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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) CESS (Journal of Computer Engineering, System and Science) Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknologi Sistem Informasi dan Aplikasi JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Information Systems and Informatics JTIK (Jurnal Teknik Informatika Kaputama) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Applied Science, Engineering, Technology, and Education Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Syntax: Journal of Software Engineering, Computer Science and Information Technology Jurnal IPTEK Bagi Masyarakat Journal of Computer Science and Informatics Engineering Edu Society: Jurnal Pendidikan, Ilmu Sosial dan Pengabdian Kepada Masyarakat
Fakhriza, M.
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering Physics Public Health Social Sciences Other

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Comparison of Naive Bayes Algorithms and Decision Tree for Classifying Hero Fighter Items in the Mobile Legends Hafidz, Hasbanur; Fakhriza, M.
Journal of Applied Science, Engineering, Technology, and Education Vol. 6 No. 2 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3519

Abstract

The classification of hero fighter items in the Mobile Legends Game is a significant challenge due to the complexity of features and the variety of strategies employed by players. This study aims to develop an effective classification model using the Naïve Bayes and Decision Tree algorithms and compare the performance of these two algorithms. The dataset used in this study was obtained from item recommendations during live Gameplay, community sources such as forums, and Game guides. This dataset contains relevant information to support the classification of items for hero fighters, such as hero attributes, roles, and enemy types. The model training process was conducted using the scikit-learn library, with data split into 80% for training and 20% for testing. The study results show that the Decision Tree algorithm consistently delivers better performance than Naïve Bayes. In the evaluation using accuracy metrics, Decision Tree achieved an accuracy rate of 84.78%, significantly higher than Naïve Bayes, which only reached 45.65%. Furthermore, the precision, recall, and f1-score metrics for Decision Tree also showed superior results for almost all classes compared to Naïve Bayes. Based on these findings, the Decision Tree algorithm is recommended as a more suitable choice for classifying hero fighter items in the Mobile Legends Game.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN PUPUK UNTUK TANAMAN HIAS MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING DAN MULTI ATTRIBUTE UTILITY THEORY Irawati, Cici; Zufria, Ilka; Fakhriza, M.
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 1 (2025): February 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i1.2708

Abstract

Abstract: Providing fertilizer that is not appropriate to soil conditions and plant needs will greatly affect plant growth, so this needs to be paid close attention and cannot be done haphazardly or excessively. Applying a combination of the SAW method and the MAUT method to produce a decision support system that can provide advice on determining the best type of organic fertilizer that can be given to ornamental plants. This research uses the Simple Additive Weight method which is used in selecting alternatives, then ranking them and getting the best alternative and using the Multi Attribute Utility Theory method to solve the problem by using a final evaluation scheme for an object or it can be said with a weight value which is added up with the relevant value of each utility. -his. Using the SAW method helps weight alternatives and criteria with a weight scale of 1-5, after weighting the alternatives, the ranking is then used using the MAUT method to get the final value, 1st place was obtained by Mutiara Pupuk NPK 16-16-1 with a final value of 0.815 and 20th place. obtained by ZPT Golstar 250 SC with a final value of 0.59, therefore Mutiara Pupuk NPK 16-16-1 is the best fertilizer for ornamental plant fertilizer.Keyword: Decision Making System, SAW, MAUT, Alternative Fertilizer Abstrak: Pemberian pupuk yang tidak sesuai dengan kondisi tanah dan kebutuhan tanaman akan sangat mempengaruhi pertumbuhan dari tanaman, sehingga hal ini perlu dicermati dan tidak bisa dilakukan secara sembarangan atau dilakukan secara berlebihan. Melakukan penerapan kombinasi dari metode SAW dan metode MAUT untuk menghasilkan sebuah sistem pendukung keputusan yang dapat memberikan saran untuk menentukan jenis pupuk organik terbaik yang dapat diberikan pada tanaman hias. Penelitian ini menggunakan metode Simple Additive Weigth yang digunakan dalam menyeleksi alternatif kemudian dilakukan perengkingan dan didapatkan alternatif terbaik dan menggunakan metode Multi Attribute Utility Theory untuk menyelesaikan permasalahan dengan menggunakan skema evaluasi akhir dari suatu objek atau dapat dikatakan dengan nilai bobot yang dijumlahkan dengan nilai relevan tiap utility-nya. Dengan menggunakan metode SAW membantu pembobotan alternatif dan kriteria dengan skala bobot 1–5, setelah dilakukan pembobotan alternatif selanjutnya perangkingan menggunakan metode MAUT untuk mendapatkan nilai akhir, rangking 1 didapatkan oleh Mutiara Pupuk NPK 16-16-1 dengan nilai akhir yaitu 0,815 dan ranking 20 didapatkan oleh ZPT Golstar 250 SC dengan nilai akhir yaitu 0,59, oleh karena itu Mutiara Pupuk NPK 16-16-1 merupakan pupuk terbaik untuk pupuk tanaman hias.Kata kunci: Sistem Pengambilan Keputusan, SAW, MAUT, Pupuk Alternatif
K-Means Clustering Untuk Mengukur Pengaruh Kompetensi Terhadap Kinerja Pegawai Syaqila, Saidatus; Fakhriza, M.
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6758

Abstract

Human resources play an important role in improving organizational performance, including in the North Sumatra Province Youth and Sports Agency (Dispora). This study aims to measure the effect of competence on employee performance using the K-Means Clustering algorithm, known as an unsupervised data clustering method. The dataset consists of 700 employee data with 15 attributes covering technical, managerial, and social competencies. Data were collected through direct surveys and processed using Python with a normalization process through the StandardScaler method to ensure data consistency. The elbow method was used to determine the optimal number of clusters, resulting in five clusters: best performance, very good, and average. The results of the analysis show that the clustering results group employees into five clusters, namely Cluster 0 with 145 employees who have high technical competence, Cluster 1 with 160 employees who excel in social and managerial competence, Cluster 2 with 125 employees who show average competence in all aspects, Cluster 3 with 135 employees who have moderate technical competence but excel in social competence, and Cluster 4 with 135 employees who have great potential for development. This research provides practical benefits in the form of identifying competency patterns for developing group-based training needs, as well as more objective strategic decision-making in human resource management. Thus, this research is expected to support improving employee performance through an effective data-based approach.
K-Nearest Neighbors (KNN) to Determine BBRI Stock Price Baihaqi, Abdullah Afif; Fakhriza, M.
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i2.5098

Abstract

Sales prediction is a calculation aimed at forecasting future conditions by analyzing past situations. The research method used in this study is the Research and Development (RnD) method. The modeling employs the K-Nearest Neighbor algorithm, utilizing data processed through the Knowledge Discovery in Database (KDD) stages. The objective of this research is to obtain a predictive model that can preprocess structured product data, enabling it to present a forecast for the public regarding the general overview of BBRI stock price determination, as well as to provide recommendations for BBRI stock prices that have been classified by the researcher using the K-Nearest Neighbor method. The results of the stock price prediction indicate fluctuations in value during the period, where the model is capable of capturing trends in stock price changes based on historical data. For example, on February 10, 2025, the stock price is predicted to be 4867.020, while on February 15, 2025, it rises to 5101.620. This demonstrates that the k-NN method can analyze stock price movement patterns by considering the nearest neighbors from previous data. The k-NN method has proven effective in studying historical data patterns and generating structured predictions.
Kombinasi AHP-TOPSIS Pada Pemilihan Varietas Unggul Jagung Hibrida Di Desa Pantoan Maju Hidayati, Lily; Fakhriza, M.; Putri, Raissa Amanda
JATISI Vol 12 No 1 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i1.9256

Abstract

The large number of varieties of hybrid corn seeds on the market and farmers' lack of understanding of the characteristics of each variety often make it difficult for farmers to make the right choice according to the conditions of their agricultural land. This is a major challenge for farmer groups in Hamlet III, Pantoan Maju Village, who experience difficulties in selecting superior hybrid corn seed varieties to increase agricultural productivity. To overcome this problem, a web-based decision support system was built that combines the Analytical Hierarchy Process (AHP) method and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). AHP is used to calculate weights on the criteria used such as crop quality, resistance to pests, and environmental adaptability, while TOPSIS is used to rank preferences for each alternative used. This system is expected to help farmers make more objective and targeted decisions. Test results show that this system is able to provide accurate and relevant recommendations, according to the needs of local farmers. And from the test results of the combination of the two methods, a decision was made on the alternative with the highest preference value of 0.928 from the Bisi-18 corn seed variety.
Pengembangan Aplikasi Evaluasi Pembelajaran Berbasis Web Pada Mata Kuliah SPK Dengan Metode Linier Congruential Generator Salim, Putra; Fakhriza, M.
EDU SOCIETY: JURNAL PENDIDIKAN, ILMU SOSIAL DAN PENGABDIAN KEPADA MASYARAKAT Vol. 5 No. 1 (2025): Februari-Mei 2025
Publisher : Association of Islamic Education Managers (Permapendis) Indonesia, North Sumatra Province

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56832/edu.v5i1.802

Abstract

Evaluasi hasil belajar dalam pendidikan dilakukan untuk menilai sejauh mana kemampuan atau pencapaian siswa selama mengikuti proses pembelajaran. Pada tingkat perkuliahan, evaluasi ini dilakukan melalui berbagai cara, yang pada dasarnya melibatkan tes atau ujian. Artikel ini bertujuan untuk mengembangkan aplikasi berbasis web untuk evaluasi pembelajaran pada mata kuliah Sistem Pendukung Keputusan (SPK), dengan menggunakan metode Linear Congruential Generator (LCG), yang dapat berfungsi sebagai media pendukung pembelajaran agar mahasiswa dapat belajar lebih efektif. Penelitian ini merupakan penelitian jenis Research and Development (R&D) yang bertujuan mengembangkan aplikasi evaluasi pembelajaran berbasis web pada mata kuliah pengantar ilmu komputer, menggunakan metode LCG. Proses penelitian ini mengikuti tahapan pengembangan sistem yang meliputi analisis kebutuhan, desain, implementasi, dan evaluasi sistem. Aplikasi ini terdiri dari komponen soal kognitif, afektif, dan psikomotorik. Dengan memanfaatkan algoritma LCG untuk pengacakan soal, diharapkan pertanyaan yang muncul tidak mudah diprediksi oleh mahasiswa
Application of Data Mining with C5.0 Algorithm to Recommend Prosperous Family Card (KKS) Recipients Fadilla, Nurul; Zufria, Ilka; Fakhriza, M.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 2 (2025): Research Article, Volume 7 Issue 2 April, 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i2.5913

Abstract

Poverty is a social problem that still often occurs in various regions in Indonesia, including in Silau Laut District which consists of several villages such as Bangun Sari, Silo Bonto, Silo Lama, Lubuk Palas, and Silo Baru. Although the area is quite large, there are still many families who are classified as poor and unable to meet their basic needs. To overcome this, the government launched the Prosperous Family Card (KKS) program as a form of social assistance. However, the process of determining prospective KKS recipients still faces various obstacles, such as a random selection method based on data sent by each village to the central government. This raises concerns about the inaccuracy of the target in the distribution of aid, so that the aid is not received by families who really need it. In addition, a lot of data has not been utilized optimally in the selection process. Therefore, this study aims to design a website-based information system that can help Silau Laut District in providing recommendations for prospective KKS assistance recipients by utilizing data mining techniques. The algorithm used is C5.0, because it is able to produce a decision tree with high accuracy, while the system development method used is Rapid Application Development (RAD) to accelerate the system development process. The result of this research is an information system that can process community data and provide recommendations for prospective KKS assistance recipients in a more objective and targeted manner in the next period.
Expert System Based on K-Nearest Neighbor for Oil Palm Fertilizer Application Optimization Triutami, Anggun; Fakhriza, M.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6092

Abstract

This study aims to develop an expert system utilizing the K-Nearest Neighbor (KNN) algorithm to recommend suitable fertilizers for oil palm plants based on soil conditions, climate, and plant age. A quantitative approach was employed, involving literature review, data collection, model development, and evaluation. Data were obtained from PT. Nusantara Plantation IV Torgamba Plantation, including variables such as soil pH, dolomite, NPK, urea application, and crop yields. The KNN model was optimized with a K-value of 6 and evaluated using metrics including accuracy (63.63%), precision, recall, F1-score, Mean Absolute Error (MAE: 1995.38), and Mean Squared Error (MSE: 5,257,254.73). The system demonstrates the ability to provide fertilizer recommendations by identifying similarities in historical data, though further accuracy improvements are possible. The practical implications of this research include assisting farmers in optimizing fertilizer selection, enhancing productivity, and minimizing environmental impact. Future studies could explore the integration of additional variables or alternative algorithms such as Decision Tree or Naive Bayes to improve performance.
Sistem Informasi Berbasis Web untuk Meningkatkan Manajemen Penyewaan Alat Elektronik CV. Rentalindo Digital Pro Manday, M Irsyan Antony; Muliani, Aninda; Fakhriza, M.
Jurnal IPTEK Bagi Masyarakat Vol 4 No 3 (2025)
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/j-ibm.v4i3.1092

Abstract

CV. Rentalindo Digital Pro is an MSME in the electronic equipment rental sector that still relies on a manual recording system, which creates issues such as data loss, administrative errors, and service delays. This study develops a web-based rental information system as an appropriate technology solution to improve operational efficiency and data accuracy while supporting MSME empowerment. The study employs the Software Development Life Cycle approach with the Waterfall model, which includes needs analysis, system design, implementation, testing, and maintenance, in developing the system. The testing results, as presented in the testing table, show that the system is capable of automating transaction recording, centrally managing customer data, providing real-time information on inventory and booking status, and streamlining operational processes through an easy-to-use interface. Significant improvements in data security, information transparency, and service efficiency demonstrate that this system not only resolves internal issues but also has the potential to empower MSMEs through the effective use of information technology.
SISTEM INFORMASI PENGELOLAAN DATA SERANGAN ORGANISME PENGGANGGU TANAMAN (OPT) BIOFARMAKA PADA UPTD PTPH PROVINSI SUMATERA UTARA BERBASIS WEBSITE Tarigan, Putri Amelia; Fakhriza, M.; Nasution, Muhammad Adnan Buyung
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.3214

Abstract

Abstract: This study aims to design and implement a web-based information system for managing pest attack data (Plant Disturbing Organisms/OPT) on medicinal plants (biofarmaka), particularly in the operational area of the UPTD PTPH of North Sumatra Province. The identified problems include inefficient manual reporting, vulnerability to errors, and delays in information delivery. This research adopts a qualitative method and applies the waterfall model for system development. The results show that the system effectively assists field officers, district coordinators, and provincial administrators in inputting, verifying, and monitoring pest attack data in a more efficient, accurate, and real-time manner. Additionally, the system supports visual analysis through charts and report summaries, thereby facilitating strategic decision-making for OPT control. Keywords: Information System, Plant Disturbing Organism (OPT), Biofarmaka, UPTD PTPH Abstrak: Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem informasi berbasis website untuk pengelolaan data serangan Organisme Pengganggu Tanaman (OPT) pada tanaman biofarmaka, khususnya di wilayah kerja UPTD PTPH Provinsi Sumatera Utara. Permasalahan yang dihadapi berupa proses pelaporan manual yang kurang efisien, rawan kesalahan, dan keterlambatan penyampaian informasi. Penelitian ini menggunakan metode kualitatif serta model pengembangan perangkat lunak waterfall. Hasil implementasi menunjukkan bahwa sistem ini mampu membantu petugas lapangan, koordinator kabupaten, dan admin provinsi dalam menginput, memverifikasi, dan memantau data serangan OPT secara lebih efisien, akurat, dan real-time. Selain itu, sistem ini mendukung analisis visual melalui grafik dan rekapitulasi laporan, sehingga mempermudah pengambilan keputusan strategis dalam pengendalian OPT.  Kata kunci: Sistem Informasi, Organisme Pengganggu Tanaman (OPT), Biofarmaka, UPTD PTPH
Co-Authors Abdul Aziz Abdul Halim Hasugian Andini Wulandari Angga Ardiansyah Aninda Muliani Armanda, Akbar Agustama Astuti, Andriani Dwi Baihaqi, Abdullah Afif Baratih, Ira Iranda Isyha Br Sembiring, Nadia Fadilla, Nurul Haerani, Sintia Hafidz, Hasbanur Harahap, Putri Sari Febrianty Hasibuan, Maria Hikmah Heri Santoso Hidayati, Lily Ilka Zufria Irawati, Cici Lubis, Desy Ramadhani Manday, M Irsyan Antony Manurung, Haidar Azra Mhd Furqan Muchain, Alfira Nafhan Muhammad Dedi Irawan Nasution, Muhammad Adnan Buyung Raissa Amanda Putri Rangkuti, Syawaliah Putri Ritonga, Fazrul Umri Salim, Putra Silalahi, Dinah Makhroza Sinaga, Imam Adlin Sitorus, Andriani Situmeang, Monica Syaqila, Saidatus Tarigan, Putri Amelia Triutami, Anggun