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Jurnal Sistem Informasi dan Ilmu Komputer
Published by International Forum of Researchers and Lecturers
ISSN : 29865158     EISSN : 29864976     DOI : 10.59581
Core Subject : Science,
Computer Science & IT
Jurnal Sistem Informasi dan Ilmu Komputer berfokus pada publikasi hasil penelitian, kajian konseptual, dan pengembangan keilmuan di bidang Sistem Informasi dan Ilmu Komputer. Jurnal ini bertujuan menjadi media diseminasi ilmiah bagi akademisi, peneliti, dan praktisi dalam pengembangan serta penerapan teknologi informasi yang inovatif dan berkelanjutan. Ruang Lingkup Ruang lingkup jurnal mencakup, namun tidak terbatas pada, topik-topik berikut: Bidang Sistem Informasi Analisis dan Perancangan Sistem Informasi Manajemen Sistem Informasi Sistem Informasi Manajemen Sistem Enterprise (ERP, SCM, CRM) Sistem Pendukung Keputusan Business Intelligence dan Data Warehouse Tata Kelola Teknologi Informasi Audit dan Keamanan Sistem Informasi E-Government dan E-Business Bidang Ilmu Komputer Rekayasa Perangkat Lunak Kecerdasan Buatan (Artificial Intelligence) Machine Learning dan Deep Learning Data Mining dan Big Data Jaringan Komputer dan Keamanan Jaringan Internet of Things (IoT) Pengolahan Citra dan Visi Komputer Sistem Terdistribusi dan Cloud Computing Human-Computer Interaction (HCI)
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 169 Documents
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Implementasi Data Mining untuk Menentukan Pola Penjualan pada Coffee Shop Menggunakan Algoritma Apriori: Studi Kasus: Menrabic Coffee Shop
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 3 (2025): Agustus : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i3.5624

Abstract

Currently, the use of data mining technology has become essential in enhancing business management efficiency, including in the trending coffee shop industry. Data mining allows business owners to analyze sales information in depth, enabling more accurate decision-making regarding inventory management, promotions, and sales strategies. This study aims to implement the Apriori algorithm to analyze sales data at Menrabic Coffee Shop. The Apriori algorithm is used to discover association patterns or relationships between products frequently purchased together by customers, which can assist management in providing inventory that aligns with customer preferences. The research method illustrates the detailed implementation process of the Apriori algorithm, starting from sales data collection, data cleaning, programming, and analysis of the results. The implementation uses web programming languages such as HTML, CSS, MySQL, and JavaScript, while back-end logic is programmed with PHP. The results of applying this algorithm reveal the most popular sales patterns among customers, providing valuable insights for management to improve operational performance and customer satisfaction. Therefore, this study demonstrates that applying data mining with the Apriori algorithm can be an effective tool for understanding consumer behavior and supporting data-driven decision-making at Menrabic Coffee Shop. By utilizing these insights, management can optimize inventory, enhance sales strategies, and ultimately increase overall business efficiency.
Penerapan Algoritma K-Nearest Neighbors (K-NN) dan Naïve Bayes untuk Menentukan Pemilihan Penerima Bantuan Sosial Berdasarkan Ekonomi Masyarakat
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 3 (2025): Agustus : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i3.5646

Abstract

One approach the government employs to decorate public welfare, mainly among low-income families, is through social help initiatives. however, the subjectivity inside the choice process regularly ends in mistargeting all through implementation. This observe objectives to apply the ok-Nearest Neighbor (ok-NN) and Naive Bayes algorithms inside a decision support device to perceive eligible recipients based on community statistics. The ok-NN algorithm determines similarity by calculating the Euclidean distance among new and current facts, whilst the Naive Bayes set of rules utilizes a probabilistic method based at the likelihood of attribute incidence inside each elegance. Key criteria considered consist of household income, employment kind, number of dependents, housing conditions, and asset possession. Experimental consequences reveal that each algorithms are powerful in as it should be classifying eligibility for help, with k-NN barely outperforming Naive Bayes. therefore, the combination of these algorithms can support stakeholders in making extra goal and efficient selections regarding the distribution of social useful resource.
Peran Chatbot dalam Membentuk Interaksi Sosial, Fandom, dan Identitas Pengguna di Media Sosial
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i4.5795

Abstract

The rapid development of artificial intelligence has encouraged the widespread use of chatbots on social media platforms, transforming patterns of digital communication and interaction. This study aims to examine the role of chatbots in shaping social interaction, fandom dynamics, and users’ digital identities within contemporary online culture. The research employs a literature review approach using grounded theory as an analytical framework to identify patterns, themes, and emerging concepts from relevant academic publications published between 2021 and 2025. Articles were collected through academic databases and systematically selected based on predefined inclusion and exclusion criteria. The findings indicate that chatbots have shifted from being purely functional technological tools to becoming cultural actors that influence emotional engagement, community formation, and identity expression in digital spaces. Chatbots contribute to creating perceived emotional closeness, strengthening fandom interactions, and facilitating self-expression, particularly within popular culture and creative industries. However, the study also highlights several challenges, including emotional dependency, algorithm-driven homogenization of preferences, gender bias, and aggressive behavior in human–machine interactions. Cultural context plays a significant role in shaping user acceptance and interpretation of chatbots. These findings imply that chatbot development and implementation should consider not only technical efficiency but also social, psychological, and ethical dimensions to ensure responsible and inclusive digital interaction.
Data Mining Pengelompokkan Jenis Penyakit pada Balita Berdasarkan Usia Menggunakan Metode Clustering
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 4 (2025): Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i4.5837

Abstract

Toddlers are a vulnerable age group to various types of diseases due to their immune systems that are still developing. Limited utilization of medical record data and the lack of structured information regarding disease patterns in toddlers based on age and causative factors have resulted in suboptimal prevention and treatment efforts. Therefore, an approach is needed to systematically classify toddler disease data. This study aims to apply data mining techniques using the clustering method with the K-Means algorithm to group types of diseases in toddlers based on age and causative factors. The variables used in this study include toddler age, type of disease, and causative factors. The data were obtained from RSUD Dr. R. M. Djoelham Binjai and processed using MATLAB software with three clusters. The results show that the K-Means algorithm successfully groups toddler disease data into three clusters with different characteristics. The first cluster is dominated by toddlers aged 0–11 months with appendicitis caused by genetic factors. The second cluster is dominated by toddlers aged 1–3 years with diarrhea caused by environmental factors and has the largest number of members. Meanwhile, the third cluster is dominated by toddlers aged 0–11 months with sore throat caused by environmental factors. The clustering results indicate a relationship between toddler age, disease type, and causative factors, which can be used as supporting information for decision-making in the prevention and treatment of toddler diseases.
Perancangan Aplikasi Jadwal dan Laporan Kunjungan Kerja pada Bappelitbang
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 4 (2025): Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i4.5858

Abstract

The Planning, Research, and Development Agency (BAPPELITBANG) has an important role in supporting regional development planning and evaluation. One of the main activities of this agency is the coordination of working visits with external agencies or institutions. The process of managing schedules and work visit reports is currently still carried out manually, causing obstacles such as delays in information, duplicate schedules, and lack of integration of report data. This research aims to design a web-based application that is able to manage work visit schedules in a structured manner and facilitate the creation of visit reports digitally. The method used in this study is the Waterfall system development method which includes needs analysis, system design, implementation, and testing. The results of the study show that the application is able to display the visit schedule in real time, minimize schedule conflicts, and speed up the process of preparing work visit reports. Thus, this application makes a significant contribution in increasing the effectiveness and efficiency of the work visit administration process at BAPPELITBANG.
Evaluasi dan Perbandingan Metode Klasifikasi Support Vector Machine dan K-Nearest Neighbor untuk Prediksi Kompetensi Lulusan Perguruan Tinggi
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 4 (2025): Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i4.6032

Abstract

The world of work is an environment related to the work we are currently in. In other words, it is a place where various individuals perform an activity. The quality of college graduates is not only seen in terms of high or good grades / GPA. There are many other considerations, where large companies see a potential possessed by the person concerned. The dataset in this study was taken from student respondents about the world of work. One way to classify the influence of competence on the world of work in machine learning is to use datasets as training data so that performance testing can be carried out with the right classification method. From the results of the tests carried out, it is concluded that the results of the comparison are different, which shows the accuracy value of KNN which is around 96%, while the results of the SVM accuracy tested are 98%, so that the accuracy of SVM is better than KNN.
Sistem Pakar Berbasis Pengetahuan Menggunakan Metode Forward Chaining untuk Rekomendasi Peminatan Jurusan SMK
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 4 (2025): Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i4.6037

Abstract

The purpose of this scientific paper is to design and implement a knowledge-based expert system to assist students in determining their major specializations at Vocational High Schools (SMK) more objectively and accurately. A major problem frequently faced by SMK students is the mismatch in department selection caused by a lack of understanding regarding their own potential and the specific criteria of each competency. To address this issue, the system was developed using the Forward Chaining method as the inference engine. This method operates in a data-driven manner, beginning with the collection of facts such as interests, academic abilities, and psychological aspects, which are then matched against a Knowledge Base consisting of IF-THEN logical rules. Based on system testing results, the inference engine is capable of processing the list of facts to generate a specialization diagnosis for SMK students and provide the most relevant departmental recommendations, such as Computer and Network Engineering (TKJ), Accounting, Office Automation and Governance (OTKP), or Marketing. The research results indicate that the implementation of the Forward Chaining method is effective in accelerating the decision-making process and minimizing placement errors. This expert system is expected to serve as a tool for Guidance and Counseling (BK) teachers in providing appropriate career direction for students based on structured empirical data.
Perencanaan Strategis Sistem Informasi pada Wyndham Opi Hotel Palembang Desvilia Desvilia
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 4 No. 1 (2026): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v4i1.6038

Abstract

This research aims to design an Information Systems and Information Technology (IS/IT) strategic plan for Wyndham OPI Hotel Palembang to support operational efficiency and enhance the quality of five-star hotel services. The study applies the Ward and Peppard framework, supported by analytical methods including Value Chain,PEST,SWOT,Critical Success Factors (CSF), MOST and McFarlan Strategic Grid. Through these approaches, the current IS/IT condition, challenges, and opportunities for digital system development within the hotel environment were mapped. The analysis reveals that although the hotel has implemented technologies such as SiteMinder and the Rhapsody management system, there is a need to improve self-service check-in capabilities, strengthen IT infrastructure, and maximize digital technology utilization. The proposed strategy recommends the development of an integrated self check-in system, enhancement of network infrastructure, and employee training through an LMS platform. This strategic plan is expected to support the hotel’s digital transformation to remain competitive in the modern hospitality industry.
Perencanaan Strategis Sistem Informasi pada KR Hotel Palembang Abel De Lando
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 4 No. 1 (2026): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v4i1.6039

Abstract

This study aims to develop a strategic plan for Information Systems and Information Technology (IS/IT) at KR Hotel Palembang by applying the Ward and Peppard methodology. The analysis began with external environment assessment using the PEST framework and internal analysis through the MOST method and Value Chain model. The results were synthesized into a SWOT analysis to identify the organization's strengths, weaknesses, opportunities, and threats. From this, Critical Success Factors (CSF) were formulated to guide the determination of key information system needs. Application portfolio mapping was then conducted using the McFarlan Strategic Grid to classify systems based on their strategic impact. Findings indicate that KR Hotel has strong potential in leveraging digital technologies but faces challenges such as the absence of integrated systems across departments and limited IT training for staff. To address these issues, an integrated system named ZKBiolock was proposed, encompassing modules such as hotel management, financial management, customer relationship management (CRM), human resource training systems, digital promotion, and internal network monitoring and control. This strategic plan is supported by a comprehensive database design, network topology, human resource and infrastructure analysis, investment budgeting, and Return on Investment (ROI) evaluation. The proposed strategy aims to enhance the efficiency and effectiveness of the hotel's operational management.

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