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Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika
Published by Asosiasi Riset Teknik Elektro Dan Informatika Indonesia
ISSN : 30318904     EISSN : 30318912     DOI : 10.61132
Core Subject : Science,
Computer Science & IT
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika memuat naskah hasil-hasil penelitian di bidang Sistem Informasi dan Teknik Informatika
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 235 Documents
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Peran Kecerdasan Buatan terhadap Diagnosis dan Penanggulanan Masalah Kesehatan Mental Andri Sahata Sitanggang; Muhammad Restu Aufa Cahyadin; Muhammad Dzikri Maulaarif; Muhammad Lutfhi Khaeri Ihsan; Septian Muqtiyana
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 5 (2025): September : Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i5.1021

Abstract

The increasing number of mental health disorders in various countries has created an urgent need for innovation in the diagnosis and treatment process. This problem not only impacts individuals' quality of life but also creates a significant social and economic burden. One solution that is beginning to be widely researched is the use of artificial intelligence (AI) in the field of mental health. This research used a literature review of various previous studies discussing the role, application, and impact of AI. The results of the review indicate that AI technology, particularly in the form of digital applications such as chatbots, has great potential to support the recovery process for patients with mental disorders. AI-based chatbots can provide responsive, two-way interactions, so users feel heard and receive initial emotional support. One technical approach used is Natural Language Processing (NLP), which enables the system to understand natural human language. Simultaneously, Long Short-Term Memory (LSTM) algorithms are used to analyze language patterns and detect symptoms of depression more accurately. Various studies have reported that the application of NLP and LSTM can improve the reliability of diagnoses and provide responses tailored to user needs. Furthermore, AI can provide personalized recommendations, tailor interventions to the user's condition, and monitor mental health developments in real time. This has the potential to assist mental health practitioners in making faster and more informed decisions. However, the adoption of AI among practitioners remains relatively low. Influencing factors include limited technological understanding, limited infrastructure, and debates over ethical aspects and data privacy. Therefore, while AI has significant potential to improve the quality of mental health services, regulations, ethical guidelines, and synergy between technology and healthcare professionals are needed to ensure safe and effective implementation.
Implementasi Algoritma Kriptografi Hybrid AES dan RSA dalam Rancang Bangun Aplikasi Bank Sampah Pancadaya Berbasis Web untuk Keamanan Data Transaksi Nasabah Mardhyah Fathania ‘Izzati; Widya Darwin
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 5 (2025): September : Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i5.1036

Abstract

This research aims to develop a transaction data security system on the web-based Pancadaya Waste Bank application by applying a hybrid cryptographic algorithm that combines Advanced Encryption Standard (AES) and Rivest Shamir Adleman (RSA). The problem faced in the previous system is the weak recording and security of customer transaction data, because the process is still carried out manually so that it is prone to recording errors, loss of important information, and potential misuse of data by unauthorized parties. To answer these problems, this study uses the Rapid Application Development (RAD) method which allows the application development process to be carried out quickly, flexibly, structured, and according to user needs. The research method used was a qualitative approach with interview techniques with the management of the Pancadaya Waste Bank and the Environment Office, as well as an in-depth literature study on the application of hybrid cryptographic algorithms in modern information systems. The system is built using the PHP programming language, MySQL database, and OpenSSL library as the main support for the data encryption and decryption process. The implementation of the algorithm is carried out by encrypting transaction data using AES for efficiency and speed, then the AES key is secured through RSA to ensure a higher level of security while preventing illegal access. The test results showed that the system was able to encrypt and decrypt transaction data in real-time, as well as display transaction results in the form of digital notes on deposit and balance withdrawal activities. In addition, performance tests using GTmetrix showed that the application has excellent speed, stability, and processing efficiency, making it feasible to be widely implemented in Pancadaya Waste Bank operations.
Perancangan Sistem Informasi Layanan Pengaduan Masyarkat dan Pengajuan Hibah Berbasis Web Dibagian Kesejahtraan Rakyat Kabupaten Situbondo Moh. Dafid Halid; Achmad Baijuri
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 5 (2025): September : Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i5.1095

Abstract

The development of information technology plays an important role in improving the quality of public services, including the processes of public complaints and grant submissions. Currently, these services at the Welfare Section of Situbondo Regency are still carried out manually, which often causes recurring problems such as delayed verification, lack of transparency in decision-making, and difficulties in data archiving and retrieval. These challenges not only slow down administrative processes but also reduce public trust in government services. Therefore, the design of a web-based information system is considered crucial to support the implementation of e-government and to ensure more effective, efficient, and accountable services. This study aims to design an integrated web-based information system that facilitates both public complaints and grant submissions within one platform. The research method applied is Object Oriented Analysis and Design (OOAD), which emphasizes systematic analysis and modeling using the Unified Modeling Language (UML). The analysis phase includes identifying system requirements, business process modeling, and defining functional and non-functional needs. The design phase produces various models such as business process design, input-output forms, application architecture using a three-tier structure, UML diagrams (use case, activity, class, and sequence diagrams), and database modeling. The results of this research are expected to provide a system design that improves the speed of service delivery, enhances transparency through real-time status tracking, reduces the risk of data loss by implementing digital archiving, and increases efficiency in the verification process. Overall, the proposed system design contributes to strengthening good governance practices in Situbondo Regency and serves as a reference for similar developments in other local government institutions.
Perancangan Sistem Informasi Kelayakan Bisnis untuk Mendukung Pengembangan Laboratorium Inkubator Bisnis Mutinda Teguh Widayanto; Tamam Asrori; Mohammad Mohammad; Rizal Nurdin Imano; Naufal Abiyyu Imano
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 6 (2025): November: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i6.1124

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in Indonesia’s economy, yet their failure rate remains high due to weak business planning and the absence of systematic feasibility studies. University business incubator laboratories are expected to assist prospective entrepreneurs in conducting comprehensive feasibility analyses, but evaluations are often performed manually and subjectively. This study aims to design a Business Feasibility Information System to support business incubator laboratories in achieving more objective, efficient, and documented assessments. The research employs a Research and Development (R&D) approach using the System Development Life Cycle (SDLC) model, encompassing stages of requirement analysis, system design, and conceptual validation. The system is designed to evaluate four key aspects of business feasibility: market, production, human resources, and finance. The result is a conceptual system prototype that integrates all aspects into a unified assessment framework. The findings indicate that the proposed system enhances the effectiveness of incubator laboratories in evaluating and assisting tenants objectively while fostering digital entrepreneurship literacy. The study implies that information technology integration is essential for strengthening MSME sustainability and decision-making in Indonesia.
Sistem Pendukung Keputusan untuk Penentuan Penerima Bantuan Pendidikan di SMK Negeri 2 Binjai Menggunakan Metode Waspas Zhya Anggraini; Yani Maulita; Kristina Annatasia Br Sitepu
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 6 (2025): November: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i6.1135

Abstract

Advances in information and communication technology (ICT) have revolutionized various aspects of life, including the education sector. The application of technology in education enables more flexible, interactive, and personalized learning, as well as expanding access for students in various regions, including remote areas. SMK Negeri 2 Binjai is one of the vocational education institutions in Binjai City that is currently facing challenges in the process of determining recipients of educational assistance, particularly the Indonesia Pintar (PIP) Program, which is intended for underprivileged students. Until now, the selection mechanism for PIP recipients has been carried out manually, making it prone to subjectivity, lack of transparency, and limited integrated data. To overcome this problem, a decision support system is needed to help schools determine the recipients of educational assistance objectively and structurally using the Weighted Aggregated Sum Product Assessment (WASPAS) method, which is an effective multi-criteria decision-making technique for processing various assessment criteria to produce the best alternative ranking. The results of the calculation using the WASPAS method produced different preference values (Qi) for each student alternative. The highest score was obtained by Ilyas Ramadhanu with a Qi of 0.6899, followed by Binar Sembiring with a Qi of 0.5963, and Dimas Dwi Andika with a Qi of 0.5790. The lowest value was obtained by Adit Rahmazi with a Qi of 0.3852.
Penerapan Metode K-Nearest Neighbor untuk Mengetahui Tipe Gangguan Kecemasan Berdasarkan Faktor yang Mempengaruhi Zehy Fadia; Yani Maulita; Husnul Khair
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 6 (2025): November: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i6.1137

Abstract

Anxiety disorders are common mental health problems in society, often unrecognized by the sufferer. Identifying the type of anxiety disorder and its influencing factors is crucial for proper treatment. This research aims to apply the K-Nearest Neighbor (K-NN) method in identifying types of anxiety disorders based on influencing factors, focusing on patient data from Sylvani Hospital, Binjai. The K-NN method was chosen because of its ability to classify based on data proximity. This study used medical record data of patients with anxiety disorders, which were processed using MATLAB and Microsoft Excel software. The results show that the K-NN method is effective in identifying types of anxiety disorders, with a high level of accuracy, especially in the identification of Panic Disorder (K05) and Social Anxiety Disorder (K03). The use of MATLAB simplified the identification process by automating results, while data processing in Excel improved classification accuracy. This study concludes that the K-NN method can be an effective alternative in identifying anxiety disorder types based on the factors that influence them. It is recommended for future research to involve more variables and mental health experts for a more comprehensive validation of the results.
Diagnosa Penyakit Syndrome pada Anak menggunakan Metode Case Base Reasoning (CBR) Amysa Putri Sitepu; Novriyenni Novriyenni; Muammar Khadapi
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 6 (2025): November: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i6.1139

Abstract

Syndrome is a serious problem in children's health because it has a major impact on growth and development, especially in terms of intelligence and daily activities. Down Syndrome, as one of the most well-known chromosomal disorders, is often the main cause of intellectual developmental disorders, hypotonia, facial dysmorphism, early onset of Alzheimer's disease, and various behavioral disorders. Diagnosing syndrome diseases in children is often difficult due to complex and varied symptoms, requiring lengthy, costly, and time-consuming medical evaluations. This study aims to design a Case-Based Reasoning (CBR)-based expert system for diagnosing syndromes in children, which is expected to help accelerate the disease identification process and provide more effective and efficient solutions. The method used is the development of an expert system with a CBR approach, in which the system performs calculations and matching based on the symptoms selected by the user against the available case base. The results of the study show that from symptom inputs such as wide hands with short fingers, short stature, small head, stunted growth, small lower jaw, abnormal body appearance, and weak joints, the system was able to diagnose Klinefelter syndrome with a percentage of 43.58%. This system can be an alternative for patients or families who have limited time and funds to obtain medical consultations, so that diagnosis and follow-up can be carried out more quickly and efficiently.
Diagnosa Penyakit Hisprung pada Bayi menggunakan Metode Dempster Shafer Nadia Nurhafiza; Rusmin Saragih; Melda Pita Uli Sitompul
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 6 (2025): November: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i6.1140

Abstract

Hirschsprung’s disease is a congenital disorder caused by abnormal nerve cell development in the large intestine, leading to chronic intestinal obstruction in infants. This condition often manifests through symptoms such as constipation, abdominal distension, vomiting, and failure to thrive. The weak immune system of infants makes them highly susceptible to bacterial infections and further complications. At Bidadari General Hospital, there were 110 patients suspected of having Hirschsprung’s disease. One of the major challenges in managing these cases is the limited number of medical specialists, particularly pediatricians and pediatric surgeons, resulting in long waiting times for accurate diagnosis, especially during peak service hours. To address this issue, this study applies the Dempster-Shafer method in an expert system to assist in diagnosing Hirschsprung’s disease based on clinical symptoms. The method effectively handles uncertainty and combines multiple pieces of medical evidence to produce more accurate diagnostic probabilities. The analysis results show that from the selected symptoms, the highest diagnosis probability corresponds to short-segment Hirschsprung’s disease with a confidence level of 71.54%. These findings suggest that the Dempster-Shafer method can serve as an effective alternative tool to support early and accurate diagnosis of Hirschsprung’s disease in infants.
Penerapan Algortima K-Means untuk Mengelompokkan Siswa Berdasarkan Tingkat Pemahaman dan Kemandirian Belajar dalam Kurikulum Merdeka Ingke Fuji Utami Br Barus; Novriyenni Novriyenni; Imeldawaty Gultom
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 6 (2025): November: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i6.1141

Abstract

The Merdeka Curriculum implemented in various schools in Indonesia aims to provide flexibility in learning, where students can learn according to their individual needs, interests, and pace. One of the challenges in implementing this curriculum is how to effectively identify classroom activity and student discipline. SD Islamiyah, as a school that implements the Merdeka Curriculum, also faces challenges in understanding variations in student classroom activity and discipline. Some students are able to learn in a disciplined manner with little guidance, while others require more intensive support from teachers. Therefore, a system is needed that can group student data more systematically so that teachers can develop teaching strategies that suit the needs of each group of students. One algorithm that can be used in data grouping is k-means clustering. The K-Means algorithm is a non-hierarchical algorithm derived from the data clustering method. The K-Means algorithm begins with the formation of cluster partitions at the beginning, then iteratively refines these cluster partitions until there are no significant changes in the cluster partitions. The K-Means method partitions data into groups so that data with similar characteristics are placed in the same group and data with different characteristics are grouped into other groups. This method can help group students more accurately based on their Class Activity and Discipline. From the results of the analysis, it was concluded that the student data group with Class Activity was Moderately Active Students, with Discipline being Disciplined, and an average score of 71-80.
Pengelompokan Data Siswa SMP dalam Mendeteksi Kesehatan Remaja Menggunakan Algoritma K-Means Delvi Kibina Br Sembiring; Khairul Khairul; Melda Pita Uli Sitompul
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 6 (2025): November: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i6.1142

Abstract

Technological advancements in education have led to major transformations, particularly with the implementation of the Merdeka Curriculum, which emphasizes learning flexibility, student-centered approaches, and educator autonomy in developing innovative teaching methods. One of its essential aspects is the integration of technology for managing educational data, including student health records. At SMP IT Mutia Rahma, biannual student health monitoring has generated a growing volume of data, making it difficult to identify students experiencing psychological challenges. Adolescent mental health problems—such as learning stress, anxiety, and social pressure—can negatively affect academic performance if left unaddressed. This study aims to group students based on their mental health conditions to support more effective intervention strategies. The K-Means Algorithm, a data mining technique for clustering data by similarity, was employed to analyze student health data. The results show that in a three-cluster model, Cluster 2 represents students in a stable condition characterized by high resilience and low counseling needs, indicating good mental health and academic engagement. Meanwhile, Clusters 1 and 3 include students requiring further attention and support. This research demonstrates that the K-Means Algorithm can serve as an effective tool in identifying and categorizing student mental health conditions to improve school-based health management and early intervention programs.

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