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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Petir Computer Science (CO-SCIENCE) Algoritme Jurnal Mahasiswa Teknik Informatika Informatics and Enginering Dedication Klik - Jurnal Ilmu Komputer Arcitech: Journal of Computer Science and Artificial Intelligence Prioritas : Jurnal Pengabdian Kepada Masyarakat MDP Student Conference Jurnal Sistem Informasi Komputer dan Teknologi Informasi Jurnal Teknik Indonesia (JU-TI) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)

Daniel Udjulawa

Universitas Multi Data Palembang

Author-ID : 4240614

Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Other

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Identifikasi Tingkat Kesegaran Daging Ayam Kampung Menggunakan Metode KNN Berdasarkan Warna Daging Kasanova, Sinyo; Udjulawa, Daniel
Jurnal Algoritme Vol 4 No 2 (2024): April 2024 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v4i2.7872

Free-range chicken is a type of poultry that is still natural in the sense that it has not received genetic improvement treatment. The economically advantageous characteristics of free-range chickens are relatively few compared to purebred chickens, even in terms of egg production and the ability to produce meat. Determining the level of freshness of free-range chicken meat is an important factor in determining the quality of the meat to be consumed, so that people as consumers can avoid the worst risks if they consume free-range chicken meat that is not fresh. For this reason, research was carried out to determine the level of freshness of free-range chicken meat using the KNN and HSV methods. The level of freshness is divided into 3 levels, namely rotten, fresh and not fresh. Based on the results of tests carried out using the KNN method with models k=1, k=3, k=5, k=7, k=9, and k=11, it was found that in the testing process the value of the highest accuracy was obtained by the value k=5 namely 80% and k=7, namely 80%, meanwhile the lowest result was obtained by the value k=1, namely 80%.

Klasifikasi Kanker Kulit Pada Citra Dermatoskopi Menggunakan CNN Martin, Nicolas; Udjulawa, Daniel
Jurnal Algoritme Vol 5 No 1 (2024): Oktober 2024 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v5i1.9034

Skin health is an important aspect of human well-being that is often overlooked because it is considered trivial. There are various types of skin diseases, ranging from allergies, fungal infections, to skin cancer which causes high mortality rates according to WHO. Early diagnosis is essential to improve skin cancer recovery, but often requires sophisticated medical devices and biopsies, where doctors remove a patient's skin lesion through minor surgery to detect cancer cells. This study uses the Convolutional Neural Network (CNN) method with the AlexNet architecture to classify skin cancer types. Convolutional Neural Network was chosen because of its ability to extract complex features from images for accurate classification. The dataset used came from Kaggle, consisting of 24,839 images, with testing using all data and 3,000 data, 500 images each for 6 types of skin cancer. The data is divided into 80% for training and 20% for testing. The best results were achieved using 24.839 data, a learning rate of 0.0001, Adamax Optimizer, batch size 16, and epoch 40, resulting in an accuracy value of 72%, a recall value of 72%, a precision value of 70%, and an F1 score of 69%.

Deteksi Kategori Sampah Menggunakan Metode You Only Look Once Ja'far, Ja'far; Udjulawa, Daniel
Jurnal Algoritme Vol 5 No 2 (2025): April 2025 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v5i2.9047

Waste is the residue generated from human daily activities or natural processes that is no longer needed. According to data from the Ministry of Environment and Forestry, waste generation in Indonesia reaches 36 million tons per year, with unmanaged waste totaling 13 million tons annually. Inadequate waste management can lead to various issues. One significant source of unmanaged waste is found in schools, attributed to lack of awareness and low concern, resulting in student’s laziness in disposing of waste properly. This project aims to develop a system that assists students in identifying specific waste categories and incorporates a royalty points system to boost student motivation. The method employed is You Only Look Once Version 5 with the Darknet architecture, utilizing an 80% training, 10% validation, and 10% testing dataset split. The results of testing this method at the development stage showed a recall value of 92.4%, precision of 88.4%, and mAP of 96.4%. Meanwhile, at the implementation stage on smartphones, the recall value reached 89.9% with a precision of 94.2%, and an average detection speed of around 1.68 seconds.

Comparison of Dijkstra's Algorithm and A Star's Algorithm in the Pac-Man game Ramadhan, Ahmad Wildan Rizky; Udjulawa, Daniel
Jurnal Algoritme Vol 1 No 1 (2020): Oktober 2021 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

AI (Artificial Inteligence) atau yang disebut juga dengan kecerdasan buatan merupakan salah satu cabang dari ilmu komputer untuk memberikan suatu pengetahuan pada komputer agar dapat mampu menyelesaikan tugas – tugas atau berpikir seperti manusia. Salah satu contoh kecerdasan buatan yang dapat diterapkan pada game adalah Path Finding. Path Finding adalah salah satu kecerdasan buatan yang dipakai untuk menentukan jaur terpendek antara titik awal dengan titik akhir. Logika Fuzzy merupakan ilmu yang mempelajari mengenai ketidakpastian. Logika Fuzzy juga mampu untuk memetakan suatu ruang input kedalam suatu ruang output dengan tepat. Metode yang digunakan dalam penelitian ini adalah meode prototype dimana tahap-tahap yang dilakukan adalah menganalisis kebutuhan, mendesain prototype, implementasi, dan pengujian. Tujuan utama yang ingin dicapai dari penelitian ini adalah Untuk membandingkan performa algoritma Djikstra dan algoritma A Star untuk penyelesaian game Pac-Man. Hasil yang didapatkan untuk algoritma Dijkstra adalah 2 kali gagal, dan 1 kali berhasil dalam menyelesaikan permainan dengan score 4100, 3350, 3940, sedangkan untuk algoritma A Star mendapatkan hasil 2 kali berhasil, dan 1 kali gagal dengan score 4300, 2350, 3450. Dari kedua Algoritma yang digunakan untuk menyelesaikan permaian PAC-MAN dengan mendapatkan score terbaik adalah algoritma A Star.

PERBANDINGAN PERFORMA ALGORITMA MINIMAX DAN ALPHA-BETA PRUNING PADA GAME CATUR CINA Kurniawan, Marthin Hokita; Udjulawa, Daniel
Jurnal Algoritme Vol 1 No 1 (2020): Oktober 2021 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Algoritma merupakan urutan yang lengkap dan logis, dengan urutan yang logis banyak cara yang dilakukan dengan urutan yang berbeda. Pada kasus ini akan dibandingkan performa dari algoritma Minimax dan Alpha Beta Pruning pada game Catur Cina (XiangQi). Tujuannnya adalah sejauh mana waktu yang digunakan oleh kedua algoritma tersebut efektif dalam permainan Catur Cina. Metodologi yang digunakan dalam membangun aplikasi adalah Rapid Application Development, yaitu merupakan pengembangan dari metodologi Software Development Life Cycle. Kegiatan yang dilakukan antara lain yaitu melakukan perencanaan dan analisis terhadap pengembangan game dan melakukan pembuatan game dengan menggunakan game engine Unity dan bahasa pemograman C#, Editor yang digunakan adalah Atom. Hasil pembuatan game dan koding algoritma akan di uji coba dengan iterasi kedalaman dan preset yang ditentukan sesuai dengan Minimax dan Alpha-Beta Pruning. Data yang didapat yaitu kecepatan dan banyak putaran antara kedua algoritma. Data tersebut akan dibandingkan sehingga performa kedua algoritma akan terlihat jelas.

Perancangan Aplikasi Simulasi Penyelamatan Diri Dari Gempa Bumi Marzali, Azizurrahman; Udjulawa, Daniel; Yoannita, Yoannita
Jurnal Algoritme Vol 1 No 2 (2021): April 2021 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Menurut The World Risk Index tahun 2019, Indonesia berada pada peringkat 37 dari 180 negara paling rentan bencana. Pada tanggal 5 Agustus 2018 gempa bumi di Lombok menelan korban sebanyak 259 orang meninggal dunia, dan 1.033 mengalami luka berat. Kurangnya kesiap siagaan dan edukasi mengenai bencana gempa bumi menjadi salah satu faktor penyebab banyaknya jumlah korban. Maka dari itu dibuatlah sebuah aplikasi simulasi yang ditujukan untuk mengedukasi masyarakat supaya dapat mengetahui apa saja yang harus dilakukan pada saat terjadi gempa bumi. Aplikasi ini dibuat menggunakan metode prototyping untuk melakukan identifikasi masalah yang ada pada setiap kejadian gempa bumi. Tujuan dari pembuatan aplikasi ini adalah untuk memberikan pengetahuan tentang bagaimana cara menyelamatkan diri dari gempa bumi. Aplikasi ini berbentuk game yang mempunyai sudut pandang First Person yang mempunyai empat stage dan setiap stage mempunyai beberapa misi. Pemain harus menyelesaikan seluruh misi pada setiap stage agar dapat melanjutkan ke stage selanjutnya. Hasil dari penelitian ini yaitu menghasilkan sebuah aplikasi simulasi dalam cara menyelamatkan diri dari gempa bumi. Berdasarkan uji Black-Box yang telah dilakukan, diperoleh hasil uji coba bahwa aplikasi ini dapat dijalankan dengan baik dan sesuai dengan tujuan.

Klasifikasi Penyakit Daun Sawit Menggunakan Metode Jaringan Saraf Tiruan Dengan Fitur Local Binary Pattern Simanjuntak, Andreas Jeremy Obet; Udjulawa, Daniel
Jurnal Algoritme Vol 3 No 1 (2022): Oktober 2022 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i1.3158

Diseases on palm leaves are diseases caused by bacteria or fungi. One way to find out diseases on palm leaves is to observe the pattern on the surface of the palm leaves. The pattern on the palm leaves will be analyzed by an expert to find out whether there is disease on the palm leaves or not. This study aims to classify oil palm leaves whether there is disease or not on oil palm leaves by using a program. The right method is needed to produce good accuracy, the researcher uses the ANN (Artificial Neural Network) classification method and the LBP (Local Binary Pattern) extraction method. The steps carried out on the image before being classified are Grayscale, then extraction using LBP (Local Binary Pattern) and classification using ANN (Artificial Neural Network) using 17 train functions with the result that 5 neurons get an average accuracy of 81%, precision 95 %, and 94% recall. In 10 neurons get an average of 95% accuracy, 97% precision, and 96% recall. And the 20 neurons get an average of 97% accuracy, 97% precision, and 96% recall. Keywords: Palm leaf disease, LBP, ANN, neuron

Identifikasi Penyakit Pada Tanaman Kopi Berdasarkan Citra Daun Menggunakan Metode Convolution Neural Network Fatchurrachman, Ahmad; Udjulawa, Daniel
Jurnal Algoritme Vol 3 No 2 (2023): April 2023 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i2.3384

Coffee plants are usually made for drinks made from coffee beans that have been ground into powder. One of the causes of decreased coffee quality is caused by pests that can attack from the leaves, stems and roots. This study aims to identify coffee plant diseases based on leaves using the Convolution Neural Network (CNN) method with the ResNet-50 architecture with the Adam optimizer. The total data from the dataset is 1664 images, in the dataset there are 1264 train data images and 400 test images. The highest result in training in this study using 60 epochs and Adam's optimizer with a probability value of learning_rate of 0.0001 getting a probability value of 0.9969 and the lowest value getting a probability value of 0.4918. The results of testing the test data in this study obtained an accuracy rate of 99%.

Deteksi Masker Melalui Video CCTV Menggunakan You Only Look Once Darmawan, Dean; Udjulawa, Daniel; Wijaya, Novan
Jurnal Algoritme Vol 3 No 2 (2023): April 2023 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i2.3598

The coronavirus pandemic or known as the COVID-19 pandemic is a global pandemic of corona virus that are caused by severe acute respiratory syndrome coronavirus 2 that are started in Wuhan, China in 2019. In 30th January 2020 World Health Organization (WHO) declared an emergency situation towards COVID-19 and in 11th March 2020, WHO officially declared an ongoing global pandemic of COVID-19. COVID-19 cases in the world itself is already reaching 181 million of cases with around 3.92 million deaths. Indonesia itself is one of the country that are affected by COVID-19 spread with 2.09 million cases and 56,729 deaths. In order to decrease the amount of COVID-19 cases, WHO require each individuals to do social distancing, stay hygiene, and always wearing face mask to prevent even more spread of the virus. A method to do face mask detection is proposed using a object detection method, You Only Look Once (YOLO). The test results obtained by calculating f-measure with the highest accuracy of 0.59 and the lowest of 0.19 using CCTV video that are taken with 70 cm distance. In the second test using video that are recorded with more than 90 cm the program obtained it’s result of 0.

Implementasi Algoritma K-Nearest Neighbor untuk Klasifikasi Cuaca Dandy, Dandy; Udjulawa, Daniel; Yohannes, Yohannes
Jurnal Algoritme Vol 4 No 1 (2023): Oktober 2023 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v4i1.4932

Weather is a brief natural event concerning the atmospheric conditions that take place on Earth which are determined by pressure, wind speed, temperature, and air phenomena. This study classifies 3 weather classes, namely sunny, cloudy, and rainy using the K-Nearest Neighbor algorithm as a weather classification algorithm with K value parameters of 3, 5, 7, and 9. Weather dataset 96.453 data to be examined is data taken from the Kaggle website. The dataset is divided into training data and test data with a ratio of 80:20. The implementation of the K-Nearest Neighbor algorithm produces a confusion matrix and classification report where in the confusion matrix, the largest number of correctly predicted data is at the value K = 9, namely 13.132 correctly predicted data with the largest number of correctly predicted data in the cloudy class, namely 10.865 data. As for the classification report, the highest accuracy value for both the cloudy, rainy, and sunny weather classes is at K = 9, which is 68.073%, and the highest precision, recall, and f1-score values are found in the cloudy class at K = 9, respectively contributed 72.095%, 89.288%, and 79.775%.

Co-Authors Abdul Rahman Andre Zulnardi Anggoro Aryo P. Dafid Dafid Dafid Dafid Dandy, Dandy Darmawan, Dean Famerdi, Farhan Agung Fatchurrachman, Ahmad Febbiola Febbiola Febbiola, Febbiola Ja'far, Ja'far Kadafi, Aldo Kasanova, Sinyo Kurniawan, Marthin Hokita M Fajri Septian Dwi Cahyo Martin, Nicolas Marzali, Azizurrahman Muhammad Haviz Irfani Mulyati Mulyati Novan Wijaya Nyimas Artina Oktarina, Serly Pramudiya, Relin Ramadhan, Ahmad Wildan Rizky Regiza Giovanno Setiawan, Jerry Simanjuntak, Andreas Jeremy Obet Sutanto, Steven Yesua Timoteus Ivan Sariyo William William Wiwik Handayani Yoannita, Yoannita Yohannes Yohannes

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