Articles
<![CDATA[An efficiency metaheuristic model to predicting customers churn in the business market with machine learning-based ]]>
<![CDATA[Y. Syah, Rahmad B.]]>;
<![CDATA[Muliono, Rizki]]>;
<![CDATA[Akbar Siregar, Muhammad]]>;
<![CDATA[Elveny, Marischa]]>
<![CDATA[ IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijai.v13.i2.pp1547-1556
<![CDATA[Metaheuristics is an optimization method that improves and completes a task in a short period of time based on its objective function. The goal of metaheuristics is to search the search space for the best solution. Machine learning detects patterns in large amounts of data. Machine learning encourages enterprise automation in a variety of areas in order to improve predictive ability without requiring explicit programming to make decisions. The percentage of customers who leave the company or stop using the service is referred to as churn. The purpose of this research is to forecast customer churn in the market business. Particle swam optimization (PSO) was used in this study as a metaheuristic method to provide a strategy to guide the search process for new customers and obtain parameters for processing by support vector regression (SVR). SVR predicts the value of a continuous variable by determining the best decision line to find the best value. The number of transactions, the number of periods, and the conversion value are the parameters that are visible. Efficiency models are added to improve prediction results through two optimizations: prediction flexibility and risk minimization. The findings demonstrate the effectiveness of prediction in reducing customer churn.]]>
<![CDATA[The Impact of k-means on Association Rules Mining Algorithms Performance ]]>
<![CDATA[Hasudungan, Andre]]>;
<![CDATA[Muliono, Rizki]]>;
<![CDATA[Khairina, Nurul]]>;
<![CDATA[Novita, Nanda]]>
<![CDATA[ Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 5, No 2 (2024) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Sumatera Utara, Indonesia ]]>
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DOI: 10.30596/jcositte.v5i2.20907
<![CDATA[Association Rule Mining (ARM) is one of unsupervised learning approach of machine learning. It acts as a data analysis technique that enables the identification of frequent patterns, correlations, associations, and causal structures within certain datasets. This method widely used in numerous studies and practices to explore knowledges and strengthen decision making. However, dealing a large dataset with high number of transactions may become the shortcoming for the ARM algorithms, such as Apriori, FP-Growth, and Eclat. It leads them to face several challenges, including computational complexity, long mining durations, and memory consumption. Hence, this paper proposes k-means clustering to generates several groups of data to handle the issue, then proceed the ARM algorithms for each individual produced cluster. The study used Elbow method and Silhouette Coefficient as the method to determining optimum number of clusters to be used. The result pointed out that k-means-ARM generates a greater number of rules and provides more contextually relevant and significant correlations. In term of Lift Ratio average score, the k-means-ARM shows the greater value rather than non k-means ARM. The k-means-ARM combination is robust; this approach improves the efficiency and scalability of ARM for large datasets and enhances the interpretability of the discovered association rules]]>
<![CDATA[ANALISIS PERBANDINGAN MENGGUNKAN METODE TOPSIS DAN WASPAS DALAM PENENTUAN KARYAWAN TELADAN ]]>
<![CDATA[Sri Wahyuni]]>;
<![CDATA[Rizki Muliono]]>;
<![CDATA[Nurul Khairina]]>;
<![CDATA[Muhathir]]>
<![CDATA[ JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 7 No. 1 (2023): JATI Vol. 7 No. 1 ]]>
Publisher : <![CDATA[Institut Teknologi Nasional Malang ]]>
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DOI: 10.36040/jati.v7i1.6295
<![CDATA[CV. Multisindo Karya selaku industri konsultan teknologi data pada cara penentuan karyawan teladan saat ini masih menggunakan cara pemantauan langsung. Namun, proses ini dinilai belum efektif dan belum bisa mengakomodir terhadap hal-hal lain yang harusnya mendukung penilaian karyawan sehingga memungkinkan terjadinya kesalahan dalam penilaian dan memperlambat proses penentuan karyawan teladan acuan sedang memakai cara kalkulasi sebagai buku petunjuk, cara ini pastinya menghabiskan durasi cukup lama. Proses penilaian dengan menggunakan beberapa kriteria yang digunakan yaitu , kriteria dalam penilaian karyawan seperti disiplin kerja, tanggung jawab, komunikasi dan kerjasama, pemahaman dan penguasaan pekerjaan, dan inisiatif. Dengan memakai metode Technique for order Performance by Similarity to Ideal Solution, serta metode Weighted Aggregated Sum Product Assesment penulis merancang suatu aplikasi yang dapat melaksanakan cara penentuan karyawan teladan dengan hasil yang dapat dibanding antara kedua tata cara. Bersumber pada hasil kalkulasi dari tata cara TOPSIS memberikan hasil Ira Astriani Saragih dengan angka TOPSIS 0, 748, Serta menggunakan tata cara WASPAS memberikan hasil Ira Astriani Saragih dengan angka WASPAS 0,960. Dan tingkat akurasi yang didapat metode TOPSIS ialah 49,67% dan WASPAS ialah 50,33%.]]>
<![CDATA[RANCANG BANGUN APLIKASI E-LEARNING DENGAN IMPLEMETASI ALGORITMA FISHER YATES SHUFFLE DALAM PENGACAKAN SOAL UJIAN ]]>
<![CDATA[Irfansyah]]>;
<![CDATA[Rizki Muliono]]>; Susilawati
<![CDATA[ JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 7 No. 1 (2023): JATI Vol. 7 No. 1 ]]>
Publisher : <![CDATA[Institut Teknologi Nasional Malang ]]>
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DOI: 10.36040/jati.v7i1.6296
<![CDATA[E-Learning merupakan media yang digunakan untuk melakukan proses pembelajaran secara online. Setiap E-Learning mempunyai fitur yang berbeda-beda sesuai dengan keperluan masing-masing dalam melakukan proses pembelajaran. Fitur E-Learning yang banyak digunakan adalah fitur ujian. Ujian dilakukan sebagai tolak ukur untuk mengetahui tingkat pemahaman siswa selama pembelajaran. Penelitian ini fokus pada fitur pengacakan soal ujian untuk memastikan setiap siswa mendapatkan urutan soal yang berbeda dengan komposisi soal yang sama. Algoritma Fisher Yates Shuffle menghasilkan permutasi acak secara berurut untuk menghindari pengulangan urutan yang sama. Hasil pengujian yang telah dilakukan menunjukan bahwa dari 100 sampel siswa dan data soal yang diacak sebanyak 30 soal dengan soal yang ditampilkan kepada siswa sebanyak 15 soal menggunakan algoritma Fisher Yates Shuffle berhasil menghasilkan seperti yang diharapkan dan tidak terjadi pengulangan urutan soal yang sama oleh setiap siswa.]]>
<![CDATA[Perancangan Sistem Informasi Desa Gunung Malintang Kecamatan Barumun Tengah Kabupaten Padang Lawas ]]>
<![CDATA[Siregar, Yusril Izza Haholongan]]>;
<![CDATA[Muliono, Rizki]]>
<![CDATA[ Jurnal Ilmiah Teknik Informatika & Elektro (JITEK) Vol 4, No 1 (2025): Jurnal Ilmiah Teknik Informatika & Elektro (JITEK) ]]>
Publisher : <![CDATA[Universitas Medan Area ]]>
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DOI: 10.31289/jitek.v4i1.5654
<![CDATA[Systems that are still manual or direct recording that is not in accordance with their function will run for a very long time and take a lot of time, where manual systems still rely heavily on recording that prioritizes accuracy and observation as the main focus in the implementation process. This research aims to design and build a web-based information system to replace the manual recording system used by village officials in Gunung Malintang Village, Central Barumun District, Padang Lawas Regency. The system is designed using the PHP programming language with MySQL database. The system design follows the System Development Life Cycle (SDLC) approach with a waterfall model that includes requirements analysis, design, implementation, and system testing. The results of the study show that the designed information system is able to improve the efficiency of data management, reduce recording errors, and speed up the village administration process. This system not only makes it easier for village officials to manage data, but also provides benefits to the community through faster and more accurate services. With the implementation of this information system, it is hoped that village governance will become more modern and transparent, supporting the improvement of the quality of public services in rural areas.]]>
<![CDATA[Involvement of Various Selection Methods for Genetic Algorithms in Determining the Optimal Production Schedule Problem ]]>
<![CDATA[Muliono, Rizki]]>;
<![CDATA[Silviana, Nukhe Andri]]>;
<![CDATA[Novita, Nanda]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.8.4.2632
<![CDATA[This research investigates using genetic algorithms (GA) to optimize production scheduling in Medan's shoe industry. The study compares traditional manual and First Come First Serve (FCFS) methods against a GA approach, incorporating selection variations such as Boltzmann, Fitness Uniform Selection Scheme (FUSS), Exponential Rank Selection, and Roulette Wheel Selection. The optimal production order is derived from the chromosome with the highest fitness. Results indicate that GA with FUSS selection significantly reduces production time from 73,630 minutes to 45,650 minutes, achieving a 35% improvement in efficiency. This optimization is attributed to FUSS’s ability to maintain a diverse population, preventing premature convergence and ensuring a broader solution for space exploration. Additionally, it was found that using a smaller population size relative to the number of generations yields better optimization results. The study also demonstrates that while Roulette Wheel Selection shows more variability, it achieves higher optimization over time than FCFS. The practical implications of these findings are substantial for the shoe industry, including faster production cycles, better resource allocation, and an enhanced ability to meet customer demands. These benefits are exemplified by implementing the SISPROMA application, an innovative production scheduling information system that leverages machine learning to optimize scheduling in the manufacturing industry. This study provides valuable insights into applying genetic algorithms for production scheduling, highlighting their potential to enhance operational efficiency and reduce costs. Future research should explore additional optimization techniques and real-world applications to validate and extend these findings, ensuring broader applicability and continuous improvements in manufacturing efficiency.]]>
<![CDATA[DECISION SUPPORT SYSTEM IMPLEMENTATION IN DETERMINING STUDENTS TO RECEIVE BOS FUNDING USING THE WASPAS METHOD ]]>
<![CDATA[Napisah, Napisah]]>;
<![CDATA[Muliono, Rizki]]>;
<![CDATA[Khairina, Nurul]]>;
<![CDATA[-, Muhathir]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 1 (2023): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER ]]>
Publisher : <![CDATA[Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia ]]>
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DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4046
<![CDATA[Success in learning and learning activities at SMA Asy-Syafiiyah Medan, is not only influenced by teachers, but also by student aspects such as attendance, parental income, activity participation, achievement scores, and discipline. To obtain optimal results, the authors designed an application using the Weighted Aggregated Sum Product Assessment (WASPAS) method that can determine students who receive BOS funds. After calculating 5 times with predetermined criteria, Rizki Ridho Silalahi's final result was 0.9197. The system designed for receiving BOS Fund assistance at SMA Asy-Syafiiyah Medan has been tested by inputting criteria data and carrying out the calculation process using the WASPAS method.]]>
<![CDATA[Pemberdayaan generasi muda dalam transisi energi hijau melalui pelatihan teknologi fuel cell ]]>
<![CDATA[Iswandi, Iswandi]]>;
<![CDATA[Supriatno, Supriatno]]>; Susilawati, Susilawati;
<![CDATA[Hermanto, Tino]]>;
<![CDATA[Hasibuan, Samsul Abdul Rahman Sidik]]>;
<![CDATA[Muliono, Rizki]]>;
<![CDATA[Royani, Ida]]>;
<![CDATA[Aldori, Yopan Rahmad]]>
<![CDATA[ Jurnal Anugerah Vol 7 No 1 (2025): Jurnal Anugerah: Jurnal Pengabdian kepada Masyarakat Bidang Keguruan dan Ilmu Pen ]]>
Publisher : <![CDATA[Universitas Maritim Raja Ali Haji ]]>
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DOI: 10.31629/anugerah.v7i1.7174
<![CDATA[Krisis energi global dan rendahnya literasi energi bersih di kalangan pelajar mendorong perlunya edukasi teknologi alternatif yang berkelanjutan. Kegiatan pengabdian ini dilatarbelakangi oleh kebutuhan untuk meningkatkan wawasan siswa terhadap teknologi energi terbarukan, khususnya fuel cell. Tujuan kegiatan ini adalah untuk memperkenalkan prinsip dasar kerja teknologi fuel cell serta membangun pemahaman dan keterampilan awal siswa Sekolah Menengah Kejuruan (SMK) sebagai bagian dari edukasi transisi energi hijau. Pengumpulan data dilakukan sebagai langkah evaluatif untuk meninjau keberhasilan kegiatan PkM. Tolok ukur keberhasilan ditentukan berdasarkan peningkatan pemahaman kognitif siswa serta tingkat partisipasi dan respons positif terhadap materi pelatihan. Metode pelaksanaan menggunakan pendekatan pelatihan interaktif, pendidikan masyarakat, dan substitusi ipteks. Peserta kegiatan berjumlah lebih dari 50 siswa jurusan Bisnis dan Manajemen di SMK Swasta Nurul Amaliyah Tanjung Morawa. Teknik pengumpulan data mencakup pre-test dan post-test untuk mengukur peningkatan pemahaman, observasi untuk menilai keterlibatan siswa, serta wawancara semi-terstruktur untuk menggali persepsi dan ketertarikan siswa terhadap teknologi energi bersih. Analisis data dilakukan secara deskriptif kuantitatif dan naratif. Hasil menunjukkan adanya peningkatan skor pemahaman peserta dari 42% menjadi 81%, disertai partisipasi aktif dan ketertarikan tinggi terhadap materi. Peserta juga mampu mengaitkan prinsip kerja fuel cell dengan peluang usaha berbasis energi bersih. Kegiatan ini membuktikan bahwa edukasi ipteks lintas disiplin dapat menjembatani kesenjangan pemahaman teknologi dan membentuk kesadaran technopreneurship. Oleh karena itu, model pelatihan ini berpotensi diterapkan secara lebih luas dalam satuan pendidikan vokasi non-teknik untuk mendukung transisi energi nasional.]]>
<![CDATA[Sentiment Towards Social Media Politeness Ambassadors: A Case Study Using the Naive Bayes Method ]]>
<![CDATA[Fikri, Ridho Ahmad]]>;
<![CDATA[Muliono, Rizki]]>
<![CDATA[ JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 3Spc (2025): Special Issues 2025: Innovations in Predictive Analytics and Sentiment Analy ]]>
Publisher : <![CDATA[Universitas Medan Area ]]>
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DOI: 10.31289/jite.v8i3Spc.14404
<![CDATA[Social media has had a significant impact on modern society, serving as a primary platform for sharing information and opinions. One intriguing phenomenon is the viral case of a female police officer, Putri Cikita, who earned the title "Ambassador of Courtesy" due to her actions in a video. This study aims to analyze public sentiment regarding this case on Twitter using the Naive Bayes Classifier (NBC) method. The research adopts a quantitative descriptive approach with sentiment analysis based on Text Mining, utilizing Python and Google Colab. The dataset consists of 2,000 Indonesian-language tweets collected from August to November 2024 using the keywords "Ambassador of Courtesy" and "Putri Cikita." The research stages include data collection, data preprocessing (case folding, tokenizing, filtering, stemming), and sentiment labeling into positive, negative, and neutral classes. The analysis results reveal that 11.55% of tweets express positive sentiment, 68.40% are neutral, and 20.05% are negative. The Naive Bayes method proves effective in classifying textual sentiment data. This research provides insights into public perceptions of viral events and underscores the importance of public image management in the digital era.]]>
<![CDATA[Classification of Hepatitis Disease Using The Fuzzy Mamdani Method ]]>
<![CDATA[Hidayani, Nurul]]>;
<![CDATA[Muliono, Rizki]]>
<![CDATA[ JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 3Spc (2025): Special Issues 2025: Innovations in Predictive Analytics and Sentiment Analy ]]>
Publisher : <![CDATA[Universitas Medan Area ]]>
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DOI: 10.31289/jite.v8i3Spc.14426
<![CDATA[In the modern world, almost everyone uses technology and information. This is evident in various fields, ranging from education and employment to entertainment. Society is too dependent on technology and information, to the point of neglecting their own health. There are many diseases caused by neglecting one's own health, one of which is hepatitis. This is because some people pay little attention and are reluctant to get it checked. Because hepatitis is very dangerous for human survival, treatment must begin as soon as the first symptoms appear and assist in the early diagnosis of hepatitis. This will allow for the identification of the type of hepatitis disease. The aim of this research is to apply the Mamdani fuzzy method for the classification of hepatitis diseases. The Mamdani fuzzy method has been successfully utilized in systems for diagnosing hepatitis diseases. In this system, it will provide instructions, namely to select which symptoms are experienced, then you can choose those symptoms by checking them off, and this system will provide a diagnosis based on the symptoms experienced. The diagnosis results include the type of hepatitis disease experienced, as well as treatment solutions. The results obtained for diagnosing hepatitis A disease using fuzzy Mamdani calculation shows that 68% , and the diagnosis of hepatitis B disease using fuzzy mamdani calculations shows 53% , and the diagnosis of hepatitis C disease using fuzzy mamdani calculations shows 59%.]]>
