Articles
<![CDATA[PENGEMBANGAN APLIKASI ANDROID "HITUNG CEPAT MATEMATIKA" ]]>
<![CDATA[Moh Syadidul Itqan]]>;
<![CDATA[Wahab Syaroni]]>;
<![CDATA[Abu Tholib]]>
<![CDATA[ NJCA (Nusantara Journal of Computers and Its Applications) Vol 3, No 2 (2018): Desember 2018 ]]>
Publisher : <![CDATA[Computer Society of Nahdlatul Ulama (CSNU) Indonesia ]]>
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DOI: 10.36564/njca.v3i2.77
<![CDATA[Pengembangan aplikasi android dalam penelitian ini untuk menjadi media belajar hitung cepat matematika bagi siswa sekolah mengah atas. Salah satu media pembelajaran yang banyak digunakan saat ini adalah aplikasi android. Alasan menggunakan aplikasi android sebagai media pembelajaran merupakan tuntutan dari revolusi industry 4.0 dalam segala bidang termasuk pendidikan. Android adalah sebuah system operasi untuk perangkat mobile berbasis linux yang mencakup system operasi, middleware dan aplikasi. Android menyediakan platform terbuka bagi para pengembang untuk menciptakan aplikasi mereka[1]. Hasil observasi pada siswa Sekolah Menengah Atas (SMA) Nurul Jadid diperoleh fakta bahwa 20 siswa dari 26 siswa merasa tidak menyukai matematika karena prosedur pemecahan masalahnya rumit dan membutuhkan waktu yang lama. Metode penelitian yang digunakan adalah metode Research and Development (R & D), dikarenakan penelitian ini mengembangkan aplikasi android.Model pengembangan system yang digunakan adalah model waterfall (air terjun). Hasil penelitian ini adalah telah dihasilkan aplikasi android hitung cepat matematika sebagai media belajar siswa sekolah menengah atas. Kata Kunci: Android, Hitung, Matematika.]]>
<![CDATA[ANALISIS PREDIKSI HARGA RUMAH DI JABODETABEK MENGGUNAKAN MULTIPLE LINEAR REGRESSION ]]>
<![CDATA[Inayatul Maula]]>;
<![CDATA[Linda Uswatun Hasanah]]>;
<![CDATA[Abu Tholib]]>
<![CDATA[ Jurnal Informatika Kaputama (JIK) Vol 7 No 2 (2023): Volume 7, Nomor 2, Juli 2023 ]]>
Publisher : <![CDATA[STMIK KAPUTAMA ]]>
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DOI: 10.59697/jik.v7i2.135
<![CDATA[The economic and infrastructure development in the Jabodetabek area has increased the rate of population growth in the region continues to increase. This attracted the attention of property agents in the housing price competition in the area, considering that the demand for housing will also continue to increase. There are several kinds of specificities and house prices in the Jabodetabek area, so an appropriate analysis is needed to get the desired house in this study the researcher implements the Multiple Linear method Regression to predict house prices with the desired specifications. This study used a total dataset of 3553 data with 11 variables obtained from the Kaggle.com. website The data will be through the pre-pronce process of data before training the model. Furthermore, at the evaluation stage using a test matrix, namely CC (Coefficient of Correlation), MAE (Met Absolute Error), RMSE (Root Met Square Error) is used to assess the performance of the model. Based on the results of the analysis from the dataset were 965 data, where the data was divided into two parts, namely, 80% as training data and 20% as testing data from the analysis results were obtained at an accuracy rate of 0.85 or 85% with an error rate of MAE of 375428909.51 and the RMSE level of 516385,50. ]]>
<![CDATA[PREDIKSI HARGA EMAS MENGGUNAKAN METODE LSTM DAN GRU ]]>
<![CDATA[Abu Tholib]]>;
<![CDATA[Nanda Kurnia Agusmawati]]>;
<![CDATA[Fitwatul Khoiriyah]]>
<![CDATA[ Jurnal Informatika dan Teknik Elektro Terapan Vol 11, No 3 (2023) ]]>
Publisher : <![CDATA[Universitas Lampung ]]>
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DOI: 10.23960/jitet.v11i3.3250
<![CDATA[Prediksi harga emas sangat penting karena menjadi acuan bagi para investor untuk menentukan strategi yang tepat dalam berinvestasi. Tren metode prediksi dalam beberapa tahun terakhir adalah deep learning, yang merupakan subbidang machine learning dan populer dalam menangani masalah prediksi time-series. Dalam penelitian ini, kami membandingkan performa dua model deep learning, yaitu Long Short-Tern Memory (LSTM) dan Gated Recurrent Unit (GRU) dalam memprediksi harga Emas. Hasil dalam penelitian ini menunjukkan bahwa model LSTM memiliki performa lebih baik dibanding model GRU dalam memprediksi harga Emas, dengan hasil perhitungan nilai eror LSTM lebih rendah yaitu nilai MAE sebesar 0.0389, RMSE sebesar 0.0475, dan MAPE sebesar 5.2047%. Dari hasil penelitian ini, kami menemukan bahwa LSTM adalah model yang lebih efektif dan akurat untuk memprediksi harga Emas dibanding LSTM.]]>
<![CDATA[Comparison of C4.5 and Naive Bayes for Predicting Student Graduation Using Machine Learning Algorithms ]]>
<![CDATA[Abu Tholib]]>;
<![CDATA[M Noer Fadli Hidayat]]>;
<![CDATA[Supri yono]]>;
<![CDATA[Resty Wulanningrum]]>;
<![CDATA[Erna Daniati]]>
<![CDATA[ International Journal of Engineering and Computer Science Applications (IJECSA) Vol 2 No 2 (2023): September 2023 ]]>
Publisher : <![CDATA[Universitas Bumigora Mataram-Lombok ]]>
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DOI: 10.30812/ijecsa.v2i2.3364
<![CDATA[Student graduation is a very important element for universities because it relates to college accreditation assessment. One of them is at the Faculty of Engineering Nurul Jadid University, which has problems completing the study period within a predetermined time. So that it can be detrimental because accreditation is less than optimal, and the number of active students makes it less ideal in teaching and learning activities. This study aimed to compare the level of accuracy using the C4.5 algorithm and Naïve Bayes method in predicting graduation on time. The C4.5 and Naïve Bayes algorithms are one of the methods in the algorithm for classifying. Tests were carried out using the C4.5 and Naïve Bayes algorithms using Google Colab with Python programming language, then validated using 10-fold cross-validation. The results of this study indicate that the Naïve Bayes method has a higher accuracy value with an accuracy rate of 96.12%, while the C4.5 algorithm method is 93.82%.]]>
<![CDATA[PREDIKSI HARGA EMAS MENGGUNAKAN METODE LSTM DAN GRU ]]>
<![CDATA[Abu Tholib]]>;
<![CDATA[Nanda Kurnia Agusmawati]]>;
<![CDATA[Fitwatul Khoiriyah]]>
<![CDATA[ Jurnal Informatika dan Teknik Elektro Terapan Vol 11, No 3 (2023) ]]>
Publisher : <![CDATA[Universitas Lampung ]]>
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DOI: 10.23960/jitet.v11i3.3250
<![CDATA[Prediksi harga emas sangat penting karena menjadi acuan bagi para investor untuk menentukan strategi yang tepat dalam berinvestasi. Tren metode prediksi dalam beberapa tahun terakhir adalah deep learning, yang merupakan subbidang machine learning dan populer dalam menangani masalah prediksi time-series. Dalam penelitian ini, kami membandingkan performa dua model deep learning, yaitu Long Short-Tern Memory (LSTM) dan Gated Recurrent Unit (GRU) dalam memprediksi harga Emas. Hasil dalam penelitian ini menunjukkan bahwa model LSTM memiliki performa lebih baik dibanding model GRU dalam memprediksi harga Emas, dengan hasil perhitungan nilai eror LSTM lebih rendah yaitu nilai MAE sebesar 0.0389, RMSE sebesar 0.0475, dan MAPE sebesar 5.2047%. Dari hasil penelitian ini, kami menemukan bahwa LSTM adalah model yang lebih efektif dan akurat untuk memprediksi harga Emas dibanding LSTM.]]>
<![CDATA[GAME EDUKASI MATEMATIKA UNTUK MENINGKATKAN PENALARAN SISWA BERBASIS ANDROID ]]>
<![CDATA[Tholib, Abu]]>;
<![CDATA[Eliyanto, Andik Elfandiyono]]>;
<![CDATA[Supriadi, Ahmad]]>;
<![CDATA[Syafiih, M]]>;
<![CDATA[Rahman, M Fadhilur]]>;
<![CDATA[Halimi, Ahmad]]>
<![CDATA[ Insand Comtech : Information Science and Computer Technology Journal Vol 9, No 1 (2024): Insand Comtech ]]>
Publisher : <![CDATA[Universitas Madura ]]>
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DOI: 10.53712/jic.v9i1.2297
<![CDATA[One of the subjects taught at every level of education is mathematics. Mathematics is an absolute science that cannot be revised but student interest in mathematics is declining because mathematics is considered a difficult subject for students and the media used is only books so that students get bored in learning. A new innovation is needed to increase student interest by utilizing technology, namely mathematics educational games. Educational games aim to increase students' interest as well as make learning fun by playing while learning. The research method used is the ADDIE Model, namely Analysis, Design, Development, Implementation and Evaluation. The result of this study is the Math Education Game on Android-Based Comparison Material based on the results of the blackbox test, it was found that all functions in the game ran according to the expected results and the assessment with a Likert scale to students obtained a score of 85.7% with a very agreeable interpretation. Thus, it can be concluded that this Android-based math educational game application is suitable for use by students as an independent learning medium and can help increase student interest in learning]]>
<![CDATA[Classification of Final Project Titles Using Bidirectional Long Short Term Memory at the Faculty of Engineering Nurul Jadid University ]]>
<![CDATA[Warda, Faridatul]]>;
<![CDATA[Fajri, Fathorazi Nur]]>;
<![CDATA[Tholib, Abu]]>
<![CDATA[ Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 3 (2023): NOVEMBER ]]>
Publisher : <![CDATA[ISB Atma Luhur ]]>
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DOI: 10.32736/sisfokom.v12i3.1723
<![CDATA[Every year, the Faculty of Engineering at Nurul Jadid University forms a committee to manage the process of students' final projects from the title selection stage to the final examination process until graduation. The process of selecting the final project title is still done manually, namely by checking the titles one by one, which takes a long time and allows errors because there is a lot of data to check, so human errors can also occur. Therefore, this research proposes to use the Bidirectional Long Short Term Memory (BiLSTM) method to classify the final project title based on its grade category. Several experiments were conducted to generate the most appropriate labels. The first experiment produced 4 labels and the second experiment produced 2 labels. From the results of several experiments, it was concluded that the second experiment had the best accuracy results with the 'good enough' and 'good' classes. The oversampling technique was then applied to overcome overlapping data, and the turning process was then performed on several parameters that could re-optimize the previous accuracy result of 75.24% to 91.15%. With a configuration of 10 random state parameters, using 64 batch sizes and 50 epochs. In addition, model adjustments were made to the hidden layer by adding a dropout layer and relu activation.]]>
<![CDATA[Aplikasi Inventaris Sekolah Berbasis Web menggunakan Framework Django di MTs. Nurul Hidayah Sumberrejo Paiton ]]>
<![CDATA[Tholib, Abu]]>;
<![CDATA[Fauziah, Gustin]]>
<![CDATA[ COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Vol 3, No 1 (2022): Pengembangan Aplikasi Berbasis Mobile untuk Layanan Publik: Studi Implementasi d ]]>
Publisher : <![CDATA[Universitas Nurul Jadid ]]>
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DOI: 10.33650/coreai.v3i1.4211
<![CDATA[Inventaris merupakan suatu kegiatan pencatatan, pelaporan serta pengolahan data-data barang yang tersedia di sekolah. Beberapa instansi pendidikan di Indonesia belum memiliki sistem yang menyediakan informasi inventaris sekolah. Padahal pengelolaan inventaris yang baik sangat penting bagi kelancaran sarana dan prasarana sekolah. Proses inventarisasi di MTs. Nurul Hidayah Sumberrejo Paiton masih dilakukan secara konvensional yaitu dengan mencatat ke buku inventaris kemudian data diinputkan ke dalam Microsoft Excel. Hal ini membutuhkan waktu yang cukup lama dalam pembuatan laporan inventaris serta mempersulit proses pencarian data barang tertentu. Berdasarkan permasalahan diatas maka dibuat sebuah aplikasi inventaris sekolah berbasis web menggunakan framework django dengan memanfaatkan teknologi QR Code dengan menggunakan bahasa pemrograman Python yang dapat memudahkan karyawan tata usaha dalam melakukan proses inventarisasi dan menyediakan informasi sesuai kebutuhan. Hasil penelitian adalah sebuah Aplikasi Inventaris Sekolah Berbasis Web Menggunakan Framework Django yang dapat digunakan untuk mempercepat proses inventarisasi serta membantu petugas dalam penyusunan laporan. Hasil pengujian aplikasi dengan responden sebagai user bahwa aplikasi inventaris sekolah berbasis web menunjukkan persentase pada pertanyaan 1 yaitu sebesar 70% (Setuju), pertanyaan 2 sebesar 75% (Sangat Setuju), pertanyaan 3 sebesar 75% (Sangat Setuju), pertanyaan 4 sebesar 70% (Setuju), pertanyaan 5 sebesar 70% (Setuju), dan pertanyaan 6 sebesar 75% (Sangat Setuju). Rata-rata hasil pengujian dengan responden sebesar 72,5% yang memiliki arti bahwa aplikasi ini sangat baik dan responden sangat setuju untuk menggunakan aplikasi.]]>
<![CDATA[OPTIMASI KEAMANAN DATA PENERIMAAN MAHASISWA MENGGUNAKAN AES-256, SHA-256, DAN BASE64 ]]>
<![CDATA[Ahmad Halimi]]>;
<![CDATA[Abu Tholib]]>;
<![CDATA[Moh. Ainol Yaqin]]>
<![CDATA[ JUSTIFY : Jurnal Sistem Informasi Ibrahimy Vol. 3 No. 1 (2024): JUSTIFY : Jurnal Sistem Informasi Ibrahimy ]]>
Publisher : <![CDATA[Fakultas Sains dan Teknologi, Universitas Ibrahimy ]]>
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DOI: 10.35316/justify.v3i1.5107
<![CDATA[In this era of extraordinary information technology, data security is a priority, especially the process of admitting new students (PMB) to tertiary institutions. This process involves collecting sensitive personal data from thousands of prospective students each year. To protect this data, this research applies 256-bit Advanced Encryption Standard (AES), Secure Hash Algorithm 256 (SHA-256), and Base64 encryption methods. AES-256-CBC is known to be effective in maintaining data security with a high level of security. SHA-256 enhances security further by generating a unique hash that verifies data integrity. Meanwhile, Base64 converts binary data into a more manageable text format. This research also includes testing encryption and verification speed using the Laravel framework. The application of this method is expected to increase trust and meet strict data security standards in the PMB information system, guarantee comprehensive data protection and improve system integrity.]]>
<![CDATA[KLASIFIKASI DATA MINING DI TINGKAT KEPUASAN MAHASISWA TERHADAP PELAYANAN SISTEM INFORMASI FAKULTAS TEKNIK UNIVERSITAS NURUL JADID ]]>
<![CDATA[Zain, Ahmad Naufal Waliyus]]>;
<![CDATA[Muafi, Muafi]]>;
<![CDATA[Tholib, Abu]]>
<![CDATA[ SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 2 (2024): Jurnal SKANIKA Juli 2024 ]]>
Publisher : <![CDATA[Universitas Budi Luhur ]]>
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DOI: 10.36080/skanika.v7i2.3200
<![CDATA[This research aims to assess impacts of information system services on student satisfaction to prevent dissatisfaction with campus information services. Students become active members of the academic community at higher education, are the center point of this investigation. Because the measurement of student satisfaction level on information services at the Faculty of Engineering is still unknown. By measuring student satisfaction, the faculty can improve the quality of service information system. The importance of campus information system services cannot be overstated because it serves as the main center for information management in higher education. in higher education. By using the Naïve Bayes Algorithm for the method used in this research utilizes simplicity and ease of application. its application. Data was collected through a questionnaire technique filled out by students of faculty of Engineering. The questionnaire contains about the quality of information systems and information service quality. A total of 316 student datasets were collected from 3 study programs in the Faculty of Engineering namely informatics, electrical engineering, and information technology study programs. Testing using naïve Bayes algorithm accuracy value of 94%, precision of 92% recall of 95%, and f1-score of 93%. It is hoped that this research can play an important role in improving the existing information system services to increase effectiveness. information system services to increase effectiveness.]]>
