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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Kursor KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) INOVTEK Polbeng - Seri Informatika Infoman's: Jurnal Ilmu-Ilmu Manajeman dan Informatika Jurnal Mantik Jurnal Informatika dan Rekayasa Elektronik Indonesian Journal of Electrical Engineering and Computer Science Jurnal Rekayasa elektrika
Achmad Basuki
Politeknik Elektronika Negeri Surabaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media

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Mobile sensing in Aedes aegypti larva detection with biological feature extraction Dia Bitari Mei Yuana; Wahjoe Tjatur Sesulihatien; Achmad Basuki; Tri Harsono; Akhmad Alimudin; Etik Ainun Rohmah
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (656.868 KB) | DOI: 10.11591/eei.v9i4.1993

Abstract

According to WHO, Dengue fever is the most critical and most rapidly mosquito-borne disease in the world over 50 years. Currently, the presence and detection of Aedes aegypti larvae (dengue-mosquitoes vector’s) are only quantified by human perception. In large-scale data, we need to automate the process of larvae detection and classification as much as possible. This paper introduces the new method to automate Aedes larvae. We use Culex larva for comparison. This method consists of data acquisition of recorded motion video, spatial movement patterns, and image statistical classification. The results show a significant difference between the biological movements of Aedes aegypti and Culex under the same environmental conditions. In 50 videos consisting of 25 Aedes larvae videos and 25 Culex larvae videos, the accuracy was 84%.
DETEKSI KUALITAS BERAS MENGGUNAKAN SEGMENTASI CITRA BERDASARKAN PECAHAN BULIR DAN SEBARAN WARNA Eko Supriyadi; Achmad Basuki; Riyanto Sigit
Jurnal Informatika dan Rekayasa Elektronik Vol. 3 No. 1 (2020): JIRE April 2020
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v3i1.210

Abstract

Ada banyak kasus penipuan dalam pemalsuan beras dengan mencampur beras berkualitas baik dengan beras berkualitas rendah untuk kenaikan harga. Untuk melindungi masyarakat dari pemalsuan, kami melakukan penelitian untuk mendeteksi kualitas beras yang nantinya dapat membantu masyarakat untuk dapat membedakan kualitas baik dan buruk. Penelitian ini menyajikan sistem pemrosesan citra beras berbiaya rendah untuk menilai kualitas beras. Banyak faktor yang mempengaruhi kualitas beras seperti fragmen biji-bijian, warna yang tidak seragam, bau dan faktor lainnya. Penelitian ini menggunakan prosentase butiran beras pecah dan keseragaman warna untuk menentukan kualitas beras. Kami mengusulkan fitur tekstur dengan segmentasi Otsu untuk menentukan jumlah butiran pecah dan distribusi warna untuk menentukan seragam warna. Hasil klasifikasi menggunakan validasi K Folddengan k=10 pada data asli menunjukkan hasil K-Nearest Neigbour memiliki akurasi 99,87%.
PERMODELAN VISUAL TINGKAT KETAKUTAN PADA SIMULASI EVAKUASI KEBAKARAN 3D MENGGUNAKAN SELF ASSASSEMENT MANIKIN Iqbal Sabilirrasyad; Achmad Basuki; Tri Harsono
Jurnal Informatika dan Rekayasa Elektronik Vol. 3 No. 1 (2020): JIRE April 2020
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v3i1.217

Abstract

Simulasi kebakaran digunakan untuk memberikan edukasi tentang apa yang harus dilakukan saat berhadapan dengan api atau digunakan untuk meningkatkan kesadaran dalam bencana kebakaran. Dengan majunya teknologi kita tidak lagi harus mempersiapkan segala keperluan yang berbahaya dalam membangun simulasi kebakaran yang ada. Melainkan dengan teknologi VR atau 3D kita mampu memberikan visual serta suasana seakan berada dalam kebakaran yang sedang terjadi. Namun untuk membangun VR serta 3D yang mampu memberikan ilusi yang sangat kuat diperlukan rangsangan yang kuat pula. Api merupakan salah satu media yang mampu memberikan rangsangan tersebut. Namun masalah yang dihadapi ialah api yang sperti apa yang mampu memberikan rangsangan emosi yang kuat. Dalam penelitian ini kita akan mencari tahu model visual api seperti apa yang mampu memberikan rangsangan emosi yang kuat. Dengan membangun simulasi kebakaran yang berdasar pada hasil dari kuisioner self assessment manikin yang berfokus pada tema kebakaran, player akan menilai kembali dengan menggunakan sistem yang sama. self assessment manikin merupakan sistem penilaian emosi dari gambar yang ditampilkan. Simulasi yang dibangun mampu membangun rasa takut user, pada kriteria kurang menakutkan. Dapat dikatakan simulasi serta dataset gambar yang bertemakan api memiliki potensi sebagai salah satu cara meningkatkan rangsangan emosi manusia.Namun potensi yang dimiliki dataset maupun simulasi yang dibangun masih membutuhkan beberapa parameter tambahan yang mampu menyesuaikan perbedaan pengalaman pada saat berhadapan dengan api.
THE IMPLEMENTATION OF HEART RATE SENSOR AND MOTION SENSORS BASED ON INTERNET OF THINGS FOR ATLETE PERFORMANCE MONITORING Sritrusta Sukaridhoto; Muhammad Aksa Hidayat; Achmad Basuki; Riyadh Arridha; Andi Roy; Titing Magfirah; Agus Prasetyo; Udin Harun Al Rasyid
Jurnal Ilmiah Kursor Vol 10 No 1 (2019)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v10i1.208

Abstract

Indonesian achievements in the ASEAN Games continued to decline in achievement starting in 1962 with the acquisition of 51 medals and up to 2014 with the acquisition of 20 medals. The decline in achievement was due to the lack of athletic resources due to the absence of media that could record athletes' abilities in the field. Can record the athlete's performance before running, running and after running using the Heart Rate sensor and Motion Capture sensor. The results of the sensor recording will be stored in the database. This system applies the Internet of Things (IoT) concept, using raspberry pi, Arduino microcontroller, T34 polar heart rate sensor to capture and send heartbeat to receivers, gyro-based motion-capture sensors that named wear notch where this sensor serves to capture the movement of athletes, sensors communicate with the system using 4G connectivity, use MQTT as edge computing which acts as a communication medium from sensors to databases, Maria DB and influx DB as accumulation which plays a role in storing heart rate and athlete's movements that have been recorded by sensors, athlete performance monitoring platform with a heart rate sensor and athlete's motion capture is a web-based application that collaborates all processes from the sensor to the system. Sensor heart rate recording results are categorized good because the error margin is only 0.4%. Wearnotch sensor data can be stored in the database, and athletic data can be recorded before sports, while sports, and after sports in real-time
HAND GESTURE RECOGNITION FOR INDONESIAN SIGN LANGUAGE INTERPRETER SYSTEM WITH MYO ARMBAND USING SUPPORT VECTOR MACHINE Aditiya Anwar; Achmad Basuki; Riyanto Sigit
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 7, No 2 (2020)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v7i2.320

Abstract

Hand gestures are the communication ways for the deaf people and the other. Each hand gesture has a different meaning.  In order to better communicate, we need an automatic translator who can recognize hand movements as a word or sentence in communicating with deaf people. This paper proposes a system to recognize hand gestures based on Indonesian Sign Language Standard. This system uses Myo Armband as hand gesture sensors. Myo Armband has 21 sensors to express the hand gesture data. Recognition process uses a Support Vector Machine (SVM) to classify the hand gesture based on the dataset of Indonesian Sign Language Standard. SVM yields the accuracy of 86.59% to recognize hand gestures as sign language.Keywords: Hand Gesture Recognition, Feature Extraction, Indonesian Sign Language, Myo Armband, Moment Invariant
3D Virtual Catalogue Of PENS Campus Using Augmented Reality Kholid Fathoni; Achmad Basuki; Octario Rezkavianto
Infoman's : Jurnal Ilmu-ilmu Manajemen dan Informatika Vol. 14 No. 1 (2020): Infoman's
Publisher : STMIK Sumedang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33481/infomans.v14i1.133

Abstract

PENS is a vocational education campus that is actively promoting the community to capture the interests of prospective students to register as students. This requires promotion of media innovation that can attract public interest. Multimedia technology, especially augmented reality can be used as an attractive alternative media for PENS to carry out promotions. This study aims to develop promotional media in the form of an augmented reality technology-based virtual catalog to introduce various study programs available in PENS. Catalogs that are generally in the form of physical media are converted into markers that can bring up 3D objects and videos that explain the contents to the user so that the user does not need to read because there is already an audio visual explanatory facility. The trial results show that the PENS virtual catalog can function well in viewing AR mascot, AR video and information.
Klasterisasi Kualitas Beras Berdasarkan Citra Pecahan Bulir Dan Sebaran Warna Eko Supriyadi; Achmad Basuki; Riyanto Sigit
Jurnal Inovtek Polbeng Seri Informatika Vol 6, No 1 (2021)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v6i1.1657

Abstract

Intisari – Berassebagai bahan pokok makanan masyarakat Indonesia , karena di dalam beras terdapat kandungan karbohidrat kompleks, serta dapat memberikan berbagai zat gizi lain yang penting bagi tubuh. Masih banyak masyarakat yang berasumsi jika beras dalam keadaan bersih, tak berbau, dan memiliki harga lebih mahal, beras tersebut berkualitas baik, padahal belum tentu beras yang dimaksud tersebut mempunyai kualitas baik. Untuk itu dalam melakukan penelitian mendeteksi kualitas beras yang nantinya dapat membantu masyarakat untuk dapat membedakan kualitas baik dan buruk. Banyak faktor yang mempengaruhi kualitas beras seperti fragmen biji- bijian, warna yang tidak seragam, bau dan faktor lainnya. Penelitian ini menggunakan persentase buliran beras pecah dan keseragaman warna untuk menentukan kualitas beras. Penelitian ini menggunakan parameter buliran pecah dan distribusi warna yang selanjutnya  diproses klasterisasi dengan metode K-Means di mana nilai klaster dijadikan sebagai nilai class untuk melabeli jenis beras sesuai mutu dari medium 1,2, dan 3. Selanjutnya data yang terlabel klaster dilakukan proses klasifikasi untuk mendapatkan akurasi yang terbaik, dan metode klasifikasi yang terbaik adalah neural network sebesar 99,85%.Kata kunci – kualitas beras, citra beras, K-Mean, Neural Network.
Implementation of Yin Algorithm to Detect Human Voice Emotions According to Gender: Implementation of Yin Algorithm to Detect Human Voice Emotions According to Gender Fikri Aulia; Achmad Basuki; Bima Sena Bayu Dewantara
Jurnal Mantik Vol. 4 No. 1 (2020): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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

Abstract

Computer technology and artificial intelligence experience rapid development every year, one of which is in media speech recognition. Speech recognition is a virtual digital data assistant that exists in software applications, and is used as a tool to help human needs such as communication, but is often misused by users. This study conducted a voice recording to get the difference in the sound of each human gender data. The study uses the Yin algorithm to extract data, then the sound pitching process is performed using the histogram pitch feature of the standard deviation and the mean. From this study, it was found that the pitch of men is different from women. The shape of the pitch histogram contours is similar between men and women but the female pitch histogram shifts to a higher frequency than men. This pitch shift in women occurs in all expressions.
Optimization of Virtual Reality-Based Flood Simulation by Manipulating Particle System David Fahmi Abdillah; Achmad Basuki; Tri Harsono
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

VR (Virtual reality) is a technology that is gaining in popularity and many fields have used it in the applications they have developed. VR is the best tool to use as a learning medium and simulations that previously could not be done due to a lack of qualified technology, such as natural disaster simulations where users can feel like one of the victims who are affected by natural disasters and can feel it directly through simulations. the. However, this technology can also have side effects when using it, such as discomfort, dizziness to nausea. This is commonly known as cybersickness. To reduce the possibility of cybersickness, it is necessary to optimize the application by keeping the frame rate at least more than 60-90 fps. Particles are one of the systems that can affect the performance frame rate if not optimized by manipulating their emission for each system. This paper will explain how to optimize VR applications and analyze experiments involving FPS optimization in VR applications.
Implementation of Elo Rating System and Player Clustering for Competitive Matchmaking in Trivia Education Game Muhammad Wahyu Nugroho Sakti; Achmad Basuki; Ali Ridho Barakbah
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Multi-player online games have a matchmaking system, where two or more players can meet each other in a virtual room [19][20]. Players do not gain competitive experience when the matchmaking system uses a single parameter because the system cannot recognize players properly. Previous studies carried out several matchmaking methods, namely skill-based, behavior-based, role-based, and latency-based. However, few studies have discussed the computation of multi-parameter aggregation. We propose a matchmaking system that combines three essential things that become competitive matchmaking parameters: skill rating, behavior cluster, and location cluster. The Elo rating system will use to measure player ability. It will combine with player behavior clustering and player location clustering. It combines a statistical approach to managing distributions and unsupervised machine learning to identify players. Grouping players with machine learning methods is a new thing that has been researched in recent years [6][8]. The application of the algorithm with these parameters is carried out on the trivia education game to make it more competitive
Co-Authors Aditiya Anwar Agus Prasetyo Ali Ridho Barakbah Alimudin, Akhmad Andi Roy Anwar Anwar Aziz, Adam Shidqul Bima Sena Bayu Dewantara David Fahmi Abdillah Dia Bitari Mei Yuana Eko Supriyadi Fikri Aulia I Putu Adi Surya Gunawan Iqbal Sabilirrasyad Kholid Fathoni M Udin Harun Al Rasyid, M Udin Harun Muhammad Aksa Hidayat Muhammad Wahyu Nugroho Sakti Octario Rezkavianto Riyadh Arridha Riyanto Sigit Rizka Rahayu Sasmita Rohmah, Etik Ainun Sholahuddin Muhammad Irsyad Sritrusta Sukaridhoto Taufik Hidayat Titing Magfirah Tri Harsono Wahjoe Tjatur Sesulihatien