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All Journal Jurnal Mantik Penusa MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Komputasi dan Teknologi Informasi JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) ComTech: Computer, Mathematics and Engineering Applications Jurnal Mantik TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) INFOKUM Journal of Innovation Information Technology and Application (JINITA) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Computer Networks, Architecture and High Performance Computing International Journal of Basic and Applied Science Jurnal Mandiri IT Jurnal Nasional Teknologi Komputer LEBAH Journal of Computer Science and Research International Journal of Enterprise Modelling Indonesian Journal of Education And Computer Science
Fristi Riandari
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Development of stable qubits and error correction in quantum computer architecture for superconducting quantum processors Sihotang, Hengki Tamando; Siringoringo , Rimmar; Riandari, Fristi; Song , Jiang Lou; Sim, Lee Choi
Journal of Computer Science and Research (JoCoSiR) Vol. 1 No. 4 (2023): Oct: Computing Quantum and Related Fields
Publisher : Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65126/jocosir.v1i4.27

Abstract

A comprehensive mathematical model formulation is presented, encompassing gate fidelity optimization, coherence time extension, stabilizer code evolution, and surface code implementation. The research demonstrates significant advancements in qubit stability, with a 7% increase in gate fidelity and a remarkable 50% extension in coherence time achieved through optimized gate operations and material improvements. Quantum error correction techniques, guided by the Lindblad master equation and the surface code, result in a 25% reduction in error rates, contributing to the overall stability of the quantum processor. The outcomes not only bring practical quantum computing closer to realization but also provide a foundation for future innovations. The research identifies avenues for continued optimization, including advanced gate designs, exploration of emerging qubit technologies, and the development of sophisticated error correction codes. Further interdisciplinary collaborations and investigations into scalable quantum architectures, materials science, and cryogenic engineering are essential for overcoming remaining challenges. The insights gained contribute to the advancement of fault-tolerant quantum computing systems, offering transformative capabilities for computation and technology.
Graph-based Exploration for Mining and Optimization of Yields (GEMOY Method) Sihotang, Hengki Tamando; Riandari, Fristi; Sihotang , Jonhariono
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 2 (2024): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol16.2024.777.pp70-81

Abstract

This research explores the application of graph-based optimization techniques to enhance yield management and minimize transportation costs in industrial operations, particularly focusing on mining. By representing mining sites and processing plants as nodes and transportation routes as edges in a graph, we formulated an optimization problem aimed at maximizing yields while minimizing associated costs. Utilizing linear programming, we demonstrated significant cost savings, reducing transportation costs from 2100 units to 1700 units through optimized flow distribution. The study integrates elements of graph theory, optimization algorithms, and machine learning, providing a robust framework for efficient resource allocation and operational planning. The numerical example underscores the practical applicability of these techniques, paving the way for further research and refinement to accommodate additional constraints and dynamic changes in resource availability. This research highlights the potential of graph-based methods to achieve substantial economic and operational improvements across various industrial contexts.
Leveraging AI for optimization in supply chain decision support: Enhancing predictive accuracy Judijanto, Loso; Riandari, Fristi; Marsoit, Patrisia Teresa
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 3 (2024): July: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol16.2024.858.pp171-184

Abstract

This research explores the use of AI-driven techniques to optimize supply chain decision-making by integrating demand forecasting, inventory management, and logistics optimization. The main objective is to enhance predictive accuracy while minimizing overall supply chain costs through the application of machine learning and reinforcement learning methods. The research design involves the development of a comprehensive mathematical model that combines AI-based demand forecasting with cost optimization in inventory and transportation. A machine learning model is employed to predict demand, while optimization techniques are used to minimize inventory and logistics costs. Reinforcement learning is introduced as a method for real-time decision-making, allowing the system to continuously adapt and improve. The methodology involves testing the model through a numerical example, where predicted demand is used to optimize inventory and logistics costs. The main results show that the AI-based model achieves a demand forecasting accuracy with a Mean Squared Error (MSE) of 50, resulting in a total supply chain cost of 760 units, which includes both inventory and transportation costs. Despite the initial prediction error, the model demonstrates the potential for cost savings and operational efficiency through better alignment of supply chain components. The research concludes that while the AI-driven approach offers significant improvements in supply chain management, further refinement of the predictive model and the practical application of reinforcement learning are necessary to fully realize its benefits. Future research should focus on enhancing model accuracy and scalability in real-world supply chain environments
Perancangan Aplikasi Pemilihan Texapon Dalam Pembuatan Sabun Cair Dengan Menerapkan Metode Analytical Hierarchy Process Riandari, Fristi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 1 No. 1 (2019): Computer Networks, Architecture and High Performance Computing
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnapc.v1i1.47

Abstract

Keberhasilan sebuah produk dari perusahaan tergantung dari kwalitas bahan baku. dan sulitnya dalam menentukan bahan baku secara cepat dan membutuhkan waktu yang lama. Oleh karena itu di perlukan untuk mengatasi masalah tersebut adalah sebuah Sistem Pendukung Keputusan untuk memilih Texapon dalam pembuatan sabun cair dengan metode AHP.Untuk mengetahui hal tersebut, maka akan dilakukan suatu metode pengambilan keputusan multikriteria dengan cara memecahkan situasi kompleks dan tidak terstruktur kedalam bagian-bagian dan menyusunnya dalam hierarki.Dengan menggunakan metode AHP pada SPK maka penentuan Texapon dalam pembuatan sabun cair dapat dihitung berdasarkan perhitungan dari bobot kriteria masing-masing, sehingga dapat memilih Texapon dalam pembuatan sabun cair di dalam perusahaan dapat dilakukan secara cepat.
Implementation of Decision Support System for Determination of Employee Contract Extension Method Using SAW Sinaga, Baik Sepwanri; Riandari, Fristi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 2 No. 2 (2020): Computer Networks, Architecture and High Performance Computing
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnapc.v2i2.397

Abstract

Effect of rapid technological developments have contributed so as to provide an opportunity to study and analyze a problem. In the company of PT. Cipta Mandiri Agung Jaya, employee contract renewal process is done in less efficient. In general, the process of employee contract extension is carried out by way of division form a contract extension, has not made an assessment atupun evaluation of each employee. Through employee contract renewal process conducted so far gives a great influence to the advancement of the company. On this occasion, in view of the managerial aspects of the formulation of the problem is how to implement the SAW method in the determination of employee contract extension. How to implement a decision support system in the determination of contract extensions employees at PT. Court Of Human Self Jaya, how to design decision support systems in the SAW method using the employee contract extension programming language VB 2010 and the Microsoft Access database. The purpose was to analyze the issue formulation SAW method in the determination of employee contract extension, implementing a decision support system in the determination of contract extensions employees at PT. Court Of Human Self Jaya, pendukunng system design decisions in the SAW method using the employee contract extension programming language VB 2010 and the Microsoft Access database.
Determination of the Decision Support System Based on Teacher Performance Rewards Receiver With AHP method on SMK Negeri 1 Beringin Subowo, Subowo; Riandari, Fristi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 2 No. 2 (2020): Computer Networks, Architecture and High Performance Computing
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnapc.v2i2.413

Abstract

Abstract Teacher performance evaluation of SMK Negeri 1 Beringin Deli Serdang Regency was conducted on 3 teachers as samples of teacher performance appraisal data as material for consideration of the continued relationship of cooperation for the future budget. Components of performance appraisal of teacher performance at VOCATIONAL SCHOOL 1 Beringin Deli Serdang Regency are work performance, performance quantity, performance discipline, cooperation, and loyalty. Problems with the teacher performance appraisal process that occur due to unclear criteria and assessment weights. A method in a decision support system can help the optimal decision making process, the AHP method in determining the performance evaluation of honorary employees. There are three employee performance weights, which are very good, good, sufficient and good enough, from 3 employees who are categorized by performance appraisal, after applying the AHP method, it is obtained Irmala, S.Kom value = 1.139 Iswadi, S.Kom value = 0.739 and Hadi Suprayetno, ST value = 0.79, the three teachers were categorized with very good performance assessments.
Expert System Mediagnosa Hama On Phon Oil With Certainty Factor Method Situmorang, Lamhot; Riandari, Fristi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 2 No. 2 (2020): Computer Networks, Architecture and High Performance Computing
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnapc.v2i2.416

Abstract

The process of palm oil culture is influenced by various factors, one of which is the pest and disease factors. Generally the problem of farmers differentiating pests and diseases, this is dyed most of the farmers lack information and rely on the experience of other farmers to overcome the existing pest and disease problems. In handling pests and diseases, it is necessary to have a farmer consilant who is able to diagnose pests and diseases on oil palm trees. In this study, an expert system for diagnosing pests and diseases in palm tree plants, as well as providing various solutions for pests or diseases. The method used in this expert system is the Certainty Fators method. Certainty Method The factors was chosen because this method is suitable in the process of determining the identification of pests and diseases and the result of this application is the percentage of the system. The percentage is influenced by the CF value obtained from the system, the percentage of expert system consultations is taken from the highest yield as an alternative to other pests or diseases that attack oil palm tree crops.
Komparasi Metode Certainty Factor dan Dempster Shafer untuk Mendiagnosa Penyakit Autis Ginting, Ramadhanu; Riandari, Fristi; Afrisawati; Syechu, Weno; Afifa, Rizky Maulidya; Ritonga, Rama Prameswara
Indonesian Journal of Education And Computer Science Vol. 3 No. 1 (2025): INDOTECH - April 2025
Publisher : PT. INOVASI TEKNOLOGI KOMPUTER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60076/indotech.v3i1.1212

Abstract

Penelitian ini membahas perancangan sistem yang bertujuan untuk menangani masalah autisme pada anak-anak. Autisme merupakan gangguan yang mempengaruhi kemampuan individu, terutama dalam hal interaksi sosial. Dalam konteks ini, sistem pakar digunakan untuk mentransfer keahlian seorang pakar ke dalam bentuk algoritma yang dapat digunakan untuk diagnosis.Penelitian ini menganalisis dua metode dalam sistem pakar, yaitu Certainty Factor dan Dempster Shafer, yang ditujukan untuk mendiagnosis autisme pada anak. Tujuan utama penelitian ini adalah untuk mengevaluasi dan menentukan metode mana yang paling efektif untuk diimplementasikan dalam aplikasi yang dapat membantu mengklasifikasikan anak-anak dengan autisme.Hasil komparasi menunjukkan bahwanya metode Certainty Factor mencapai tingkat probabilitas di atas 95 %, dibandingkan dengan metode Dempster Shafer dalam komparasi 2 metode yang penulis lakukan. Temuan ini memberikan wawasan yang signifikan mengenai efektivitas kedua metode, serta kontribusi mereka dalam pengembangan sistem pakar untuk diagnosis autisme. Diharapkan penelitian ini dapat menjadi referensi untuk solusi yang lebih baik dalam bidang kesehatan mental anak.
Hungarian maximization model approach for optimizing human resource assignment in multi-site projects Riandari, Fristi; Dalimunthe, Yulia Agustina; Ginting, Ramadhanu; Afifa, Rizky Maulidya; Afrisawati, Afrisawati
Jurnal Teknik Informatika C.I.T Medicom Vol 17 No 2 (2025): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Digital transformation in project management demands the implementation of computational models that are able to handle the complexity of human resource (HR) allocation efficiently and objectively. This study examines the application of the Hungarian algorithm in the form of maximization as a computer science-based optimization solution to the HR assignment problem in multi-location projects. By constructing a benefit matrix calculated from weighted attributes such as technical expertise, experience, and location preference, this study implements linear transformations and matrix processing procedures using a numerical approach in Python. This digitalization process allows the system to perform assignment evaluation and allocation automatically and with high precision. Simulation results on a case study of five workers and five project locations show that the model produces optimal assignments with a total benefit score of 420. This model proves its effectiveness in solving polynomial assignment problems, while expanding the use of the Hungarian algorithm in the domain of applied computer science to support data-driven decision making. This study emphasizes the role of classical algorithms in supporting scalable and replicable digital solutions for modern HR management systems.
Pemanfaatan Artificial Intelligence (AI) dalam Menyusun Karya Ilmiah bagi Siswa SMA Unggulan Al-Azhar Medan Afifa, Rizky Maulidya; Ginting, Ramadhanu; Afrisawat, Afrisawat; Riandari, Fristi; Safitri, Habibi Ramdani
Lebah Vol. 18 No. 4 (2025): July: Pengabdian
Publisher : IHSA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/lebah.v18i4.358

Abstract

Pengabdian masyarakat ini bertujuan untuk memanfaatkan teknologi Kecerdasan Buatan (AI) dalam proses penyusunan karya ilmiah bagi para siswa di SMA Unggulan Al-Azhar Medan. Di era digital saat ini, kemampuan menulis karya ilmiah merupakan kompetensi yang sangat penting untuk dikuasai oleh siswa. Namun, banyak siswa yang mengalami kesulitan dalam tahapan penyusunan, mulai dari pemilihan topik hingga penulisan dan pengeditan. Melalui pengabdian masyarakat khususnya dalam pelatihan pemanfaatan Artificial Intelligence (AI) diperkenalkan alat berbasis AI dengan memperhatikan penggunaan prompt yang dapat membantu siswa SMA Unggulan Al-Azhar Medan dalam mengidentifikasi tema, menyusun kerangka, serta menghasilkan konten berkualitas. Metode yang diterapkan mencakup demonstrasi langsung, sesi tanya jawab, dan praktik mandiri. Hasil dari kegiatan ini menunjukkan adanya peningkatan pemahaman siswa tentang proses penulisan ilmiah, serta kemampuan  dalam memanfaatkan teknologi AI sebagai alat bantu. Pelatihan pemanfaatan AI diharapkan dapat mempercepat dan mempermudah proses pembelajaran, serta menghasilkan karya ilmiah yang lebih baik di kalangan siswa. Kegiatan ini dapat memberikan kontribusi signifikan terhadap peningkatan kualitas pendidikan serta keterampilan menulis siswa di era digital dengan bimbingan guru di SMA Unggulan Al-Azhar Medan. Kegiatan ini juga dapat memberikan kontribusi jangka panjang pada pembentukan generasi siswa yang lebih adaptif, kreatif dan memiliki literasi yang tinggi di dalam teknologi serta dengan tetap menekankan aspek etika penggunaan AI, keaslian dengan pendampingan guru. Pelatihan ini diharapkan dapat mewujudkan budaya literasi digital yang positif di lingkungan sekolah, peningkatan kemampuan berpikir kritis serta terbentuknya generasi pelajar yang siap menghadapi tantangan akademik dan teknologi di masa depan
Co-Authors Adjie Bintang Pamungkas Afifa, Rizky Maulidya Afrisawat, Afrisawat Afrisawati afrisawati, Afrisawati Agustina Simangunsong Aisyah Alesha Arjon Samuel Sitio Baik Sepwanri Sinaga Barreto Jose da Conceição Benny Ginting Bosker Sinaga Chandra, Suherman Christina Simanjuntak Cristy, Niolinda Dalimunthe, Yulia Agustina Danvy Nadhira Dedi Setiawan Halawa Demita Sihotang Dewi Novika Simanjuntak Dimas Ribowo Esera Gulo Ginting, Ramadhanu Hamed Huckle Schubert Hasugian , Paska Marto Hasugian, Penda Sudarto Hengki Tamando Sihotang Husain Husain Ibnu Rizky John Foster Marpaung Judijanto, Loso Lamhot Situmorang Lise Pujiastuti Marsoit, Patrisia Teresa Mochamad Wahyudi Muhammad Rafli Muhammad Syaif Nasib Ratna Sari Purba Nellysa Putri Denila Nasution Novita Ria Lase Nurul Hayani Petti Indrayati Sijabat Pilisman Buulolo R. Mahdalena Simanjorang Ramayuni Marpaung Rehentiara Siringoringo Rian Syahputra Rita Zahara Tarigan Ritha Zahara Tarigan Ritonga, Rama Prameswara Rohit Gautama Roimasro Sibagariang Safitri, Habibi Ramdani Sari Murni Sarjon Defit Sethu Ramen Sihotang , Jonhariono Sim, Lee Choi Simangunsong, Agustina Sinaga, Baik Sepwanri Siringoringo, Rimmar Siti Ilya Suwella Situmorang, Lamhot Song , Jiang Lou Subowo Subowo Subowo Subowo Sulistianingsih, Indri Susandri, Susandri Tarisa Tarigan Tasril, Virdyra Temasokhi Ndruru Teresia Herniamwati Zebua Vina Winda Sari Vinsensia, Desi Wan Wimar Yahya Weno Syechu Yuda Perwira Yunus Simare-mare