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All Journal Jurnal Media Infotama LEX ET SOCIETATIS Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Sistemasi: Jurnal Sistem Informasi Information System for Educators and Professionals : Journal of Information System Sebatik JOURNAL OF SCIENCE AND SOCIAL RESEARCH EDUKATIF : JURNAL ILMU PENDIDIKAN Menara Ilmu JATI (Jurnal Mahasiswa Teknik Informatika) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Computer Science and Information Technology (CoSciTech) Bulletin of Computer Science Research Journal of Education Research Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Sains dan Teknologi Jurnal Sains Informatika Terapan (JSIT) Jurnal Komtekinfo Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Populer: Jurnal Penelitian Mahasiswa INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Jurnal Ilmiah Teknik Informatika dan Komunikasi Indonesian Research Journal on Education Jurnal Ilmiah Dan Karya Mahasiswa Jurnal Satya Informatika Jurnal Sistem Informasi dan Ilmu Komputer Indo Green Journal Jurnal Elektronika dan Teknik Informatika Terapan Jurnal Penelitian Teknologi Informasi dan Sains Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Jurnal Quancom: Jurnal Quantum Komputer Jurnal Pengabdian Masyarakat dan Riset Pendidikan Journal of Information System and Education Development Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Pengabdian Masyarakat Bangsa Jurnal Ilmu Komputer dan Informatika Indo Green Journal Jurnal TAM (Technology Acceptance Model) Journal of Computer Science Advancements Edumaspul: Jurnal Pendidikan
Billy Hendrik
Universitas Putra Indonesia YPTK Padang
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Prediksi Penjualan Sepeda Motor Yamaha dengan Jaringan Syaraf Tiruan dan Backpropagation (Studi Kasus: CV Sinar Mas) Santriawan, Aji; Gunadi Widi Nurcahyo; Billy Hendrik
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6709

Abstract

Perkembangan teknologi yang begitu pesat dengan kebutuhan masyarakat tentang kendaraan pribadi untuk mempermudah segala aktivitas sehari-hari. Pertumbuhan penduduk Indonesia yang meningkat juga mempengaruhi bertambahnya jumlah kendaraan bermotor yang ada di Indonesia. Sepeda Motor Yamaha merupakan salah satu brand sepeda motor yang telah lama berada di Indonesia. Oleh karena itu konsumen menggunakan sepeda motor saat ini sangatlah tinggi. Dengan peningkatan penjualan dan minat masyarakat terhadap sepeda motor untuk tahun berikutnya. Masalah yang terjadi pada CV Sinar Mas adalah tidak ada metode untuk memprediksi bagaimana kecenderungan peningkatan/penurunan jumlah unit tertentu setiap tahun. Sehinggan dengan Jaringan Syaraf Tiruan menggunakan metode Backpropagation dengan Software Matlab dapat menjadi data prediksi penjualan sepeda motor di bulan berikutnya atau yang akan datang. Penelitian ini bertujuan untuk meningkatkan akurasi penjualan sepeda motor Yamaha pada Cv Sinar Mas. Metode yang digunakan dalam penelitian ini adalah Jaringan Saraf Tiruan Backpropagation. Algoritma Backpropagation digunakan untuk memprediksi dengan akurat berdasarkan data historis penjualan sepeda motor Yamaha dari tahun 2019-2022. Dataset yang digunakan terdiri dari 48 data penjualan. Hasil penelitian ini dapat memprediksi penjualan dengan menggunakan pola terbaik yaitu 4-25-1 dengan hasil MSE 0.00010594. Oleh karena itu penelitian ini dapat menjadi acuan untuk mempredisi penjualan sepeda motor Yamaha pada CV Sinar Mas
Vision Transformer untuk Identifikasi 15 Variasi Citra Ikan Koi Uthama, Rayhan; Yuhandri; Billy Hendrik
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6711

Abstract

This research aims to classify various types of koi fish using Vision Transformer (ViT). There is previous research [1] using Support Vector Machine (SVM) as a classifier to identify 15 types of koi fish with training and testing datasets respectively of 1200 and 300 images. This research was continued by research [2] which implemented a Convolutional Neural Network (CNN) as a classifier to identify 15 types of koi fish with the same amount dataset. As a result, the research achieved a classification accuracy rate of 84%. Although the accuracy obtained from using CNN is quite high, there is still room for improvement in classification accuracy. Overcoming obstacles such as limitations in classification accuracy in previous studies and further exploration of the use of new algorithms and techniques, this study proposes a ViT architecture to improve accuracy in Koi fish classification. ViT is a deep learning algorithm adopted from the Transformer algorithm which works by relying on self-attention mechanism tasks. Because the power of data representation is better than other deep learning algorithms including CNN, researchers have applied this Transformer task in the field of computer vision, one of the results of this application is ViT. This study was designed using class and number datasets retained from two previous studies. Meanwhile, the koi fish image dataset used in this research was collected from the internet and has been validated. The implementation of ViT as a classifier in koi classification in this research resulted in an accuracy level that reached an average of 89% in all classes of test data.
Sistem Deteksi Otomatis dan Self Cleaning pada Cat Litter Box Masril, Mardhiah; Ghinaa Fadhiilah; Ruri Hartika Zain; Billy Hendrik
JURNAL QUANCOM: QUANTUM COMPUTER JURNAL Vol. 2 No. 1 (2024): Juni 2024
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jqc.v2i1.325

Abstract

This research discusses the development of an Automatic Detection and Self Cleaning System on a Cat Litter Box using the Wemos D1 mini microcontroller, to improve the efficiency of cat maintenance. In this context, cats as pets have psychological uniqueness closely related to humans. The litter box, as a specific place for burying cat feces and urine, requires continuous attention and maintenance to keep it clean. This research develops a device that automatically detects cats entering the litter box, and then separates the feces from the sand in the cat litter box. The feces are transferred to a container that will be weighed using a load cell. Cat owners will receive notifications on their smartphone devices through their Telegram application to dispose of the waste. The system also monitors the sand height in the storage container, and the sand dispenser will refill it to a certain limit. The development of this system is expected to provide a solution for cat owners who need to leave their pets for a certain period. This research also demonstrates positive results through testing and notifications on smartphone devices as well as display on the LCD screen in the litter box.
Anomali Data Mining Menggunakan Metode K-Means Dalam Penilaian Mahasiswa Terhadap Pelayanan Prodi Karmanita, Deti; Hendrik, Billy
Jurnal Media Infotama Vol 19 No 2 (2023): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v19i2.4744

Abstract

Cluster analysis is a data mining technique that aims to identify a group of objects that have the same characteristics. The number of groups that can be identified depends on the amount of data and the type of object, so that data problems arise when there is a change to a number of redundant data, but not all of it is changed where the data above is repeatedly made into one table with a different code as the primary key and there are anomalies Insertion, so K-means is one method of clustering data which is divided into the form of one or more clusters/groups that have the same characteristics. Student data clustering uses the k-means method, consisting of student assessments. This study uses student assessment data. Then it was concluded that the assessment group was based on reliability aspects: the ability of lecturers, education staff and administrators to provide services, responsiveness aspects: the willingness of lecturers, education staff and administrators to help students and provide services quickly, aspects of certainty ( assurance): the ability of lecturers, staff and administrators to give confidence to students that the services provided are in accordance with the provisions, aspects of empathy (empathy): the willingness/concern of lecturers, staff and managers to give attention to students, tangibles aspects: students' assessment of the adequacy , accessibility, quality of facilities and infrastructure from the grouping results based on reliability, responsiveness, assurance and empathy data.
Penerapan Algoritma Decession Tree C4.5 Untuk Diagnosa Penyakit Ispa Pada Puskesmas Sabak Auh Sonia Indhira, Sonia; Billy Hendrik
Journal of Information System and Education Development Vol. 1 No. 2 (2023): Journal of Information System and Education Development
Publisher : Manna wa Salwa Foundation (Yayasan Manna wa Salwa)

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Abstract

ABSTRACTInfeksi Saluran Pernapasan Akut atau yang kita sering sebut ISPA merupakan penyakit yang umum terjadi pada semua kategori umur, terutama pada anak- anak. Dengan membuat aplikasi penerapan data mining dengan metode klasifikasi menggunakan Algoritma Decision Tree C4.5 dalam memprediksi seseorang terkena penyakit ISPA, dimana nantinya data yang masuk ke sistem informasi dihitung dengan rumus Algoritma Decision Tree C4.5 yang hasilnya nanti terperinci, dapat menghasilkan nilai secara valid dan lebih akurat.
Penggunaan Metode Systematic Literatur Review Untuk Menganalisis Artikel Sistem Pakar Metode Forward Chaining Resnawita; Billy Hendrik
Journal of Information System and Education Development Vol. 1 No. 2 (2023): Journal of Information System and Education Development
Publisher : Manna wa Salwa Foundation (Yayasan Manna wa Salwa)

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Abstract

The development of AI or artificial intelligence has entered the forefront of the world of technology. Artificial intelligence can be one solution to various problems. One algorithm that uses an AI program is an expert system algorithm where the expert system is an AI program with a knowledge base (Knowledge Base) obtained from experience or expert knowledge or experts in solving problems in certain fields. The forward chaining method is one method of system development, which is a method with decision making that begins with considering information or facts before drawing final conclusions. With the use of the forward chaining method, the system is designed to operate on various devices such as web, mobile, or desktop. This study uses a systematics literature review (SLR) methodology, aims to determine the fields, platforms, and advantages and disadvantages of using the forward chaining method for expert systems that rely on information from related journals between 2020 and 2023
Komparasi Algoritma K-Means Dan K-Medoids Dalam Clustering Penyebaran Kasus Covid 19 olivia, Ladyka Febby; Abdi Juliantho, Dwana; Hendrik, Billy
Journal of Information System and Education Development Vol. 1 No. 2 (2023): Journal of Information System and Education Development
Publisher : Manna wa Salwa Foundation (Yayasan Manna wa Salwa)

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Abstract

Covid 19 is a rapid spread virus that has a negative impact on the province of XYZ. With the Indonesian government policy, four zone policies such as the red, green, yellow, orange zone, which each zone has a different meaning. The algorithm used in this study is K-Means and K-Medoids. Algorithm-Means group data by dividing them into several clusters based on the same characteristics. Whereas the K-Medoids algorithm selects real objects to represent the cluster. In this study, the two algorithms were compared using one dataset. The comparison is done by looking at the value of Davies-Bouldin Index (DBI) on the rapidminer. The best result of K-Means DBI is 0.078 while K-Medoids gives a value of 0.250 which is divided into 2 clusters
Sistem Pakar Mendiagnosa Penyakit Demam Berdarah Menggunakan Metode Certainty Factor Resnawita; Hendrik, Billy
Journal of Information System and Education Development Vol. 1 No. 3 (2023): Journal of Information System and Education Development
Publisher : Manna wa Salwa Foundation (Yayasan Manna wa Salwa)

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Abstract

The increasingly rapid development of technology has changed the world, the launch of various new technologies has made people depend on technology for their work which is very helpful in solving various complex and simple problems. An expert system is a technology that has the abilities of certain experts who are very helpful in solving problems. An expert system is a system that is integrated with computer equipment in which there is knowledge, facts and reasoning techniques in solving problems that usually can only be solved by an expert in that field. Such as an expert system that analyzes dengue fever by relying on the symptoms felt by a person. as a decision maker. Dengue hemorrhagic fever (DHF) is a disease caused by dengue virus infection. DHF is an acute disease with clinical manifestations of bleeding which causes shock which leads to death. This system was designed with the aim of being a means of resolving problems surrounding dengue fever using the certainty factor method. Certainty Factor is a method for proving whether a fact is certain or uncertain in the form of a metric which is usually used in expert systems. The percentage of confidence obtained by the expert system for diagnosing dengue fever reached 94% by referring to the data provided by the user to the expert system.
Penerapan Data Mining Menggunakan Algoritma K-Means untuk Klasifikasi Penyakit ISPA Indhira, Sonia; Hendrik, Billy
Journal of Information System and Education Development Vol. 1 No. 3 (2023): Journal of Information System and Education Development
Publisher : Manna wa Salwa Foundation (Yayasan Manna wa Salwa)

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Abstract

Dengan perkembangan teknologi yang semakin pesat disemua bidang baik dari sektor pemerintahan, pendidikan, pertanian dan khususnya di lingkungan kesehatan, teknologi dapat memberikan informasi yang cepat dan akurat baik untuk tim kesehatan, dokter, perawat bahkan pasien sendiri agar lebih mudah mengontrol kesehatan mereka sendiri. Tujuan penelitian ini adalah menerapkan metode untuk mengklasifikasi penyakit ISPA dan mendapatkan akurasi yang tepat dan cepat dalam mengklasifikasi gejala penyakit ISPA menggunakan metode . Metode yang digunakan yaitu dengan teknik data mining menggunakan algoritma . Proses ini menghasilkan 3 cluster yaitu cluster C1 (ISPA Biasa) dengan jumlah anggota 81, cluster C2 (ISPA sedang) dengan jumlah anggota 103, cluster C3 (ISPA Berat) dengan jumlah anggota 66. Dapat dilihat jumlah pasien penyakit ISPA terbanyak merupakan pasien dengan gejala ISPA ringan . Berdasarkan hasil analisa persentasi untuk tiap cluster adalah cluster pertama memiliki persentasi 35% data, cluster kedua 45% data dan cluster ketiga 20% data. Pengujian menggunakan validasi DBI ( Davies Bouldin Index) diperoleh nilai untuk tiap-tiap cluster. Pengujian cluster 1 menghasilkan nilai DBI -0.244, cluster 2 nilai DBI -0.250, cluster 3 nilai DBI -0.239. Karena nilai DBI dari cluster 3 lebih kecil maka cluster tersebut bisa disebut optimal.
Implementasi Data Mining Pengelompokan Data Penjualan Berdasarkan Pembelian dengan Menggunakan Algoritma K-Means pada UD. Martua Lubis, Siti Sahara; Hendrik, Billy
Journal of Information System and Education Development Vol. 1 No. 3 (2023): Journal of Information System and Education Development
Publisher : Manna wa Salwa Foundation (Yayasan Manna wa Salwa)

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Abstract

Saat ini kita tidak bisa lepas dari pengaruh teknologi informasi. Karena mau tidak mau perkembangan ilmu pengetahuan dan penerapan teknologi mengalami peningkatan yang semakin pesat terutama pada setiap lingkungan kerja seperti praktisi bisnis.Teknologi komputer/ informasi merupakan teknologi yang paling banyak dimanfaatkan diberbagai instansi baik pemerintah maupun swasta . Perkembangan teknologi saat ini yang begitu sangat cepat dari waktu ke waktu membuat pekerjaan manusia pada umumnya dapat diselesaikan dengan cepat. Teknologi merupakan salah satu alat yang sering digunakan dalam aktivitas manusia. Peran teknologi saat ini membuat pengolahan informasi menjadi lebih mudah karena pengolahan diperlukan agar informasi yang dihasilkan dapat bermanfaat bagi penggunanya. Persaingan dalam dunia bisnis menuntut para pengembang untuk menemukan suatu pola yang dapat meningkatkan penjualan dan pemasaran barang, salah satunya adalah dengan pemanfaatan data transaksi. Ketersediaan data yang melimpah, kebutuhan akan informasi sebagai pendukung pengambilan keputusan untuk membuat solusi bisnis, dan dukungan infrastruktur di bidang teknologi informasi merupakan alasan dari lahirnya teknologi data mining. Masalah yang terjadi di UD. Martua yaitu kurang dalam peninjauan produk yang dijual, produk-produk apa saja yang dibutuhkan konsumen dan penyimpanan data-data kurang efektif. Dengan adanya data mining dimaksudkan untuk memberikan solusi nyata kepada UD. Martua agar dapat mengetahui mana barang yang laris dan mana barang yang tidak laris, kemudian dapat membandingkan penjualan dari tahun ke tahun menjadi media yang efektif untuk pengembangan penjualan pada UD.Martua. Dalam pengelompokkan data penjualan field yang digunakan adalah nama barang, jumlah beli, jumlah terjual selama 1 minggu, kemudian data akan diproses dengan algoritma k-means clustering. Hasil akhir dengan 20 sampel data pengelompokkan didapatkan hasil akhir dengan 2 cluster yaitu, cluster 1 (C1) dengan 10 barang laris , cluster 2 (C2) dengan 10 barang tidak laris. Dengan Data mining menggunakan algoritma K-Means Mempercepat untuk pengambilan keputusan untuk merestock barang yang laris agar konsumen yang ingin membeli tidak menunggu lama. Memberikan informasi dari data penjualan untuk mengetahui apa saja yang mengakibatkan keuntungan ataupun kerugian pada UD.Martua. Memberikan kemudahan bagi UD.Martua dalam menentukan produk mana yang laris dan tidak laris agar tidak terjadinya penumpukan barang yang tidak laris dan mengakibatkan kerugian pada UD.Martua.
Co-Authors A'yuni, Qurrata Abdi Juliantho, Dwana Abdi Julianto, Dwana Ade Saputra Ade saputra Afifah Syahidah Nahda Akbar, Syifa Chairunnissa Deliva Akhiruddin Pulungan Amin Amirul Mukminin, Andi Amin, Andi Amir Salim Khairul Rijal Amir Salim Khairul Rijal Amri, Yassirli Andi, Muhammad Yusril Haffandi Aprilian Gevindo Arby, Willya Aswandi, Nopan Awal, Hasri Budiantoro, Hendro Deti Karmanita Dewi, Apriandini Sri Dian Maharani, Dian Diffri Solihin Siregar Doni Karseno Dwana Abdi Juliantho Dzil Hidayati Fadil Idensia Febby Olivia, Ladyka Firdaus Firdaus Firdaus , Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Fitri Amelia Lubis Fungki Wahyu Gevindo, Aprilian Ghinaa Fadhiilah Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Haffandi, Muhammad Yusril Harry Theozard Fikri Hasibuan, Elpina Sari Dewi Hasri Awal Hasri Awal Hasri Awal hidayat, Ilsa Ikhlas, Ariza Indhira, Sonia Juliantho, Dwana Abdi Karseno, Doni Ladyka Febby Olivia Lubis, Fitri Amelia Sari Lubis, Fitri Sari Lubis, Siti Sahara Mardhiah Masril Muhammad, Imam Fakhri Nasution, Ayu Lestiani Nella Novrina Doni Nugraha, Fajri Olivia, Ladyka Febby Ondra Eka Putra Permana, Nabilah Putri Putri Ramadani Raharjo, Tio Doli Resnawita Resnawita Resnawita Rico Anggara Ridwan, Ridwan Riris Agustin Riris Agustin Ritna Wahyuni Rizqi Nusabbih Hidayatullah Gaja Roy Efendi Subarja Roy Efendi Subarja Ruri Hartika Zain Ruri Hartika Zain Ruri Hartika Zain Rusydi, Rezki S Sumijan Sahara Lubis, Siti Sani, Fadhila Putri Santriawan, Aji Sari, Ade Puspita Sarjon Defit Satria Satria, Satria Septiawan, Edo Siti Sahara Lubis Siti Sahara Lubis Sonia Indhira Sonia Indhira, Sonia Sovia, Rini Sri Mulya Subarja, Roy Efendi Sukardi Sukardi Sumijan Supperianto, Bambang Suri, Melati Rahma Sutri, Ridwan Syafri Arlis Tamin, Zulfiqar Uthama, Rayhan Vidyanti, Angela Waruwu, Kalfinus Wira, M Wira Sanjaya Wirdawati, Wira Yanto, Musli Yuhandri Yuhandri, Yuhandri Yuliana Pertiwi