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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Paradigma JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Ilmiah Media Sisfo The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Bulletin of Computer Science Research Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Informatika dan Rekayasa Komputer PROCEEDING OF INTERNATIONAL CONFERENCE ON BUSINESS MANAGEMENT AND ACCOUNTING Bulletin of Informatics and Data Science Jurnal Informatika: Jurnal Pengembangan IT The Indonesian Journal of Computer Science Scientific Journal of Informatics Jurnal Pengabdian Masyarakat Unama Jurnal Lentera Ilmiah Pengabdian Masyarakat
Yovi Pratama
Universitas Dinamika Bangsa
Aerospace Engineering Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Eksperimen Layer Pooling menggunakan Standar Deviasi untuk Klasifikasi Dataset Citra Wajah dengan Metode CNN Pratama, Yovi; Rasywir, Errissya; Fachruddin, Fachruddin; Kisbianty, Desi; Irawan, Beni
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3604

Abstract

Deep Learning, especially the Convolutional Neural Network (CNN) has proven to be reliable in processing data from various programming language platforms by utilizing deep learning. In this study, we modified it by calculating the statistical variance. The modifications made are replacing calculations on the Pooling Layer which generally use two formulas, namely max pooling and average pooling. We use the standard deviation to change the reduced image intensity value. With the research experiments built, it is expected to be able to perform facial recognition as an indicator for testing modifications. The Layer Pooling experiment uses the Standard Deviation for Classifying Face Image Datasets with the CNN Method, including the type of dataset used is the Aberdeen dataset https://pics.stir.ac.uk/2D_face_sets.htm. From the results of the experiments conducted, it was found that the highest value was using the Elu activation function and the Adagrad optimizer worth 77.844% for max pooling and 79.844% for pooling with a standard deviation. The Cellu activation function and the RMSprop optimizer are 77.986% for max pooling and 75.986% for pooling with a standard deviation. The highest score with the Softplus activation function and the Sgd optimizer is 77.844% for max pooling usage and 76.344% for pooling with standard deviation. The Tanh activation function and the Adadelta optimizer are 87.844% for max pooling and 85.844% for pooling with a standard deviation. The Elu activation function and the Adam optimizer are 87.853% for the use of max pooling and 85.285% for pooling with a standard deviation. By using the Elu activation function and the Adamax optimizer, the value is 87.842% for max pooling and 86.242% for pooling with a standard deviation. The highest score is using the Elu activation function and the Nadam optimizer with a value of 87.845% for max pooling usage and 86.345% for using standard deviation calculations as pixel pooling. From all experiments it was stated that the use of pooling with the highest value technique or max pooling still gave a better value than using the standard deviation calculation with the best tuning results using the Elu activation function and Adam's Optimiser, which was 87.853%.
Reduksi False Positive Pada Klasifikasi Job Placement dengan Hybrid Random Forest dan Auto Encoder Pahlevi, M. Riza; Rasywir, Errissya; Pratama, Yovi; Istoningtyas, Marrylinteri; Fachruddin, Fachruddin; Yaasin, Muhammad
Building of Informatics, Technology and Science (BITS) Vol 5 No 4 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i4.4864

Abstract

The False Positive (FP) interpretation shows a negative prediction result and is a type 1 error answer with an incorrect positive prediction result. Based on this, we try to reduce type 1 errors to increase the accuracy value of the classification results. A low FP rate is critical for the use of Computer Aided Detection (CAD) systems. In this research proposal, to reduce FP, we use a Random Forest (RF) evaluation result design which will be reinterpreted by the Auto Encoder (AE) algorithm. The RF algorithm was chosen because it is a type of ensemble learning that can optimize accuracy in parallel. RF was chosen because it performs bagging on all Decision Tree (DT) outputs used. To suppress TP reduction more strongly, we use the Auto Encoder (AE) algorithm to reprocess the class bagging results from RF into input in the AE layer. AE uses reconstruction errors, which in this case is Job Placement classification. From the test results, it was found that combining the use of a random forest using C4.5 as a decision tree with an Autoencoder can increase accuracy in the Job Placement Classification task by a difference of 0.004652 better than without combining it with an autoencoder. Apart from that, in testing using a combination of RF and AE, fewer False Positive (FP) values ​​were produced, namely 11 items in the Cross Validation-5 (CV-5) Test, then 13 items in the Cross Validation-10 (CV-10) test and in testing split training data of 60%, the FP was only 12. This value is less than the false positives produced by testing without Autoencoder, namely 12 items on CV-5, 15 items on CV-10, and 13 on split training data
Decision Support System for Best Employee Selection on CV. Lintas Nusantara Using Profile Matching Method Manyu, Dimas Abi; Pratama, Yovi; Yanti, Elvi
International Conference on Business Management and Accounting Vol 2 No 1 (2023): Proceeding of International Conference on Business Management and Accounting (Nov
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/icobima.v2i1.3546

Abstract

CV. Lintas Nusantara Jambi is one of the companies that are located in the Jambi area that processing data selection best employee get problems occur like election process employees best the absence of computerized system and still not use a method of the support system decisions, so election employees best cannot be measured, and election process employees best is not transparent because they the evaluation process of employee performance only done by managers and unknown by employees. Hence, this study aims to give solution to problem that happens by offering decision support system of selection best employee using PHP programing language and DBMS MySQL. Writer expand the system with waterfall and methods used the system modeling unified language using use case diagram, activity diagram, class diagrams and flowchart diagram. The new system produce outputs that can data showing employees, data admin, data criteria, the sub criteria, the data employees and the results of selection best employee with profile matching methods who contributed to a company can improve performance and spirit of employees.
Public complaint tweet data feature analysis for sentiment classification Rasywir, Errissya; Pratama, Yovi; Irawan, Irawan; Istoningtyas, Marrylinteri
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7172

Abstract

The perception of the public regarding a government's performance significantly impacts a city's advancement. This research involved analyzing complaint tweets from Jambi City residents directed at the government to gauge sentiment. In the testing phase, 500 Twitter accounts were examined to categorize sentiment as positive, negative, or neutral. Training data was prepared by extracting tokens through feature selection techniques such as information gain (IG) and mutual information (MI). For testing, all tokens are entered as data in the input layer in the recurrent neural network (RNN). From the tests carried out, the average use of feature selection can achieve a good value compared to no feature selection. But more specifically the use of IG produces better accuracy compared to the use of MI. From the research conducted, Twitter data is classified using a RNN and several tests by adding feature selection to produce differences. The results are proven to improve classification performance. With a recall value of 92.243%, it shows the system's success rate in sentiment classification and a precision of 92% indicates a level of accuracy that is sufficient to support the government's sentiment assessment.
Analisis Data Mining Untuk Prediksi Kanker Payudara Menggunakan Algoritma Klasifikasi Sudewo, Raden Tio Putra; Pratama , Yovi; Yanti, Elvi
Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer) Vol 3 No 2 (2023): Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitekt
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakadata.v3i2.656

Abstract

Kanker payudara merupakan salah-satu kanker yang menyerang jaringan pada payudara yang mana lebih sering dialami oleh perempuan tetapi tidak menutup kemungkinan juga menyerang laki-laki (sangat jarang terjadi). Penerapan data mining dalam meneliti pasien kanker payudara adalah untuk menjadikan sebuah landasan dalam mengetahui akurasi dari model yang di bangun guna menentukan penderita kanker payudara dengan penggolongan “ganas” atau “jinak” dengan menggunakan naïve bayes dan C4.5. Pengujian dilakukan dengan beberapa eksperimen yaitu perhitungan split data 60%, 70%, dan 80 %. Pengujian data mengenai kanker payudara memiliki akurasi yang tinggi pada split data 70 % menggunakan algortima c4.5 dan memiliki accuracy yang lebih tinggi yaitu 99.4975 % dibandingkan dengan mode pengujian lainnya, sedangkan accuracy terendah adalah split data 80 % pada algortima naïve bayes yaitu 95.1648%. Pada perhitungan yang membandingkan algoritma C4.5 dan algoritma naïve bayes, dapat dikatakan bahwa algortima C4.5 sebagai algoritma yang efektif baik dari perhitungan ataupun hasil akhir yang mana pengujian tersebut dapat dijadikan suatu landasan terkait kanker payudara mengingat hasil akurasi dari algortima C4.5 menyentuh 99.4975 % sedangkan hasil dari algortima naïve bayes hanya menyentuh 95.8944 %.
Workshop Pembuatan Konten Media Sosial Untuk Publikasi Objek Budaya Dan Wisata Pada Desa Muaro Pahlevi, M.Riza; rasywir, errissya; Hussaein, Ahmad; Rosario B, Maria; Nurhadi, Nurhadi; Setiawan, Roby; Pratama, Yovi
Jurnal Pengabdian Masyarakat UNAMA Vol 3 No 1 (2024): JPMU Volume 3 Nomor 1 April 2024
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jpmu.2024.3.1.1614

Abstract

Abstrak Dalam era digital dan globalisasi, konten budaya dan wisata berperan penting dalam mempromosikan serta melestarikan warisan budaya suatu daerah. Desa-desa memiliki potensi besar dalam hal ini, namun seringkali belum tereksplorasi. Melibatkan generasi muda dalam penciptaan konten budaya dan wisata menjadi krusial. Perkembangan teknologi dan digitalisasi mengubah cara kita berinteraksi dan berkomunikasi. Desa-desa juga terpengaruh oleh perkembangan ini. Melalui program Pengabdian kepada Masyarakat berjudul "Mengajak Generasi Muda Berkontribusi dalam Menciptakan Konten Budaya dan Wisata", tujuan program ini adalah menginspirasi generasi muda desa dan pokdarwis (kelompok sadar wisata) agar terlibat aktif dalam pembuatan konten berfokus pada budaya dan keindahan wisata di sekitar mereka. Pengabdian kepada Masyarakat yang melibatkan generasi muda dan PokDarWis (Kelompok Sadar Wisata) dalam workshop pembuatan konten budaya dan wisata, seperti vlog, video dokumenter, dan cerita interaktif. Dengan melibatkan generasi muda, diharapkan akan tercipta konten yang lebih segar dan relevan pada Desa Muaro Pijoan. Kata kunci: Konten, Sosial, Media, Wisata, Teknologi. Abstract In the era of digital and globalization, cultural and tourism content plays an important role in promoting and preserving a region's cultural heritage. Villages have great potential in this regard, but it is often unexplored. Involving the younger generation in creating cultural and tourism content is crucial. Technological developments and digitalization are changing the way we interact and communicate. Villages are also affected by this development. Through the Community Service program entitled "Inviting the Young Generation to Contribute in Creating Cultural and Tourism Content", the aim of this program is to inspire the young generation of villages and pokdarwis (tourism awareness groups) to be actively involved in creating content focused on the culture and beauty of tourism around them. Community Service involving the younger generation and PokDarWis (Tourism Awareness Group) in workshops on creating cultural and tourism content, such as vlogs, documentary videos and interactive stories. By involving the younger generation, it is hoped that fresher and more relevant content will be created in Muaro Pijoan Village. Keywords: Content, Social, Media, Travel, Technology.
PEMBIMBINGAN INTENSIF MATERI ALGORITMA DAN PEMOGRAMAN DASAR TERHADAP PESERTA OLIMPIADE SAINS NASIONAL BIDANG INFORMATIKA TINGKAT KOTA PADA SMA NEGERI 2 KOTA JAMBI Rosario, Maria; Arief Hermawan Sutoyo, Mochammad; Siswanto, Agus; Pratama, Yovi; Feranika, Ayu; Emelia, Shinta
Jurnal Pengabdian Masyarakat UNAMA Vol 3 No 2 (2024): JPMU Volume 3 Nomor 2 Oktober 2024
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jpmu.2024.3.2.1821

Abstract

Intensive guidance on algorithms and basic programming involves OSN participants from SMA Negeri 2 Jambi City, who have passed the school selection. In the Guidance, they will be given in-depth guidance on algorithm concepts, data structures and basic programming using C++. The importance of this coaching lies in preparing OSN participants to be able to face national level exams with confidence. By increasing their understanding and mastery of basic algorithms and programming, it is hoped that participants can produce innovative and effective solutions in dealing with various problems tested in OSN Informatics. This coaching also creates a learning environment that supports the growth of participants as individuals who are ready to compete at the national level in the field of Informatics.
Analisis Dan Penerapan Algoritma Naȉve Bayes Untuk Klasifikasi Kelayakan Penerimaan Beasiswa PIP (Studi Kasus : SMPN 7 Kota Jambi) Dimas Yudha Prawira; Yovi Pratama; Yanti, Elvi
Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) Vol 4 No 2 (2024): JAKAKOM Vol 4 No 2 September 2024
Publisher : LPPM Universitas Dinamika Bangsa

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

Abstract

Scholarships are financial aid provided to the community with the aim of supporting education. Scholarship programs were established to help students overcome financial problems in completing their education. Scholarships are awarded selectively according to individual needs. To determine the accuracy of the predicted results of eligibility for the Indonesia Pintar Scholarship Program (PIP), classification techniques can be used as part of data mining. Testing is done by using all attributes and the best attributes on 3 options test, among others Use Training Set, 5 Fold Cross Validation, 10 Fold Cross Validation. Data on the acceptance of PIP scholarships has a high accuracy in the options test Use Training Set (best attribute) which is 93.18% compared to other tests. As for the lowest accuracy is 5 Fold Cross Validation 10% (2021 – 2022) which obtained an accuracy of 81.82%. Naïve Bayes algorithm can be said to be one of the effective algorithms both from the calculation and the final result where the test can be used as a foundation related to scholarship acceptance.Keywords: Data Mining, Classification, Naïve Bayes Algorithm, Rapid Miner, PIP scholarship recipients
Deteksi Objek Boneka Korban pada Kontes Robot SAR Indonesia Menggunakan ESP32-cam Taupiq, Arahmad; Pratama, Yovi; Bustami, M Irwan
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5979

Abstract

The 2024 Indonesian SAR Robot Contest demands the ability of robots to differentiate between dummy dolls and victim dolls in emergency situations. This SAR robot has the main goal of rescuing victims and bringing them to a safe zone, so the author explores the implementation of object detection on SAR robots using ESP32-cam to detect victim dolls. The authors used the Edge Impulse platform, a TinyML platform, to train an object detection model using the Faster Objects, More Objects (FOMO) architecture. This model is optimized to run efficiently on resource-limited devices such as the ESP32-cam microcontroller. Training data was obtained by taking pictures of dummy dolls and victim dolls in various angles, lighting conditions and backgrounds using a camera from the ESP32-cam. The confusion matrix results from the model training process showed that the F1 score reached 100% and when testing the model, the object detection model was able to detect the victim doll with adequate accuracy, even though there were challenges such as variations in position and environmental conditions so the researchers used additional algorithms to increase detection accuracy. . The use of FOMO allows faster object detection and is able to detect more objects in one frame. This implementation shows great potential in the development of more efficient and autonomous SAR robots for rescue missions. These findings contribute to improving robotic technology, one of which is in SAR operations and provide a basis for further research in the application of object detection.
Kontrol Navigasi Robot Hexapod berbasis Inverse Kinematic dan Body Kinematic untuk Stabilitas Optimal di Medan Ekstrem Pratama, Yovi; Saputra, Chindra; Toscany, Afrizal Nehemia; Bustami, M Irwan; Taupiq, Arahmad
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6007

Abstract

This study discusses the application of Inverse Kinematics (IK), Body Kinematics (BK), and Bézier Curves in a hexapod robot to efficiently control leg movements in a three-dimensional space. IK is used to calculate joint angles based on the desired target position, while BK enables adjustments to the robot's body posture to maintain stability during movement. Simulations demonstrate that these two approaches can produce accurate and controlled movements. Additionally, Bézier Curves are applied to the foot trajectory, significantly enhancing the smoothness of movements and the robot's stability during transitions from one step to the next. Testing the hexapod robot over a distance of 2.10 meters showed a 70% success rate with an average error of 4.2 cm. Further testing of the robot's stability on an inclined X-axis revealed that the robot could adapt to inclines up to 35 degrees; however, at inclines exceeding 35 degrees, the robot was unable to maintain balance. Based on the results, it can be concluded that the combination of IK, BK, and Bézier Curves effectively supports the hexapod robot's movement with a step accuracy of 70% and high stability when adapting to inclines up to 35 degrees. Improving stability in more extreme terrains and enhancing performance in more diverse environments are the primary focuses for maximizing the hexapod robot's capabilities.
Co-Authors Abdul Haris Abdul Harris Achpal Haddid Adelia Putri, Ananda Afrizal Nehemia Toscany Agus Siswanto Akbar Ramadhan Akwan Sunoto Alvito Widianto Amroni, Amroni Angelica, Felicia Anggraini, Dila Riski Anggy Utama Putri Annisa putri Anton Prayitno Arahmad Taupiq asih asmarani Bayu saputra Beni Irawan Borroek, Maria Rosario Bustami, M Irwan Cahyana Putra Pratama Candra Adi Rahmat Carenina, Babel Tio Chindra Saputra Defrin Azrian Desi Kisbianty, Desi Despita Meisak Dimas Pratama Dimas Yudha Prawira Dinata, Despan elvi yanti Emelia, Shinta Enjelina, Mia Errissya Rasywir Evan Albert Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin, Fachruddin farchan akbar Feranika, Ayu Fingki Lamhot Pasaribu fiqri ansyah Hartiwi, Yessi Hendrawan Hendrawan Hendrawan Hendrawan Hendrawan Hendrawan Hilda Permatasari Hussaein, Ahmad Ilham Adriansyah ilham permana Imelda Yose Indana Arum , Refi Irawan Irawan Irawan Irawan Irawan, Beni Istoningtyas, Marrylinteri Janu Hadi Susilo Jopi Mariyanto Julia Triani khalil gibran ahmad Kholil Ikhsan Luthfi Rifky M Fikrul Hakimi M Reihan Al Fajri M.Rizky Wijaya Manyu, Dimas Abi Maria Rosario Borroek Marrylinteri Istoningtyas Marrylinteri Istoningtyas Marrylinteri Istoningtyas Marshal` Koko Anand masgo Maulana Qaedi Aufar Mayang Ruza Muhammad Afif Dzaky Khairullah Muhammad Diemas Mahendra Muhammad Irwan Bustami Muhammad Ismail Muhammad Riza Pahlevi MUHAMMAD SURYA Muhammad Wahyu Prayogi Muhammad Zulfi Tisna Tama Mumtaz Ilham S Mumtaz Ilham Syafatullah NAIBAHO, RONALD Najmul Laila Naldi Irfan Nanda Ghina Nia Azzahra Nur Aini Nurhadi Nurhadi Pahlevi, M. Riza Pahlevi, M.Riza Pareza Alam Jusia Pareza Alam Jusia, Pareza Alam Ramadhan Saputra, Tri Ramadhani, Utari Reza Pahlevi Rezky Pramudia, Muhammad Riki Bayu Andhika Rio Ferdinand ROBY SETIAWAN Rohaini, Eni Rosario B, Maria Rosario, Maria Rudolf Sinaga Sandi Pramadi Santoso Saparudin, Saparudin Sariyani SIKA, XAVERIUS Steven Ie Sudewo, Raden Tio Putra Sutoyo, Mochammad Arief Hermawan Suyanti taupiq, Arahmad Toscany, Afrizal Verna Anatasya, Rara Verwin Juniansyah virginia casanova andiko andiko Warcita Warcita WILLY RIYADI Xaverius Sika Yaasin, Muhammad Yanti, Elvi Yessi Hartiwi Yessi Hartiwi Yoga Rizki Yuga Pramudya Zahlan Nugraha Zulia, Restutik