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All Journal JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) SEIKO : Journal of Management & Business Jurnal Pengabdian kepada Masyarakat Nusantara Brilliance: Research of Artificial Intelligence
Sukenda Sukenda
Universitas Widyatama
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Social Sciences Other

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IMAGE PROCESSING BASED TILAPIA SORTATION SYSTEM USING NA Sukenda Sukenda; Ari Purno Wahyu; Benny Yustim; Sunjana Sunjana; Yan Puspitarani
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 7 No. 1 (2020)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (349.654 KB) | DOI: 10.33197/jitter.vol7.iss1.2020.459

Abstract

Tilapia has a value of export quality and is imported from America and Europe, tilapia is cultivated in freshwater, the largest tilapia producing areas are Java and Bali for the export market in the Middle East, value fish with a size of 250 grams / head (4 fish / kg ) in their intact form is in great demand. According to news circulating, fish of this size in the Middle East are ordered to meet the consumption of workers from Asia. the fish classification process is a very difficult process to find the quality value of the fish to be sold to meet export quality. Fish classification techniques can use the GLCM technique (Gray Level Oc-Currance Matrix) classification using images of fish critters with the GLCM method.The fish image data is analyzed based on the value of Attribute, Energy, Homogenity, Correlation, Contrash, from the attribute the density data matrix is ??generated for each. Fish image data and displayed in the form of a histogram, the data from the GLCM results are then classified with the Naive Bayes algorithm, from the results of the classification of data taken from 3 types of tilapia from the types of gift, Red, and Blue.
MODELING OF DIGITALIZATION AND VISUALIZATION OF LABOR COMPLAINTS USING OCR, FEATURE EXTRACTION AND BUSINESS INTELLIGENCE Yan Puspitarani; Sukenda Sukenda; Ari Purno Wahyu; Benny Yustim; Sunjana Sunjana
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 7 No. 2 (2021)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (591.569 KB) | DOI: 10.33197/jitter.vol7.iss2.2021.592

Abstract

The handling of labor complaints is one of the performance factors for Disnakertrans. This performance is related to the decisions that must be taken to determine policies so that violations of labor norms can be reduced. Making this decision will be easier if the data on complaints can be recapitulated quickly and accurately. This recapitulation will be a tool to monitor the leadership in seeing the progress report on the status of incoming complaints. However, the manual administrative process makes the recapitulation slower. Therefore, this study will model the complaint reporting digitization system by utilizing OCR and information extraction as well as modeling the visualization of the results of the recapitulation using Business Intelligence. With the creation of this model, it is hoped that the performance of Disnakertrans in resolving labor complaints will be more effective
Pemanfaatan Sarana dan Prasarana Media e-Learning atau Virtual Laboratory dalam Pembelajaran Jarak Jauh di Era Pandemi Covid-19 Sukenda Sukenda; Ari Purno Wahyu; Benny Yustim; Helmy Faisal Mutaqien; Ulil Surtia Zulpratita
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 3 No. 2.1 Desember (2022): SPECIAL ISSUE
Publisher : Cv. Utility Project Solution

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Abstract

Training activities, one of the community service activities, vocational high school teacher training activities. The purpose of the training is to provide an overview of learning subjects using e-learning or virtual laboratories. It is hoped that the training will take the form of learning and the learning process will be carried out with online learning during the covid-19 pandemic. The training discussed about e-learning or virtual laboratory learning to Vocational High School teachers. This model has the aim that competence in the field of learning and practice is carried out well. Learning development using online media, virtual laboratory is a practical learning media that is carried out online. E-learning, learning subjects using information technology media. The ability to manage and use e-learning and virtual laboratories is required in distance learning (PJJ). The development of distance learning or online is the right step in using e-learning or virtual laboratories in the covid-19 pandemic era.
Cyber Pandemic – The New Cybersecurity Risks Sukenda, Sukenda; Zulpratita, Ulil Surtia; Muttaqin, Helmy Faisal; Wahyu, Ari Purno; Yustim, Benny
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4759

Abstract

We are amidst a digital pandemic. In 2020, COVID-19 sped up a change towards remote working and the product being utilized for these assaults has become more straightforward to execute, ransom ware assaults have risen quickly and keep on speeding up in 2021. The COVID-19 pandemic has changed both the actual world and the computerized space, where organizations and associations are being gone up against with overwhelming online protection challenges for which not many were prepared or prepared to confront. Attributable to the extreme change in working conditions, cyber attacks and information extortion presently rank third among the best worries of business pioneers, as detailed in the World Economic Forum's COVID-19 Risks Outlook. The likelihood of malignant digital movement is considerably more upsetting thinking about that 53% of organizations have never pressure tried their systems. The key focus point from these and a large group of other alarming probabilities is that readiness for any kind of digital emergency whatsoever levels of an association is critical. Top administration, network protection trained professionals and each representative should know how to treat an emergency hit. Cyber security centers around securing information, yet it is presently not adequate; organizations need cyber resilience.
Pengenalan Karakter Anak Untuk Mengenali Potensi Berdasarkan Sinyal Fisiologi Menggunakan K-Nearest Neighbors Classifier Sukenda, Sukenda; L, Eka Angga; Kohar, M.
SEIKO : Journal of Management & Business Vol 6, No 2.1 (2023)
Publisher : Program Pascasarjana STIE Amkop Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/sejaman.v6i2.5891

Abstract

Perkembangan teknologi informasi mulai diterapkan di bidang psikologi, salah satu contohnya adalah aplikasi yang digunakan untuk pengenalan emosi. Pada dasarnya, proses pengenalan emosi dapat dilakukan melalui beberapa cara yaitu penulisan (text), sinyal fisiologi, ekspresi wajah, intonasi suara, dan gerak tubuh. Akan tetapi, ada kemungkinan ekspresi wajah, tulisan tangan, intonasi suara dan gerak tubuh bisa dimanipulasi, sehingga membuat pengenalan emosi menjadi kurang valid. Pengenalan emosi melalui sinyal fisiologi lebih representatif dan mampu memberikan hasil yang lebih objektif karena sinyal fisiologi tidak dapat dikontrol secara sadar oleh penggunanya sendiri. Sinyal fisiologi yang dapat digunakan untuk mengenali emosi adalah detak jantung dan respon dari konduktansi kulit. Untuk dapat melakukan pengenalan emosi berdasarkan sinyal fisiologi ini dilakukan dengan membangun sebuah sistem aplikasi. Sistem aplikasi ini, terdiri dari dua unit utama yaitu unit hardware dan unit software. Unit hardware terdiri dari dua sensor yaitu sensor pulse dan sensor GSR yang terintegrasi dengan microcontroller arduino, integrasi ini untuk melakukan pengukuran sinyal dari tubuh. Unit software berfungsi untuk mengolah data yang terdiri dari aplikasi user interface, sistem database, dan machine learning. Data yang diterima dari sensor, akan disimpan ke database yang kemudian dilakukan proses pre-processing data, feature scaling, dan klasifikasi data. Proses pre-processing data terdiri dari dua tahapan, yaitu filter data dan filter attribute. Kemudian feature scaling digunakan untuk proses normalisasi. Setelah melalui kedua proses tersebut, data diklasifikasikan menggunakan algoritma KNN, untuk melakukan proses prediksi emosi. Dari hasil penelitian, sistem aplikasi yang dibangun mampu melakukan proses pengukuran sinyal fisiologi dan klasifikasi emosi dengan rata-rata nilai akurasi, presisi, dan recall adalah 76%. Kata kunci : Aplikasi, Emosi, Sinyal fisiologi, KNN.
Co-Authors Ari Purno Wahyu Wibowo Benny Yustim Helmy Faisal Mutaqien Kohar, M. L, Eka Angga Muttaqin, Helmy Faisal Sunjana * Sunjana Sunjana Ulil Surtia Zulpratita Yan Puspitarani