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All Journal CCIT (Creative Communication and Innovative Technology) Journal ICIT (Innovative Creative and Information Technology) Journal Journal Sensi: Strategic of Education in Information System CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics
Hendra Kusumah
Universitas Raharja
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice

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Media Video Company Profile Penunjang Informasi Dan Promosi PT. Harafiel Trijaya Sendy Zul Friandi; Hendra Kusumah; Muhammad Aditya Rifky Cahyadi
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 7 No 1 (2021): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1190.646 KB) | DOI: 10.33050/cices.v7i1.1463

Abstract

The internet has become the life of every human being, the internet has several types such as text, images, photos, sound, video and audio-visual. Every company, whether large, medium, or small-scale companies need something called a company profile as well as PT. Harafiel Trijaya. Currently PT. Harafiel Trijaya still uses promotion by means of promotional designs which are deemed insufficient for its dissemination to the wider community, so it is necessary to make a very good profile video so that the public or potential customers know a lot about PT. Harafiel Trijaya. PT. Harafiel Trijaya is engaged in the construction service industry (Engineering and Construction) which includes Civil Works, Building and Architecture Works, Mechanical and Electrical Works. This video company profile was created using video support applications such as Adobe Premiere Pro.
PENERAPAN TRAINER INTERFACING MIKROKONTROLER DAN INTERNET OF THINGS BERBASIS ESP32 PADA MATA KULIAH INTERFACING Hendra Kusumah; Restu Adi Pradana
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 5 No 2 (2019): JOURNAL CERITA
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (864.053 KB) | DOI: 10.33050/cerita.v5i2.237

Abstract

The absence of props remains a constraint on the learning process interfacing subjects where students have difficulty understanding the material obtained, besides because of the lack of microcontroller practice experience, students don't understand how to operate the microcontroller and also because of the lack of basic knowledge about the microcontroller. The design of the microcontroller interface trainer is intended as a teaching aid to help understand microcontroller interfacing using the UART, SPI, and I2C protocols and can be used as an Internet of Things teaching aid to help students practice monitoring and controlling input output on microcontrollers using smartphones over the internet. In designing this trainer, the author had made direct observations on learning activities in interfacing subjects and conducted questions and answers with several students. This trainer uses RFID, RTC and LCD modules as interfacing props that are connected to the ESP32 microcontroller, and there are components in the form of LEDs and potentiometers to practice the concept of the Internet of Things. The GPIO header pins and microcontroller interface pins expansion are also available on this trainer which can be connected with more modules and other components. Modules and components in the design of this trainer are connected with the ESP32 microcontroller in one integrated circuit board so as to provide practicality in its use.
Deep Learning on Facial Expression Detection : Artificial Neural Network Model Implementation Hendra Kusumah; Muhammad Suzaki Zahran; Paksi Ryandana Cholied; Muhammad Surya Alkusna; Naufal Alwan Hafidhi
CCIT Journal Vol 16 No 1 (2023): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (939.203 KB) | DOI: 10.33050/ccit.v16i1.2518

Abstract

The moods, emotions, and even medical issues of a person can frequently be seen directly reflected in their facial expressions. The fields of social science and human-computer interaction have recently begun to pay more attention to facial emotion detection as a result of this. The primary focus of this study is on the automatic recognition of human facial expressions using an artificial neural network (ANN) model and a technique based on straightforward convolution. The dataset utilized is a self-mined dataset that was obtained by utilizing the web scraping approach on Google Image with the help of the Selenium package for Python. A dataset containing six categories of fundamental human expressions that are likely to be met on a daily basis, namely anger, confusion, contempt, crying, sadness, disgust, and happiness, with a total of 6,016 photos being used. The goal of this research is to determine how accurate the model of artificial neural networks can be in predicting.
Deep Learning Pada Detektor Jerawat: Model YOLOv5 Hendra Kusumah; Muhammad Suzaki Zahran; Kadek Naufal Rifqi; Devi Alawiyah Putri; Ety Meina Wakti Hapsari
Journal Sensi: Strategic of Education in Information System Vol 9 No 1 (2023): Journal Sensi
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1047.273 KB) | DOI: 10.33050/sensi.v9i1.2620

Abstract

Jerawat (Acne Vulgaris) merupakan masalah utama yang sulit untuk dihindari pada masyarakat daerah perkotaan, seperti Jakarta dan sekitarnya. Penyebab utama dari jerawat yaitu tingginya polusi udara yang disebabkan oleh hasil pembakaran transportasi dan sektor industri. Sisa pembakaran ini umumnya mengandung PM (Particulate Matter) dengan ukuran yang cukup kecil (PM2.5 dan PM10) yang mampu masuk ke dalam kulit melalui pori-pori dan bereaksi dengan beberapa senyawa diudara sehingga menyebabkan banyak permasalahan kulit lainnya. Penelitian ini berfokus pada pendeteksian jerawat dengan menggunakan model Deep Learning, yaitu YOLOv5. YOLOv5 dilatih dengan menggunakan tiga optimizer berbeda (SGD, Adam, dan AdamW) sebanyak 100 epochs. Setelah dilakukan pelatihan, didapatkan hasil F1-score dengan optimizer SGD sebesar 43%, Adam 39%, dan AdamW sebesar 40%. Pada penelitian ini, optimizer SGD memiliki nilai F1 tertinggi sehingga dijadikan sebagai optimizer teroptimum yang dapat digunakan pada permasalahan di penelitian ini.
Deep Learning for Pothole Detection on Indonesian Roadways Hendra Kusumah; Mohamad Riski Nurholik; Catur Putri Riani; Ilham Riyan Nur Rahman
Journal Sensi: Strategic of Education in Information System Vol 9 No 2 (2023): Journal Sensi
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sensi.v9i2.2911

Abstract

Accidents are common on Indonesian roadways. Accidents are caused by vehicles, motorcycles, and public transportation. Road fatalities are caused by speeding, alcohol, distraction, fatigue, and poor road conditions. There are numerous car accidents on Indonesian roadways. 30% of Indonesian traffic incidents are explained by road infrastructure and environmental conditions, 61% by driver skill and personality, and 9% by vehicle variables such as vehicle standardization. Cars are damaged, immobilized, and crashed as a result of road conditions. Every hour, three people pass away in traffic in Indonesia, according to authorities. According to the BPS's 2021 Land Transportation Statistics report, 31.91 percent of Indonesia's roads were damaged, totaling 174,298 kilometers. Accidents among Indonesian motorists are becoming more common as roads deteriorate. Using a single camera, a deep learning algorithm can recognize and detect road degradation such as potholes and road cracks. Train and process the model using transfer learning and fine-tuning on the Nano YOLOv5 model architecture. After being validated in three major scenarios, the model performs well with the appropriate confidence level. The precision metric for the model is 0.8, while recall and mAP:0.5 are both 0.5.
Meningkatkan Profesionalitas Kerja Dengan Pemahaman Etika Profesi Dalam Dunia Bisnis H Suhada; Hendra Kusumah; Muhammad Rizki Fadlan Nullah
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 10 No 1 (2024): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v10i1.2735

Abstract

In becoming a professional at his job, it is necessary to instill and apply an understanding of professional ethics. Professional ethics is a very important aspect in carrying out business activities. Professional ethics can affect a company's image, consumer trust, and relationships with business partners. Professional ethics must be considered more to be able to face all challenges in the business world. Professional ethics can help companies to maintain a good image and reputation in the eyes of the public and improve employee professionalism. In the research conducted by the researcher this time, it is a qualitative research with data collection methods through literature study methods via the internet. The purpose of this study is to find out how important professional ethics are in improving one's professionalism in running a business. This research can also contribute to the development of science and business practice in Indonesia, especially in strengthening aspects of professional ethics in business activities. Thus, this research is expected to provide a better understanding of the importance of professional ethics in business activities as well as provide solutions and recommendations to improve work professionalism by applying good professional ethics in business activities in Indonesia.
Optimasi dan Perancangan Antena Menggunakan Metode Modified Efficient K-Nearest Neighbors Deden Rustiana; Nina Rahayu; Hindriyanto Dwi Purnomo; Ahmad Bayu Yadila; Hendra Kusumah
ICIT Journal Vol 10 No 2 (2024): Agustus 2024
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/icit.v10i2.3204

Abstract

Untuk memastikan akurasi dan mencegah perilaku machine learning yang tidak diinginkan terjadi ketika model machine learning memberikan prediksi akurat untuk data pelatihan tetapi tidak untuk data baru yang biasa disebut Overfitting, teknik machine learning yang efektif biasanya dilatih pada kumpulan data besar. Namun, ketika pengumpulan data rumit, kumpulan data yang besar menghambat penyebaran teknik machine learning. Algoritma K-Nearest Neighbors (KNN) ditingkatkan dalam penelitian ini untuk mengatasi masalah dan menyajikan pendekatan machine learning yang unik sehingga dapat mengekstraksi lebih banyak fitur dari kumpulan data yang besar. Metode ini bekerja 5 hingga 30 kali lebih cepat daripada teknik machine learning konvensional seperti jaringan syaraf tiruan (ANN) dan pengoptimalan Bayesian. Parameter antena digunakan untuk mengoptimalkan kemudian dioptimalkan menggunakan metode yang disarankan, dan cabang terpisah dibuat untuk menjalankan alat simulasi (seperti HFSS) dan memperbarui dataset saat pelatihan daripada membuatnya sebelumnya. Empat contoh antena lainnya, serta machine learning tambahan dan teknik berbasis gradien, digunakan untuk mendukung validitas dan efektivitas pendekatan yang disarankan. Kesimpulannya, metode ini disarankan dapat menghasilkan desain antena ideal dan harga terjangkau.
Co-Authors Ahmad Bayu Yadila Catur Putri Riani Deden Rustiana Devi Alawiyah Putri Ety Meina Wakti Hapsari H Suhada Hindriyanto Dwi Purnomo Ilham Riyan Nur Rahman Kadek Naufal Rifqi Mohamad Riski Nurholik Muhammad Aditya Rifky Cahyadi Muhammad Rizki Fadlan Nullah Muhammad Surya Alkusna Muhammad Suzaki Zahran Naufal Alwan Hafidhi Nina Rahayu Paksi Ryandana Cholied Restu Adi Pradana Sendy Zul Friandi