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Hubungan Penggunaan Helm dengan Beratnya Cedera Kepala Akibat Kecelakaan Lalu Lintas Darat di RSUD Ulin Bulan Mei - Juli 2013 Lahdimawan, Inas Tsurayya Fadilla; Suhendar, Agus; Wasilah, Siti
Berkala Kedokteran Vol 10, No 2 (2014): September 2014
Publisher : Fakultas Kedokteran Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jbk.v10i12.958

ABSTRACT: Head injury is one of the leading cause of morbidity and mortality in the world and the seventh cause of mortality in Indonesia . Head injury is one of the most top 10 diseases in Ulin General Hospital. The increasing number of motorcycle leading head injury to occur more often, considering that road traffic accidents are the most frequent cause of head injury. Lack of public awareness in helmet use leads it to be the primary factor of head injury. The objective of the research is to identify the relationship between helmet use and head injury severity caused by road traffic accidents. The method of the research is descriptive analytical with cross-sectional approach and it took place at Ulin General Hospital from May â July 2013. Total samples of 73 people taken based on inclusion criteria. The most frequently age group was between the age 15-24 (41,1%). Males frequently injured than female with male to female ratio was 1,9:1. Most of them were non-helmeted motorcyclist (53,4%). The most frequent head injury severity was mild head injury (64,4%). The data were statistically analyzed by Chi-square test showed p = 0.041 (Î± = 0.05). Based on the research there is a significant relationship between helmet usage and the severity of head injury caused by road traffic accidents.Â Keywords: head injury, helmet, road traffic accidentsÂ ABSTRAK: Cedera kepala merupakan salah satu penyebab kesakitan dan kematian di dunia dan ke-7 di Indonesia. Cedera kepala termasuk 10 penyakit terbesar di RSUD Ulin Banjarmasin. Meningkatnya angka kendaraan bermotor menyebabkan cedera kepala semakin sering terjadi, mengingat salah satu penyebab tersering cedera kepala adalah kecelakaan lalu lintas. Kurangnya kesadaran masyarakat dalam menggunakan helm menjadi faktor utama terjadinya cedera kepala. Penelitian bertujuan untuk mengetahui apakah terdapat hubungan antara penggunaan helm dengan beratnya cedera kepala akibat kecelakaan lalu lintas darat. Penelitian ini merupakan penelitian deskriptif analitik dengan pendekatan cross-sectional bertempat di RSUD Ulin bulan Mei â Juli 2013. Jumlah sampel sebanyak 73 orangÂ diambil berdasarkan kriteria inklusi. Kelompok usia terbanyak yaitu 15-24 tahun (41,1%). Jenis kelamin laki-laki banyak mengalami cedera kepala daripada perempuan dengan perbandingan 1,9:1. Status penggunaan helm terbanyak adalah tidak menggunakan helm (53,4%). Beratnya cedera kepala terbanyak adalah cedera kepala ringan (64,4%). Data dianalisis statistik dengan uji Chi-square menunjukkan p = 0,041 (Î± = 0,05). Berdasarkan penelitian yang dilakukan dapat diambil kesimpulan bahwa terdapat hubungan bermakna antara penggunaan helm dengan beratnya cedera kepala akibat kecelakaan lalu lintas darat.Â Kata-kata kunci: cedera kepala, helm, kecelakaan lalu lintas darat

HUBUNGAN KOORDINASI MATA DAN KAKI DAN KELENTUKAN OTOT PUNGGUNG TERHADAP KEMAMPUAN SMASH PADA ATLIT SEPAKTAKRAW PPAT CLUB RUMBAI Suhendar, Agus; Zainur, Zainur; Juita, Ardiah
Jurnal Online Mahasiswa (JOM) Bidang Keguruan dan Ilmu Pendidikan Vol 7, No 2 (2020): EDISI 2 JULI-DESEMBER 2020
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Keguruan dan Ilmu Pendidikan

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

Abstract: Based on researchers' observations in the field, it can be obtained from the trainer that the current PPAT Club Rumbai athlete sepaktakraw athletes do not yet show a maximum smash. A smasher often fails to make a hard and sharp smash, besides that the smash is often inaccurate. It is seen that so many balls don't die because they can be dammed by the opponent, the ball hits the net and even the ball comes out of the field. The population is the whole subject of the study. "The population in this study were all sepaktakraw PPAT Club Rumbai athletes, amounting to 9 people. Because the total population is less than 100 in the PPAT Club Rumbai sepaktakraw team, the sampling technique used is the population sampling technique or saturated sampling (total sampling) so that the sample is 9 people. The instruments in this research are eye and foot coordination, Bridge-Up and kedeng smash ability. Based on the results of research that the author has described in the previous chapter, the conclusion can be drawn is the results obtained, then; There was a significant relationship between eye and foot coordination with the smash ability of the PPAT Club Rumbai sepaktakraw team by rcount0.832> rtable 0.707. There is a significant relationship between the flexibility of the back muscles with the ability to smash the PPAT Club Rumbai sepaktakraw team of rcount 0.713> rtable 0.707. There was a significant relationship between eye and foot coordination and back muscle flexibility and the ability to smash on the PPAT Club Rumbai sepaktakraw team by rcount0.885> rtable 0.707.Key Words: Eye and Foot Coordination, Back Muscle Determination, Smash Ability

HUBUNGAN KOORDINASI MATA DAN KAKI DAN KELENTUKAN OTOT PUNGGUNG TERHADAP KEMAMPUAN SMASH PADA ATLIT SEPAKTAKRAW PPAT CLUB RUMBAI Suhendar, Agus; Zainur, Zainur; Juita, Ardiah
Jurnal Online Mahasiswa (JOM) Bidang Keguruan dan Ilmu Pendidikan Vol 7, No 2 (2020): EDISI 2 JULI-DESEMBER 2020
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Keguruan dan Ilmu Pendidikan

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

Abstract: Based on researchers' observations in the field, it can be obtained from the trainer that the current PPAT Club Rumbai athlete sepaktakraw athletes do not yet show a maximum smash. A smasher often fails to make a hard and sharp smash, besides that the smash is often inaccurate. It is seen that so many balls don't die because they can be dammed by the opponent, the ball hits the net and even the ball comes out of the field. The population is the whole subject of the study. "The population in this study were all sepaktakraw PPAT Club Rumbai athletes, amounting to 9 people. Because the total population is less than 100 in the PPAT Club Rumbai sepaktakraw team, the sampling technique used is the population sampling technique or saturated sampling (total sampling) so that the sample is 9 people. The instruments in this research are eye and foot coordination, Bridge-Up and kedeng smash ability. Based on the results of research that the author has described in the previous chapter, the conclusion can be drawn is the results obtained, then; There was a significant relationship between eye and foot coordination with the smash ability of the PPAT Club Rumbai sepaktakraw team by rcount0.832> rtable 0.707. There is a significant relationship between the flexibility of the back muscles with the ability to smash the PPAT Club Rumbai sepaktakraw team of rcount 0.713> rtable 0.707. There was a significant relationship between eye and foot coordination and back muscle flexibility and the ability to smash on the PPAT Club Rumbai sepaktakraw team by rcount0.885> rtable 0.707.Key Words: Eye and Foot Coordination, Back Muscle Determination, Smash Ability

Design and Development of an Android-Based Point of Sale Application: A Case Study of Warung Dapur Barokah, Pangkalpinang Hanif, Ahmad; Suhendar, Agus; Sejati, Rr. Hajar Puji
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2325

Warung Dapur Barokah is a food stall in Pangkalpinang City and was founded in 2022. This application was designed to overcome obstacles that generally arise in manual transaction processes, which are often slow, inefficient, and difficult to manage accurately sales data. This application was developed using Android Studio and adopted the Kotlin programming language. Apart from that, the database section uses Firebase. I am using Firebase because Firebase has a real-time databaseRealtime that can update data in the database in realtime. This will make the transaction data storage process synchronized, fast, and optimal. The hope is that the results of implementing this application will include increased efficiency and speed in the transaction process and potentially improve the profitability of Warung Dapur Barokah's operations. This innovation is hoped to positively contribute to advancing the operational performance of this food stall in the current digital era, as well as creating effective solutions to increase the competitiveness and sustainability of local businesses in the culinary sector.

Improving Firebase BaaS Service Security in Counseling Chat Applications: AES-256 and CBC Approach for End-to-End Encryption Nurhandhi, Mogar; Suhendar, Agus
JISA(Jurnal Informatika dan Sains) Vol 6, No 2 (2023): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v6i2.1783

The activities of using the internet and exchanging information and sending messages have used a lot of internet media, one of which is chat message media, but over time data and information security problems in chat messages that are often encountered are active and passive wiretapping. In this research, the author wants to create a counseling chat message security application using the AES (Advanced Encryption Standard) algorithm cryptographic method combined with the CBC (Cipher Block Chaining) technique which is an advanced development of the ECB (Electronic Code Book) technique. AES basically uses a block cipher with a length of 128 bits as the default operation, and the key length size varies from 128, 192 and 256 bits. so AES uses a 4x4 matrix equation with each section having a size of 1 byte. From these problems, research will be conducted to develop an application to accommodate the counseling process using a chat application that has the main focus of securing messages with image types and stored in the Firebase database service (Backend as a Service). As well as using the End-to-End service principle so that users do not need to do the encryption or decryption process directly because the process has been carried out by the system, this will also provide more security aspects in terms of confidentiality of key data and initialization vectors. So that the process of exchanging information using the media chat counseling application is secured and avoids tapping by irresponsible parties.

IMPLEMENTASI ALGORTIMA CONVOLUTIONAL NEURAL NETWORK UNTUK DETEKSI PENYAKIT DAUN KENTANG MENGGUNAKAN CITRA DIGITAL Septian, Aldianto Dickyu; Suhendar, Agus
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.4880

Potato plants are an important food crop but are susceptible to leaf diseases such as early blight and late blight, which can significantly reduce crop yields. In this study, we developed and compared several convolutional neural network (CNN) models to classify potato leaf diseases based on visual images. The data used consisted of potato leaf images in three classes: healthy, early blight, and late blight. The image dataset was processed through augmentation and normalization to improve model accuracy. Three CNN architectures, namely MobileNet-V2, VGG16, and ConvNeXtBase, were implemented and tested with different batch sizes. Based on the results, the VGG16 architecture with a batch size of 32 provided the best performance with a classification accuracy of 95.93%, followed by MobileNet-V2 with an accuracy of 94.15%. Therefore, CNN models, particularly VGG16, proved effective in identifying potato leaf diseases, contributing to more efficient crop management and reducing yield losses.

IMPLEMENTATION OF MSME CREDIT LOAN DETERMINATION USING MACHINE LEARNING TECHNOLOGY WITH KNN (K-NEAREST NEIGHBORS) ALGORITHM Nawawi, Muchamad Taufik; Suhendar, Agus
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 3 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i3.9064

This research aims to develop a loan eligibility prediction model for Micro, Small, and Medium Enterprises (MSMEs) using the K-Nearest Neighbors (KNN) algorithm. The dataset utilized includes variables such as the length of business operation, number of workers, assets, and net turnover of MSMEs. The data is split into training and test sets with a 70:30 ratio. The KNN model is trained using the training data to classify loan eligibility based on a specified k value. The model predictions include whether a loan is accepted and the probability associated with each decision. The results indicate that the KNN model achieved an accuracy rate of 83.939% in predicting loan eligibility. Based on the predictions, 929 MSMEs were deemed eligible to receive loans according to the KNN model recommendations, while 170 MSMEs were classified as ineligible. These findings contribute significantly to the development of decision support systems in the banking and finance sectors, particularly in evaluating MSME loan eligibility.

IMPLEMENTASI ALGORITMA LONG SHORT-TERM MEMORY (LSTM) UNTUK MEMPREDIKSI HARGA BERAS DI JAWA TENGAH BERDASARKAN CUACA Ashari, Yusuf; Suhendar, Agus
Djtechno: Jurnal Teknologi Informasi Vol 5, No 3 (2024): Desember
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v5i3.5136

Harga beras yang tidak stabil seringkali menjadi masalah bagi pemerintah dalam menjaga ketahanan pangan dan bagi petani untuk mendapatkan pendapatan yang stabil. Tujuan Penelitian untuk mengembangkan sistem prediksi harga beras di Jawa Tengah menggunakan metode Long Short-Term Memory (LSTM). LSTM dipilih karena kemampuannya dalam menangkap pola non-linear dan dependensi jangka Panjang yang terdapat dalam data time series seperti harga beras. Sistem dibangun dengan menggunakan data harga beras harian yang didapatkan dari website Pusat Informasi Harga Pangan Strategis Nasional (PIHPS Nasional) dan data cuaca harian yang diperoleh dari website BMKG di Jawa Tengah dari tahun 2017 – 2024. Arsitektur model LSTM yang digunakan terdiri dari tiga lapisan LSTM dengan dropout disetiap lapisannya dan satu lapisan Dense. Evaluasi performa model dilakukan dengan menggunakan tiga metrik evaluasi yaitu MAE, RMSE, dan MAPE. Hasil dari penelitian menunjukkan bahwa model prediksi harga beras menggunakan LSTM memiliki performa yang cukup baik berdasarkan dengan nilai metriks evaluasi, yaitu MAE sebesar 0.141, MAPE sebesar 1.256%, dan RMSE sebesar 0.205.

Penerapan Metode Convolutional Neural Network pada Sistem Klasifikasi Penyakit Tanaman Apel berdasarkan Citra Daun Pamungkas, Nicholas Bagus; Suhendar, Agus
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 2 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i2.27958

Apple leaf diseases can cause significant crop failure and impact the economy of farmers and the agricultural industry. With the increasing demand for quality apples, it is important to develop effective and efficient solutions to detect apple plant diseases early. This research aims to develop an automated system that can identify diseases in apple plants based on leaf images using the Convolutional Neural Network (CNN) model. This model was developed with the ResNet50V2 architecture to classify four leaf conditions: three types of common diseases and one healthy condition. This research applies the CNN model for leaf image processing and the Waterfall system development method. The stages start from needs analysis by collecting data to be processed by the cnn model, interface design of the classification system, program code implementation, and functionality testing using black-box testing. CNN model development includes the stages of collecting datasets sourced from Malang apple plantations as many as 150 images and Kaggle public datasets totalling 3,071 images, then image preprocessing, model development and training. Our research results produced an apple plant disease classification system by implementing the CNN model. Based on the results of testing the system and the model used, it shows that the CNN model applied in the system achieves a classification accuracy of 99.01%, and the functionality of the system built runs well.

The Role of Basal Cistern as Prognostic Factor in Head Injury Cases Fath, Tri Putra Nuur; Suhendar, Agus; Kania, Nia; Wibowo, Agung Ary; Poerwosusanta, Hery; Abidin, Zainal; Huldani, Huldani
Jurnal Neuroanestesi Indonesia Vol 14, No 1 (2025)
Publisher : https://snacc.org/wp-content/uploads/2019/fall/Intl-news3.html

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24244/jni.v14i1.596

Background and Objective: Head injury is a medical condition affecting various individuals around the world and is characterized by high mortality and morbidity rates. Several studies have shown that accurate management and appropriate interventions are required to achieve favorable outcomes. In this context, head CT scan has been reported to be the gold standard in diagnostic imaging for patients with head injury. In addition, head CT scan can be used to evaluate basal cistern, which is an area around the brain with a significant role in consciousness due to its close association with the brainstem. Several factors are known to influence prognosis of head injury treatment, including age, gender, severity of head injury, type of bleeding lesion, and the condition of basal cistern, which play a crucial role in the outcome of patients care. Therefore, this study aims to determine the role of basal cistern as a predictor of prognosis in cases of head injury. Subject and Method: The study procedures were carried out using the prospective observational method, and the sample population comprised 67 head injury patients at Ulin Regional General Hospital (RSUD) from February to April in 2024. Based on the inclusion and exclusion criteria, a total of 60 patients were selected as participants, and their primary data were collected. Subsequently, each variable's data was analyzed using SPSS with Chi-square and Spearman correlation tests. Results: Significant differences were observed between various variables, including 1) the type of bleeding lesion and the condition of basal cistern (p-value: 0.004), 2) action (surgery and non-surgery) and prognosis (p-value: 0.017), and 3) prognosis and the condition of basal cistern (p-value: 0.0001). Conclusion: Based on the results, basal cistern could be used as a predictor of prognosis in patients with head injury. In addition, the severity of head injury was closely related to the condition of basal cistern. The more severe head injury, the worse prognosis for patients. The results also showed that the type of bleeding lesion affected the condition of basal cistern

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