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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Informatika Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Prosiding SNATIF Infotech Journal Jurnal Pendidikan Informatika dan Sains Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) IKRA-ITH Informatika : Jurnal Komputer dan Informatika JURIKOM (Jurnal Riset Komputer) JUMANJI (Jurnal Masyarakat Informatika Unjani) Jurnal Informasi dan Komputer SEINASI-KESI Jurnal Cendikia Jurnal ICT : Information Communication & Technology Building of Informatics, Technology and Science Jurnal Muara Sains, Teknologi, Kedokteran dan Ilmu Kesehatan JUTIS : Jurnal Teknik Informatika SENSITEK Jurnal Informatika dan Rekayasa Elektronik JATI (Jurnal Mahasiswa Teknik Informatika) Abdi Masyarakat Tematik : Jurnal Teknologi Informasi Komunikasi Innovation in Research of Informatics (INNOVATICS) Journal of Applied Computer Science and Technology (JACOST) Jurnal Ilmiah Wahana Pendidikan Journal La Multiapp International Journal Software Engineering and Computer Science (IJSECS) Istech Journal (International Science And Technology Journal) Batara Wisnu : Indonesian Journal of Community Services Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Locus Penelitian dan Pengabdian Jurnal Informatika Teknologi dan Sains (Jinteks) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Algoritma Smart Society: Community Service and Empowerment Journal Electrician : Jurnal Rekayasa dan Teknologi Elektro IJESPG (International Journal of Engineering, Economic, Social Politic and Government) journal Enrichment: Journal of Multidisciplinary Research and Development Jurnal Ilmu Komputer, Sistem Informasi, Teknik Informatika (JILKOMSITI) Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Jurnal Alih Teknologi Komputer (ALTEK) Journal Of Informatics And Busisnes International Journal of Electrical, Computer, and Biomedical Engineering (IJECBE) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Komputasi
Komarudin, Agus
Universitas Jenderal Achmad Yani
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Rekomendasi Pemilihan Pemain Sepak Bola Terbaik Pada Liga X Menggunakan Metode Topsis Oki Iskandar; Gunawan Abdillah; Agus Komarudin
Prosiding SISFOTEK Vol 4 No 1 (2020): Vol 4 No 1 (2020): SISFOTEK 2020
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (327.982 KB)

Abstract

Football is a popular sport that is widely played. Proved by the number of competition titles held. Every team that competes, will provide competitive competition. Players who play an important role in presenting competitive competition. Competition that occurs is not only the team that competes but all players take part in the competition to be the best. Each competition will reward each of the best players throughout the competition. The many factors and players involved make it difficult for the organizers to determine the best player. Decision support system is a computer-based system that can manipulate data into information that can provide alternative decisions or problem solving, so that data can be processed into information. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision making method or has many criteria. This research resulted in a decision support system that can be used to choose the best soccer players by using a combination of individual ability criteria, contribution to the team, aspects of fair play and the number of minutes played. By using the TOPSIS method, as many as 11 player data were tested and resulted in a suitability level of 57.14%.
Desain Game Edukasi Bertema Penerapan Akhlakul Karimah Menggunakan Framework Mechanics Dynamics Aesthetics Selia Aysiah; Agus Komarudin; Rezki Yuniarti
Prosiding SISFOTEK Vol 4 No 1 (2020): Vol 4 No 1 (2020): SISFOTEK 2020
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Good character is a commendable attitude in accordance with Islamic teachings. Someone who has a moral character will always be liked by fellow human beings. A child does not understand whether what he is doing is dangerous or not, beneficial or detrimental, as well as right and wrong. The way to develop morality in children is by teaching them noble character. But in fact the environments that exist at this time more are considered as the cause of the occurrence of moral dedication, one of which is the rise of gadgets that contain game elements that are less educational. Based on these problems, it is necessary to present an educational game that is expected to be one of the ways to deliver the material so that children can participate in the learning of morality with good fun. In designing and compiling elements in a game one of them uses a framework method that has a sub method called Mechanics Dynamics Aesthetics (MDA). The MDA Framework was developed as a framework for understanding games through the perspective of users and developers. Based on the evaluation results of the game test through a questionnaire, where the aspects tested consist of the background of the respondent, the interaction of the respondent with the User Interface of the game, and the aesthetic or emotional challenge that must be felt when playing a good character game shows that the respondent feels happy and gets new knowledge about the character good and bad in the game.
DETEKSI OBJEK DAN JENIS BURUNG MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DENGAN ARSITEKTUR INCEPTION RESNET-V2 Prima Nugraha; Agus Komarudin; Edvin Ramadhan
INFOTECH journal Vol. 8 No. 2 (2022)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v8i2.2889

Abstract

Banyaknya spesies burung membuat kita kesulitan untuk mengenali jenis burung dan diperlukannya pemahaman yang lebih khususnya dalam bidang zoologi. mengenali spesies burung secara manual merupakan tugas berat, di perlukannya SDM yang besar untuk mengidentitifikasi spesies burung apalagi jumlah yang akan akan di identifikasi begitu banyak dan juga memakan banyak waktu. Pada penelitian ini membuat sebuah sistem yang dapat mengenali spesies burung menggunakan citra gambar secara otomatis dengan menggunakan salah satu Arsitektur dari Convolutional Neural Network yaitu Inception Resnet V2, sehingga data citra tersebut dapat diekstraksi kemudian dapat mengenali spesies dari jenis burung. Yang bertujuan untuk melakukan pemantauan satwa khususnya burung dengan mengidentifikasi spesies burung secara otomatis, kemudian diharapkan masyarakat dengan mudah untuk mengenali jenis burung dan juga meningkatkan kemampuan kita untuk mempelajari dan melestarikan ekosistem khususnya ekosistem burung.
Efektivitas Penggunaan E-Modul PAI-PTU Sebagai Bahan Pembelajaran Mandiri Nina Ikhwati Wahidah; Iskandar Iskandar; Agus Komarudin
Jurnal Ilmiah Wahana Pendidikan Vol 8 No 19 (2022): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (171.338 KB) | DOI: 10.5281/zenodo.7222847

Abstract

The purpose of this study was to see the effectiveness of using the PAI-PTU e-module for independent learning for students of the Faculty of Science and Technology, Nahdlatul Ulama University, Lampung. The research method used is a quasi-experimental, this research is classified as pre-experimental research. One group pretest and posttest to see the improvement of student learning outcomes before and after using PAI-PTU e-module learning materials as independent learning materials. The sample in this study were 100 students obtained by random sampling. The result of this study is the use of the PAI-PTU e module as an independent learning material can be seen from the results of the paried t-test, based on the results of the paired t-test, the 2-tailed significance is 0.000 < 0.05, because the 2-tailed significance result is smaller. of 0.05, it can be concluded that there is a significant difference between the results of the pretest and posttest of the use of the pai-ptu e-module at Nahdlatul Ulama University Lampung. Next for the t-count value is 13,554, then for the t table with df 99 it is 1,984. Then it can be seen that the t count is 13,554 > 1,984 t table, so it can be concluded that there is a significant difference from the pretest results before using the pai-ptu e-module learning material with the posttest results after using the pai-ptu e-module.
Gamifikasi untuk Meningkatkan Partisipasi Masyarakat Dalam Mendukung Konsep Ketahanan Terhadap Bencana Asep Id Hadiana; Rezki Yuniarti; Agus Komarudin
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

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Abstract

This study discusses the use of gamification techniques in enhancing community involvement in disaster emergency planning activities. The objective of this study is to explore how gamification can be incorporated into disaster emergency planning programs to enhance disaster resilience in West Bandung Regency. The study was conducted by collecting data from respondents through online questionnaires and structured interviews to evaluate the effectiveness of gamification techniques in motivating community participation in disaster emergency planning. The results show that the use of gamification techniques can increase community participation in disaster emergency planning programs and can also influence the democratic process. Therefore, this study provides evidence that the use of gamification techniques can be an effective tool in enhancing the efficiency and intelligence of disaster emergency planning and can help achieve the goal of disaster resilience in West Bandung Regency.
DESAIN GAME EDUKASI PENGENALAN PEREDARAN SEL DARAH MERAH DENGAN GENRE RPG MENGGUNAKAN PENDEKATAN MDA Iman Muhdi; Rezki Yuniarti; Agus Komarudin
Jurnal Informatika dan Rekayasa Elektronik Vol. 6 No. 1 (2023): JIRE April 2023
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v6i1.817

Abstract

Salah satu masalah dalam suatu pembelajaran adalah cara penyampaian yang umumnya dilakukan dengan pemaparan materi dan tanya jawab masih membuat sebagian siswa tidak memahami apa yang dipelajarinya. Game Edukasi merupakan salah satu strategi yang dapat dibangun sebagai media pembelajaran baru untuk menarik minat siswa dalam semangat belajar. Konsep pemahaman siswa dalam ilmu biologi khususnya pembahasan peredaran sel darah merah pada manusia masih tergolong kurang dipahami. Pada penelitian ini dibangun sebuah game bergenre Role-playing game (RPG) yang membahas materi peredaran sel darah merah dalam rangka meningkatkan pemahaman terhadap materi tersebut. Perancangan game ini menggunakan framework Mechanics, Dynamics, Aesthetics (MDA) dengan tujuan lebih menonjolkan sisi edukasinya tanpa mengurangi keseruan gameplay gamenya. Penerapan framework MDA pada pengembangan game edukasi untuk meningkatkan pemahaman materi terbukti diterima dengan baik oleh siswa dan berhasil mengembangkan experience dalam minat gameplay. Hal tersebut didapatkan melalui pengujian dengan hasil aspek pemahaman materi meningkat sebesar 14.23%, dari sebelumnya 72.47% menjadi 86.70% dan hasil aspek experience user dalam minat gameplay juga meningkat sebesar 6.87% dari sebelumnya 85.40% menjadi 92.27%.
Peramalan Indeks Harga Saham PT XYZ Menggunakan Metode Double Moving Average (DMA) M.Naufal Rafirhan; Ade Kanianingsih; Agus Komarudin
IJESPG (International Journal of Engineering, Economic, Social Politic and Government) Vol. 1 No. 3 (2023)
Publisher : IJESPG (International Journal of Engineering, Economic, Social Politic and Government)

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Abstract

The stock price index is an indicator that is useful as an illustration of the movement of stock prices in a period. Forecasting on the stock price index can be used as a reference or benchmark in capital market activities and products resulting from investment. In this study, there is a goal to be achieved, namely to predict the stock price index at PT XYZ based on existing historical data to see how accurate the forecast is made on actual data using the forecasting method, namely the Double Moving Average (DMA) method, which is a model. forecasting to determine the trend of a time series, so that it will obtain stock price index value forecasting data based on existing historical data. In this research, forecasting will be carried out regarding the stock price index for the period June 2018 - June 2023 at PT XYZ (Persero) Tbk, which is one of the BUMNs engaged in the construction sector. Based on the results obtained by forecasting the Double Moving Average (DMA), the values for forecasting the stock price index for the value for forecasting the stock price index for the Open index type is 3.27%, High 3.11%, Low 3.10%, and Close 3.17% each having a MAPE value of <10% . So that in the research "PT XYZ STOCK PRICE INDEX FORECASTING USING THE DOUBLE MOVING AVERAGE (DMA) METHOD" the performance of the prediction model carried out has very good and accurate performance.
SISTEM KLASIFIKASI UNTUK MENENTUKAN TINGKAT STRESS MAHASISWA SECARA UMUM MENGGUNAKAN METODE K-NEAREST NEIGHBORS Sopwatun Anisa; Agus Komarudin; Edvin Ramadhan
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 3 (2024): EDISI 21
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i3.4317

Abstract

Stress is often the main challenge faced by students due to academic and social demands in the educational environment. Factors such as nervousness, inability to control oneself, worry, etc. are several stress triggers, all of which can have a negative impact on students' physical and mental health. This research aims to identify the level of stress experienced by students using the K-Nearest Neighbors (KNN) method and evaluate the accuracy of the results of this research. The KNN method is used to classify student stress levels based on similarity or closeness to other data in the dataset. By using data taken from the data.world site, the results of this research show that the KNN method is able to achieve an accuracy of 91.58%. In addition, the precision, recall, and f1-score values are 76.10%, 73.11%, and 74.17% respectively. This research makes an important contribution in understanding student stress levels and shows the effectiveness of the KNN method in classifying stress data. It is hoped that these results will help in the development of better strategies for managing and reducing stress among college students.
PREDIKSI PENJUALAN OBAT MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK Farhan Fadilah; Melina Melina; Agus Komarudin
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 3 (2024): EDISI 21
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i3.4346

Abstract

Pengelolaan persediaan obat yang efektif merupakan salah satu komponen penting dalam meningkatkan layanan kesehatan. Namun, masalah yang sering dihadapi dalam penjualan obat herbal adalah persediaan yang sering berlebih sehingga menyebabkan kerugian karena obat herbal menjadi kadaluwarsa. Selain itu, adanya pendataan stok obat yang secara manual juga menyebabkan sering terjadinya kesalahan dalam laporan persediaan, termasuk penggandaan atau redundansi data penjualan. Untuk mengatasi masalah ini, diperlukan suatu metode prediksi penjualan yang akurat untuk pengambilan keputusan strategis. Penelitian ini menggunakan metode Artificial Neural Network (ANN) yang memiliki kemampuan dalam menangani data non-linear pada data penjualan obat. Penelitian ini menggunakan data time series dan algoritma feedforward propagation. Metodologi penelitian meliputi penentuan data latih (70%) dan data uji (30%), serta perancangan arsitektur ANN yang mencakup input layer, hidden layer, output layer, bobot awal, learning rate, momentum, epoch, dan fungsi aktivasi. Hasil penelitian ini memperoleh nilai MAPE 26,3096% dan akurasi 73,6904%.
Sistem Prediksi Hasil Produksi Jagung Menggunakan Algoritma Decision Tree C.45 Aghnie Kurnia; Wina Witanti; Agus Komarudin
Journal Of Informatics And Busisnes Vol. 2 No. 2 (2024): Juli - September
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v2i2.1571

Abstract

This research aims to develop a corn production prediction system using Decision Tree C4.5 algorithm. The system is designed to help farmers and stakeholders make better decisions regarding corn production. The data used was obtained from Kaggle, consisting of 4,121 data from various countries. The system development process involved several stages, including data preprocessing, normalization, and division of the dataset into training data (80%) and test data (20%). The C4.5 Decision Tree algorithm was chosen due to its ability to handle both continuous and categorical attributes, as well as produce an easy-to-understand decision tree. The results showed that the developed system was able to predict corn production with an accuracy rate of 92.82%. With this system, it is expected that farmers can conduct more effective and efficient production planning, and reduce the risk of losses due to inaccurate predictions.
Co-Authors Ade Kania Ningsih, Ade Kania Ade Kanianingsih Aditya Prakasa Aek Mustofa Aghnie Kurnia Aini Nurul Akhmadi Surawijaya Al Farisi, Muhammad Farid Alda Amorita Azza Alfarizi, Muhammad Bayu Ardi Asep Id, Hadiana Atika Hendryani Azhari, Anissa Azzahra, Bunga Juliana Bambang Suparapto Damayanti, Ariesta Daswara Djajasasmita Dea Destiani Deka P Gustiawan Denny Hidayat Tri Nugroho Devian, Devian Dewi Purnamasari Diansyah Andri Ramdhany Dimitri Mahayana Djamal, Esmeralda Contesa Eddie Khrisna Putra Edvin Ramadhan Erlangi, Fauzan Erlangi, Fauzan Erry Fuadillah Esmeralda C Djamal Esmeralda C Djamal Esmeralda C Djamal Esmeralda C. Djamal Esmeralda C. Djamal Esmeralda C. Djamal Esmeralda C. Djamal Fadilah, Vira Hasna Fahmi Yusron Fiddin Faiza Renaldi Faiza Renaldi, Faiza Fajri Rakhmat Umbara Farhan Fadilah Farid Purwanto Ferdi Zulkarnain Ferry Kurniawan Fitra Arifiansyah Galih Rakasiwi Gunawan Abdillah Gunawan Abdillah Gunawan Abdillah Gunawan Abdillah, Gunawan Hadiana, Asep Id Hadimas Aprilian, Doni Hafiz, Aliy Handayani, Indah Nursyamsi Hanif Abdul Aziz, Nabil Hardianto, Mohamad Aris Hartono, Rudi Ifo Wahyu Pratama Ike - Festiana Iman Muhdi Inggit Sumirah Irvan Herdiansyah Iskandar Iskandar Julianto, Ribut Kania Ningsih, Ade Kartika N Oktaviani Kasyidi, Fatan Kresna Septyana Ekaputra Krishna Putra, Eddie Kuncoro Buwono Kurniawan Ikhsan Kurniawan, Alexander Tommy Kurniawan, Fadhlika Kusuma Wardany M.Naufal Rafirhan Mandala, Muhamad Bintang Maulina, Ninda Melina Melina Mia Narulita Anggraeni Mohamad Aris Hardianto Muhammad Aditya Putra Muhammad Dwi Laksono Muhammad Iqbal Zulfikar Mulyasari, Cicik Rafka Muthoharoh, Luluk Nasy`an Taufiq Al Ghifari Nendra Cahya Permana Neni Nuraeni Nenza Nurfirmansyah Nisa, Khoirotun Novianti, Sri Hutamy Nuari Anisa Sivi Nugraha, Faisal Okta Nugraha, Faisal Okta Nugraha, Mochammad Ganjar Nur Muhammad Hasyim Nurhakim, Riri Qorib Nurputra, Windi Raihan Nurul Sabrina, Puspita Oki Iskandar Oryza Habibie Rahman P., Tacbir Hendro Pamungkas, Muhammad Putra Poppi Lodaya Pradana, Muhammad Rifqi Pramudjianto, Imam Wibowo Prima Nugraha Ramdani, Rahmat Muhamad Rasyid Ibnu Prasetyo Rezki Yuniarti Rezky Yuniarti Ridwan Ilyas Rifky Ekayama Rikarda, Willy Artanika Rikarda1, Willy Artanika Rizki Abdilah Rizkyawan, Ferdi Rozak Arief Pratama Sari, Reni Permata Sari, Wiwin Rita Sartika Dewi Selia Aysiah Septia Wahyuni Setyawati, Astri Sivi, Nuari Anisa Sopwatun Anisa Sri Hutamy Novianti Susana, Ernia Tacbir Hendro Pudjiantoro Vita Nurdinawati Wahidah, Nina Ikhwati Wahyu Eko Zulianto Wardani, Mathilda Fitri Wina Witanti Wina Witanti Wini Afrilia Wirajaya Putra, Basudewa Yajid Ichsan Syifa Yanuar, Muhammad Rizki Yulison H. Crisnanto Yulison Herry Chrisnanto