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All Journal Jurnal Informatika Infotek : Jurnal Informatika dan Teknologi ABSYARA: Jurnal Pengabdian Pada Masyarakat Jurnal PRINTER : Jurnal Pengembangan Rekayasa Informatika dan Komputer Jurnal Teknologi Informasi untuk Masyarakat (Jurnal Teknokrat)
Nur, Amri Muliawan
Universitas Hamzanwadi
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Other

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Komparasi Algoritma Data Mining Dalam Ketuntasan Belajar Daring Siswa Pada Masa Pandemi Covid 19 Muhammad Saiful; hariman bahtiar; Amri Muliawan Nur; Yupi Kuspandi Putra
Infotek: Jurnal Informatika dan Teknologi Vol. 6 No. 2 (2023): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v6i2.14850

Abstract

This research was conducted at SMA Negri 3 Selong and became the focus of students in class XI IPA and Social Studies. The sampling technique used purposive sampling method. This study aims to describe the extent to which the level of completeness of students during post-covid-19 pandemic learning with online media. This study uses a classification algorithm that functions to find a model that distinguishes data classes or data concepts, with the specific objective of determining the class of unknown object labels. The method used is the PSO-based Naïve Bayes and Naïve Bayes Comparison Algorithms. The results of this study indicate that the use of online media during online learning using the naïve Bayes algorithm is 83.91%, and the PSO-based naïve Bayes algorithm is 91.98%, from the experimental results and testing of the two algorithms, the results of the confusion matrix and AUC testing can be obtained which can be determined the best accuracy value is the PSO-based Naïve Bayes algorithm. As for the comparison of the results in the form of an accuracy value obtained by the Naïve Bayes Algorithm of 83.91% and the PSO-Based Naïve Bayes Algorithm of 91.98% and the difference in the level of accuracy of 8.07%, so it can be concluded that the algorithm that is suitable for classifying student learning completeness during the covid 19 pandemic is Naive Bayes based on particle swarm optimization.
Rancang Bangun Sistem Informasi Geografis Pemetaan Wilayah Penderita Penyakit Stunting Amri Muliawan Nur; Fathurrahman Fathurrahman; Muhammad Saipul; Nila Sulastri Oktavia
Infotek: Jurnal Informatika dan Teknologi Vol. 6 No. 2 (2023): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v6i2.17484

Abstract

Stunting is a growth disorder in children and toddlers caused by lack of nutritional intake, so that children's height is stunted compared to children their age. Currently, stunting sufferers in West Sakra District can be said to be quite vulnerable. So it requires intensive treatment and attention quickly and precisely. In mapping the area of stunting sufferers in West Sakra District it is still manual so that in the process of searching for areas with stunting in West Sakra it takes a long time and tends to cause problems. Therefore, a study was conducted to create a geographic information system for mapping the areas of stunting sufferers in West Sakra District. The purpose of this system is to provide convenience and help the West Sakra District, especially the Rensing Health Center, which manages the data. The steps taken in making this system are system requirements analysis, system design, system creation, and system testing. And in making this system, using the PHP programming language and using MySQL as the database
Penerapan Algoritma K-Means Clustering Dalam Mengelompokkan Smartphone Yang Rekomendasi Berdasarkan Spesifikasi nur, amri muliawan; Saiful2, Muhammad; Bahtiar, Hariman; Muhammad Taufik Hidayat
Infotek: Jurnal Informatika dan Teknologi Vol. 7 No. 2 (2024): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v7i2.26283

Abstract

Various types of smartphones come with different prices and specifications, causing sellers to sometimes struggle with providing recommendations to consumers who want to buy a smartphone that meets their desired specifications and price range. This challenge arises because it is difficult for sellers to remember the specifications of each smartphone for sale. K-Means Clustering aims to group existing specification data into several clusters, where the data in each cluster share similar characteristics. By forming these smartphone groups, it becomes easier for sellers to recommend appropriate smartphones to customers. The research results show that various smartphone brands are categorized into three groups: the Recommended Group, which includes 225 items; the Most Recommended Group, which includes 98 items; and the Less Recommended Group, which includes 27 items. This clustering is expected to help sellers easily increase the stock of recommended smartphones according to consumer needs in terms of price and specifications.
Implementasi Data Mining Menggunakan Algoritma Naïve Bayes Untuk Klasifikasi Penyaluran Dana Zakat Muhammad Saiful; Amri Muliawan Nur; Aswian Editri Sutriandi; Eka Puspita; B. Nadila Nuzululnisa
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28624

Abstract

Zakat is one of the pillars in Islam that aims to reduce economic disparity and assist those in need. Effective distribution of zakat requires a system capable of accurately identifying and targeting mustahik (zakat recipients). This study aims to implement data mining techniques using the Naïve Bayes Algorithm for the classification of zakat fund distribution at the National Amil Zakat Agency (BAZNAS) in East Lombok Regency. The Naïve Bayes Algorithm was chosen for its ability to predict categories based on probability and historical data. The data used is private data obtained through the financial reports of BAZNAS East Lombok Regency for the years 2022-2023, with 461 mustahik including family members, income, and economic status. There are 8 attributes used in this study. Data processing is conducted using RapidMiner software with the Naïve Bayes algorithm. The results show that the Naïve Bayes Algorithm achieved the best accuracy rate from the 3-fold validation test, amounting to 99.57% with an AUC value of 0.997%. The tests conducted provided excellent classification results. With this comprehensive and data-driven approach, it is hoped that this study can provide effective solutions to the current zakat fund distribution issues
Implementasi Algoritma K-Means Clustering Dalam Mengelompokkan Kepatuhan Wajib Pajak Bumi dan Bangunan Dengan Optimasi Elbow Nur, Amri Muliawan; Hariman Bahtiar; Mila Agustiarini Jannah
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28644

Abstract

Land and Building Tax (Pajak Bumi dan Bangunan, or PBB) is one of the primary sources of regional revenue that plays a significant role in supporting development across various regions. Therefore, efforts to improve tax compliance must be enhanced through various strategies, such as continuous socialization and education, to raise awareness of the importance of paying taxes. Additionally, improving the quality of services is essential. This study aims to classify the compliance levels of PBB taxpayers in Sakra District using the K-Means Clustering algorithm. The data used in this research is the 2023 PBB dataset for Sakra District, comprising 376 entries and involving five key attributes: land area, building area, PBB assessment, payment status, and penalties. The results obtained from processing using the K-Means algorithm indicate an optimal number of clusters, as follows: Cluster 1 represents a high compliance level, consisting of 355 items; Cluster 2 represents a moderate compliance level, consisting of 18 items; and Cluster 3 represents a low compliance level, consisting of 3 items. These clustering outcomes can serve as a reference for authorities in formulating more targeted strategies to enhance tax compliance through improved education and services in the future.
Implementasi Algoritma K-Means Untuk Klasterisasi Peserta Keluarga Berencana Berdasarkan Tingkat Risiko Kehamilan di Desa Pringgasela Selatan Hidayat, Andrian; Nurhidayati, Nurhidayati; Nur, Amri Muliawan
Jurnal PRINTER: Jurnal Pengembangan Rekayasa Informatika dan Komputer Vol. 1 No. 2 (2023): Jurnal PRINTER: Jurnal Pengembangan Rekayasa Informatika dan Komputer
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jprinter.v1i2.23598

Abstract

Program Keluarga Berencana (KB) merupakan sebuah program yang bertujuan untuk mengendalikan angkapertumbuhan populasi penduduk, meningkatkan kesejahteraan keluarga, dan upaya mencegah risiko kesehatanpada ibu dan anak. Salah satu tantangan dalam program KB adalah proses identifikasi dan pelayanan yangmaksimal terhadap peserta KB yang berisiko mengalami kehamilan dengan risiko tinggi yang dapatdiidentifikasi berdasarkan faktor 4T yaitu Terlalu Muda, Terlalu Tua, Terlalu Banyak, Terlalu Dekat.Penelitian ini bertujuan untuk melakukan klasterisasi pada peserta KB berdasarkan tingkat risiko kehamilansehingga diperoleh informasi terkait kondisi peserta KB sebagai landasan penyuluhan terkait risiko kehamilantingkat tinggi dan perancangan program yang sesuai dan tepat sasaran bagi peserta KB. Penelitian inidilaksanakan di Desa Pringgasela Selatan memanfaatkan data mining menggunakan Algoritma K-MeansClustering pada 400 data peserta KB untuk membentuk kelompok atau klaster peserta KB berdasarkan tingkatrisiko kehamilannya dengan atribut berupa Nama, Usia, Jumlah Anak, dan Usia Anak Terakhir. Hasil yangdiperoleh yaitu terbentuk 2 (dua) cluster dengan Cluster 1 sebagai kelompok kehamilan berisiko tinggi dengan170 item anggota dan Cluster 0 sebagai kelompok kehamilan berisiko rendah dengan 230 item anggota.Kata Kunci : K-Means Clustering, Keluarga Berencana, Risiko Kehamilan
Pendampingan Pembuatan Sistem Informasi Sekolah Berbasis Web di SDN 1 Montong Baan Zamroni; Amri Muliawan Nur; Ida Wahidah; Azrul Hidayat; M. Wahyudi Rahmatul Qodri
Jurnal Teknologi Informasi untuk Masyarakat Vol. 3 No. 1 (2025): Jurnal Teknologi Informasi untuk Masyarakat (Teknokrat)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jt.v3i1.28803

Abstract

Effective school information management is one of the important aspects in improving the quality of educational services. However, at SDN 1 Montong Baan, the information management process is still done manually, such as through announcements on information boards or direct communication with students' parents. This has caused several obstacles, such as delayed information, data inaccuracies, and limited access for the community. To address these challenges, a web-based school information system was developed with the aim of improving the efficiency and accuracy of school information management. This system is equipped with key features, such as a home page, school profile page, school program page, news & activities page, school facilities page, school achievements page, and new student registration page. The development of this system uses the Waterfall method, which includes the stages of requirement, design, implementation, verification, and maintenance. The development process begins with needs identification, system design, system construction, and ends with training and system testing with teachers and school staff. The implementation results show that this system successfully facilitates information management in a faster, more accurate, and structured manner. Users such as teachers, school staff, and parents of students provided positive feedback regarding the ease of access and reliability of the system. The success of this implementation is expected to serve as a model for web-based school information management for other schools, especially in rural areas
Pelatihan Teknologi Informasi Untuk Meningkatkan Kompetensi Siswa Di SMAN 1 Sakra Timur Deni Hanapi; Diki Setiawan Jodi; Baiq Andriska Candra Permana; Amri Muliawan Nur; Moh. Farid Wajdi
Jurnal Teknologi Informasi untuk Masyarakat Vol. 3 No. 1 (2025): Jurnal Teknologi Informasi untuk Masyarakat (Teknokrat)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jt.v3i1.29236

Abstract

The use of information technology in education, especially in rural areas, is crucial for improving students' skills. This study aims to enhance the skills of SMAN 1 Sakra Timur students in operating Microsoft Office applications through intensive training focused on hands-on practice. The program lasts for 18 days, involving 15 students with a participatory method and step-by-step evaluation. The training material covers an introduction to basic to advanced features of Microsoft Word, Excel, and PowerPoint. Evaluation is carried out using pre-tests and post-tests, showing an increase in the average score from 45 to 85 percent. Students also provide positive feedback and appreciate the interactive approach used. The results of this training demonstrate that a practice-based approach is highly effective in improving the digital competencies of students at SMAN 1 Sakra Timur. This program is expected to inspire other schools to adopt similar training, enabling students to better face the challenges of the digital era and prepare for an increasingly competitive world of work and education.
Penerapan Metode Naïve Bayes Untuk Penentuan Penerima Beasiswa Program Indonesia Pintar (PIP). Nur, Amri Muliawan; Nurhidayati, Nurhidayati; Fathurrahman, Imam
Infotek: Jurnal Informatika dan Teknologi Vol. 7 No. 1 (2024): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v7i1.23995

Abstract

PIP is the provision of educational cash assistance to school-aged children from underprivileged families who are marked with a smart Indonesia card (KIP). The purpose of this research is to determine the performance of the Naïve Bayes method in classifying data on students who are eligible and who are not eligible to receive a PIP scholarship at SMAN 1 Sukamulia, because this school is still experiencing problems in the decision-making process for determining potential PIP scholarship recipients, because there are no a system that can assist in processing student data that is eligible and not eligible to get the PIP scholarship. Therefore, for data processing, researchers tried to implement a new system with the Data Mining concept using the Naïve Bayes method, by carrying out 9 tests using Cross Validation starting from K-Fold Validation 2 to 10, obtaining the highest accuracy results in the 9th test. using K-Fold Validation 10 which is equal to 92.81%. Also obtained was an Area Under Curve (AUC) value of 0.973%, where AUC is a parameter used in classification analysis to determine the best model for predicting a class or attribute. AUC itself has a value range of 0-1, which means that the closer the AUC value is to 1, the better the prediction or diagnosis of the attribute
Pelatihan dan Pendampingan Penulisan Karya Ilmiah Bagi Guru dan Staff di SMK Nahdlatul Wathan Diniyah Islamiah Korleko Yahya, Yahya; Bahtiar, Hariman; Nur, Amri Muliawan; Sadali, Muhamad; Putra, Yupi Kuspandi; Fathurrahman, Fathurrahman; Sutriandi, Aswian Editri; Nurhidayati, Nurhidayati; Samsu, L. Muh.; Saiful, Muhammad
Jurnal Teknologi Informasi untuk Masyarakat Vol. 1 No. 2 (2023): Jurnal Teknologi Informasi untuk Masyarakat (Teknokrat)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jt.v1i2.24711

Abstract

Nahdlatul Wathan Diniyah Islamiah Korleko Vocational High School is one of the Vocational High Schools under the Hamzanwadi Education Foundation Darunnahdlatain Nahdlatul Wathan Diniyah Islamiah Pancor Islamic Boarding School. This school was founded to meet the demands and needs of the community, especially in the Labuhan Haji District area. NWDI Korleko Vocational School has 2 departments, namely the Department of Computer and Network Engineering (TKJ) and the Department of Multimedia. NWDI Korleko Vocational School is guided by many teaching staff who have various scientific disciplines. Even productive teachers are taught by teachers who have scientific disciplines that are very different from the competencies that must be taught. Starting from the diversity of scientific disciplines of teachers which greatly influences the competence of their students. The diversity of scientific disciplines is what creates non-uniformity in information technology knowledge, especially in the field of writing scientific papers. There are those who understand and there are those who don't understand at all. That is what causes the desire to help understand techniques and how to apply information technology in writing scientific papers. From the initial test analysis in information technology knowledge, the average teaching staff at NWDI Korleko Vocational School understands around 40% to 50% of scientific writing. After training and mentoring, there was a significant increase in the writing and application of information technology in writing scientific papers, reaching 80% to 90%, 10% of whom did not understand, which was because during the training and mentoring, the teaching staff had a high level of attendance. less than 70%. Thus, there needs to be ongoing training and mentoring so that teaching staff can understand everything
Co-Authors AA Sudharmawan, AA Ahmad Firdaus, Ahmad Almi Yulistia Alwanda Amir Bagja ANDRIAN HIDAYAT Aris Sudianto Aswian Editri Aswian Editri Sutriandi Azrul Hidayat B. Nadila Nuzululnisa Bahtiar, Hariman Baiq Andriska Candra Permana Baiq Ayu Indah Wardaningsih Bambang Harianto Deni Hanapi Diki Setiawan Jodi Eka Puspita Fathurahman Fathurahman Fathurrahman Fathurrahman Fathurrahman Fathurrahman, Imam Hadian Mandala Putra Hanny Hafiar Harianto, Bambang Ida Wahidah Imam Fathurrahman Julaini Juniarta, Adrian L M Samsu L M Samsu L.M.Samsu M. Wahyudi Rahmatul Qodri Maedani, Muhaffivin Mahpuz, Mr. Mahpuz Mila Agustiarini Jannah Moh. Farid Wajdi Muh. Adrian Juniarta Hidayat Muhammad Fauzi Zulkarnaen Muhammad Saipul Muhammad Taufik Hidayat Muhammad, Saiful Nila Sulastri Oktavia Nurhidayati Nurhidayati Nurhidayati nurhidayati, nur ida Ramli Ahmad Rodiah, Rodhiah Filkhair Sadali, Muhamad Saiful2, Muhammad Salmiah Salmiah Samsu, L. Muh. Suhartini Suhartini, Suhartini Sutriandi, Aswian Editri Tiara Febrianti Yahya Yahya Yahya Yahya, Yahya Yupi Kuspandi Putra Zainul Hadi Zamroni