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All Journal Jurnal Informatika dan Teknik Elektro Terapan Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Applied Data Sciences Instal : Jurnal Komputer Jurnal Minfo Polgan (JMP) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS)
Sarif, Muhammad Irfan
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Library & Information Science Mathematics Social Sciences

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Implementation of Recommendation Systems in Determining Learning Strategies Using the Naïve Bayes Classifier Algorithm Saleh, Amir; Dharshinni, NP; Perangin-Angin, Despaleri; Azmi, Fadhillah; Sarif, Muhammad Irfan
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.11954

Abstract

Recommendation systems are widely used in various fields of life to provide suggestions for a product, service, or piece of information to someone where there is an object to choose from. The recommendation system can also be applied in the field of education, especially in improving the quality of learning that occurs in schools. In this study, developing and implementing a recommendation system was used to determine the learning strategy applied in class. The system is very necessary in order to obtain effective and efficient learning in accordance with the desired learning style of students. In addition, learning that leads to students' desire to learn can make it easier for teachers to achieve predetermined learning goals. In this study, collaborative filtering techniques based on the Naive Bayes algorithm were used to determine the learning strategy. Before carrying out the recommendation process, datasets will be collected first, which are obtained from student responses through the questionnaires provided. This data will be used as training data to obtain recommendations on learning strategies that will be applied by the teacher in the classroom. After the training data is collected, the teacher will provide a response, and the results obtained will be used as testing data. From the results of implementing a recommendation system that has been built using the Naïve Bayes algorithm, the accuracy obtained is 90.91% in determining learning strategies that are appropriate to student learning styles.
Predicting the Feasibility of Providing Loans to Customers Using the Decision Tree Classification Algorithm, case study of the Maju Mandiri Savings and Loans Cooperative Syahputra, Muhammad Faisal; Sarif, Muhammad Irfan; Suherman
Bahasa Indonesia Vol 16 No 03 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i03.246

Abstract

Savings and loan cooperatives play an important role in providing financial access for the community. One of the main challenges faced is determining a customer's eligibility to receive a loan. This research aims to apply the Decision Tree classification algorithm in predicting the feasibility of providing loans to Maju Mandiri Savings and Loans Cooperative customers. The data used in this research includes various relevant financial variables. It is hoped that the findings of this research will help the Maju Mandiri Savings and Loans Cooperative in improving the efficiency and accuracy of the customer eligibility assessment process. In this way, cooperatives can reduce the risk of bad credit and improve the welfare of their members. This research also contributes to the academic literature by demonstrating the practical application of Decision Tree algorithms in the financial sector.
Application of Data Mining to analyze the Best Suppliers Haryanto, Hendrie; Sarif, Muhammad Irfan; Hardinata, Rio Septian
Bahasa Indonesia Vol 16 No 03 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i03.263

Abstract

This research explores the application of data mining methods with the Naive Bayes algorithm to analyze and determine the best suppliers in supply chain management. Optimal supplier selection plays an important role in increasing company efficiency and competitiveness. The aim of this research is to develop an analytical model that is not only accurate but also effective in evaluating supplier performance based on available historical data. The data used covers a variety of critical attributes, including price, product quality, delivery times, and contract compliance from several suppliers. The research process involves data preprocessing steps such as cleaning, normalization, and dividing the data into training and test sets. The Naive Bayes method is applied to identify patterns and relationships in data, as well as produce predictions regarding supplier performance. The model is evaluated using accuracy, precision, recall, and F1-score metrics to measure the reliability and accuracy of predictions. The analysis results show that the Naive Bayes method can predict supplier performance with a high level of accuracy and good consistency. These findings provide a valuable tool for companies in data-based decision making for better supplier selection. This research concludes that the Naive Bayes method is an excellent method for supplier performance analysis, offering a superior combination of accuracy and effectiveness. Recommendations for further research include the application of other data mining techniques and integration with supply chain management information systems to improve overall analysis results.
Internet Of Things Technology In Designing School Bell System Amin, Muhammad; Sarif, Muhammad Irfan; Zuriansyah, Alvin
Bahasa Indonesia Vol 16 No 02 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i02.292

Abstract

The application of Internet of Things (IoT) technology in school bell systems presents an automated, efficient, and integrated solution for managing bell schedules in real-time. The system is designed using IoT devices such as microcontrollers (Arduino or ESP32), wireless communication modules, and cloud platforms for data storage. Users can manage the bell schedule through a web- or app-based interface, enabling remote access and control. In addition, integration with sensors and smart devices allows the system to support operational flexibility, such as schedule adjustments based on specific conditions. This design offers operational efficiency, ease of management, as well as the ability to increase productivity in school environments through IoT technology automation.
E-KEDE APPLICATION DEVELOPMENT IN INCREASING UMKM SALES BASED ON SDLC Syahputra, Zulfahmi; Sarif, Muhammad Irfan; Ritonga, Ristra Sandra; Husniyyah, Ayu
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2284

Abstract

E-Kedai merupakan aplikasi bisnis online yang ditujukan untuk pengembangan UMKM. Dalam bentuknya yang paling jelas, E-Kedai menjual produk ke konsumen secara online. Sederhananya, E-commerce menciptakan, mengelola, dan memperluas hubungan komersial secara online. Dalam proses jual beli UMKM masyarakat Desa Klambir V datang langsung dan melihat barang yang ada di toko hanya bisa memilih secara manual, sehingga beberapa kali pelanggan merasa kecewa karena barang yang diinginkan tidak ada padahal pelanggan sudah ada. sudah ada di toko. Sehingga diperlukan inovasi penjualan secara online atau disebut dengan E-Kedai agar pelanggan dapat memilih barang dan melihat stok barang secara online, selain itu peneliti membuat E-Kedai dengan harapan dapat meningkatkan penjualan dan cakupan pembeli agar dapat dilihat oleh seluruh klambir. komunitas V. Hasil penelitian berupa suatu sistem yang diterapkan pada perancangan aplikasi berbasis website yang efisien dalam menjual produk dan dapat memberikan kemudahan bagi pelanggan, serta meningkatkan efisiensi usaha bagi UMKM masyarakat Desa Klambir V.
Design and Implementation of the Front-End E-Learning Website for the Banda Aceh Tekkomdik Laboratory Sari, Anisa Puspita; Sarif, Muhammad Irfan
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.129

Abstract

UPTD Balai TEKKOMDIK Banda Aceh itself is the Task Implementation Unit of the Banda Aceh City Education Service. The Center for Educational Technology and Communication (TEKKOMDIK) has tasks, one of which is developing information technology in Banda Aceh City education units in elementary and middle school environments. At UPTD TEKKOMDIK Hall there are several school services such as the E-Learning application. E-Learning Application Services are still less effective to use and are still not responsive. Therefore, in the design and implementation of the front-end E-learning website for UPTD Balai TEKKOMDIK Banda Aceh, it is necessary to develop an E-Learning application with display features that can make things easier and of course responsive. The development of the Front-End section aims to facilitate the teaching and learning display process, including displaying Admin features for user management such as teachers and students, classes, subjects, then there is also a display of features for students such as learning media, for example materials, assignments, and direct chat. Apart from the several display features that have been mentioned, there are also other display features such as display of school service features, school information, school profile, learning media and educational channels which are useful for providing information regarding assignments and materials.
Mathematical Modeling of Water Quality Dynamics in Aquaculture: A Foundation for IoT Integration and Machine Learning-Driven Predictive Analytics Sarif, Muhammad Irfan; Efendi, Syahril; Sihombing, Poltak; Mawengkang, Herman
Journal of Applied Data Sciences Vol 6, No 3: September 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i3.819

Abstract

Effective water quality management is paramount for sustainable aquaculture, yet conventional methods often fall short in providing timely and predictive insights. This paper details the development and analysis of a comprehensive suite of mathematical models designed to simulate key water quality dynamics in aquaculture systems. These models encompass critical biogeochemical processes, including the nitrogen cycle (ammonia, nitrite, nitrate, organic nitrogen), phosphorus cycle, Dissolved Oxygen (DO) balance, and Biochemical Oxygen Demand (BOD). Simulation results derived from these models illustrate the temporal evolution of these critical parameters, demonstrating their capability to capture complex interactions and provide a mechanistic understanding of the aquatic environment. This foundational modeling approach offers a robust tool for quantitative analysis and prediction of system responses under various conditions. The core contribution of this work is the articulation of these mathematical models, which serve as a crucial foundation for advanced, data-driven aquaculture management. To enhance their practical utility, we propose a conceptual framework for integrating these models with Internet of Things (IoT) sensor networks. Real-time data acquisition via IoT can be essential for model parameterization, continuous calibration, and validation against operational conditions. Furthermore, this paper discusses how outputs from these validated mechanistic models can serve as robust inputs for Machine Learning (ML) algorithms. This synergy enables the development of sophisticated predictive analytics for critical events, such as forecasting water quality deterioration, and supports optimized, proactive management strategies. This research lays the theoretical and methodological groundwork for developing more precise and resilient decision support systems in aquaculture. By emphasizing the synergistic potential of combining foundational mathematical modeling with data science techniques like IoT and ML, this work aims to contribute to transforming aquaculture into a more productive, sustainable, and environmentally responsible industry. Future efforts should focus on empirical validation and the practical implementation of the proposed integrated framework.
Sosialisasi Peran dan Peluang Karir dalam Bidang Ilmu Komputer Bagi Siswa Sekolah Menengah Amin, Muhammad; Badawi, Afif; Hariyanto, Eko; Sarif, Muhammad Irfan
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 4 No 1 (2025): Juli 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v4i1.484

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk memberikan wawasan kepada siswa sekolah menengah mengenai bidang-bidang dalam ilmu komputer serta peluang karir yang dapat ditempuh di masa depan. Latar belakang kegiatan ini didasarkan pada rendahnya pemahaman siswa terhadap ragam profesi di bidang teknologi informasi, padahal sektor ini semakin dibutuhkan di era revolusi industri 4.0 dan society 5.0. Metode pelaksanaan meliputi penyampaian materi secara interaktif melalui ceramah, diskusi, dan pemutaran video edukatif, serta didukung dengan media visual seperti slide dan modul. Strategi penyampaian difokuskan pada pendekatan edukatif dan komunikatif agar mudah dipahami siswa. Evaluasi dilakukan melalui observasi langsung dan kuisioner untuk menilai pemahaman serta antusiasme peserta. Hasil kegiatan menunjukkan tingginya ketertarikan dan pemahaman siswa terhadap bidang ilmu komputer, khususnya pada topik seperti pemrograman, kecerdasan buatan, dan desain aplikasi. Kegiatan ini dinilai berhasil membangun kesadaran akan pentingnya penguasaan teknologi informasi dan membuka peluang untuk kegiatan lanjutan yang lebih aplikatif di bidang literasi digital dan pengembangan karir teknologi.
Analisis Clustering Untuk Menentukan Siswa Berprestasi di SMK Swasta TI Panca Dharma Stungkit Menggunakan Metode K-Means Apriandi, Dicky; Sari, Rahayu Mayang; Sarif, Muhammad Irfan
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13959

Abstract

Pendidikan memiliki peran yang amat penting dalam masyarakat karena pendidikan merupakan upaya untuk memperbaiki taraf hidup manusia. Peningkatan mutu pendidikan merupakan prioritas kebijakan umum pembangunan di Indonesia yang harus terus diperhatikan. Faktor yang memiliki pengaruh besar dalam pencapaian tersebut adalah guru yang memberikan pengajaran efektif dan berkualitas. SMK TI Panca Dharma Stungkit yang beralamat di Jln. Kata Jadi Stungkit, Kecamatan Wampu, Kabupaten Langkat, Sumut. Penilaian prestasi siswa yaitu mata pelajaran baik teori dan praktek, penilaian ekstrakurikuler kehadiran dan ketidakhadiran siswa dan pada saat mengikuti ekstrakulikuler, yang dikategorikan dalam nilai pengetahuan, nilai keterampilan dan penilaan sikap. metode untuk mengolahnya menjadi sebuah informasi dan pengetahuan yang dapat digunakan sebagai bahan pertimbangan pendidik dalam proses pengambilan kebijakan dan keputusan yaitu dengan metode K-Means.
PERANCANGAN SISTEM MONITORING LEVEL AIR MENGGUNAKAN SENSOR ULTRASONIK BERBASIS IOT DENGAN APLIKASI BLYNK Hasanah, Annisa Putri; Sarif, Muhammad Irfan; Hafni, Hafni
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 2 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i2.6485

Abstract

Abstrak. Pemantauan dan pengendalian level air dalam tangki penyimpanan secara manual sering kali tidak efisien dan berisiko menyebabkan air yang terbuang sia sia. Oleh karna itu, penelitian ini mengembangkan sistem monitoring berbasis Internet of things menggunakan ESP32, sensor ultrasonik, dan relay, dengan aplikasi Blynk serrta Telegram sebagai media pemantauan dan notifikasi. Sistem ini memungkinkan pengguna untuk melihat level air secara real-time dan mengontrol pompa air secara otomatis atau manual melalui aplikasi.Pengujian sistem menunjukkan bahwa snesor ultrasonik memiliki akurasi tinggi dalam mendeteksi level air, sementara sistem kendali pompa berbasis relay bekerja dengan baik dalam mengisidan menghentikan aliran air sesuai dengan batas yang telah ditentukan. Dengan adanya sistem ini, pengguna dapat lebih mudah mengontrol ketersediaan air dan menghindari pemborosan.  Abstract. Manual monitoring and control of the water level in the storage tank is often inefficient and risks causing wasted water. Therefore, this research developed an Internet of things-based monitoring system using ESP32, ultrasonic sensors, and relays, with the Blynk application as Telegram as a monitoring and notification medium. The system allows users to view the water level in real-time and control the water pump automatically or manually through the app.System testing shows that ultrasonic sensor have high accuracy in detecting water levels, while relay-based pump control systems work well in filling and stopping the water flow according to predetermined limits. With this system, users can more easily control water availability and avoid waste.
Co-Authors Aminuddin Indra Permana Amir Saleh Apriandi, Dicky Badawi, Afif Dharshinni, NP Efendi, Syahril Eko Hariyanto Fadhillah Azmi, Fadhillah Hafni Hafni Hardinata, Rio Septian Haryanto, Hendrie Hasanah, Annisa Putri Herman Mawengkang Husniyyah, Ayu Muhammad Amin Nurfebia, Karina Perangin-angin, Despaleri Poltak Sihombing Rahayu Mayang Sari, Rahayu Mayang Ramadhani, Nuzul Aini Ritonga, Ristra Sandra Sari, Anisa Puspita Sinulingga, Nurbaiti Suherman Sulistia, Febri Yalda Syahputra, Muhammad Faisal Syahputra, Zulfahmi Zuriansyah, Alvin