti, Anita Reta Martono Hadi Putranto, Agus Muharram, Bagus Adriyan Noviely, Isra Fanliv Perdana, Ferdian Yoga Putri, R.A. Reza Kurniawan Rika Agustin Satyawan, Arief Suryadi Satyawan, Arief. S. selly Selly Sitohang, Daniel Pandapotan Sri Desy Siswanti Sutrisno, Renaldy Agung Utomo, P.A. Utomo, Prio Adjie Vini Rizqi, Vini Wulandari, Ike Yuni Yayat Rukayat