Jurnal Ilmu Komputer Ruru (JIKR) dengan e-ISSN : 3046-3714 dengan SK No.30467314/II.7.4/SK.ISSN/03/2024 merupakan jurnal ilmiah dalam sistem informasi/teknologi informasi yang berisi literatur ilmiah tentang kajian penelitian murni dan terapan dalam sistem informasi/teknologi informasi dan tinjauan publik terhadap perkembangan teori, metode dan ilmu terapan yang terkait dengan subjek. Jurnal Ilmu Komputer Ruru (JIKR) diterbitkan oleh Yayasan Grace Berkat Anugerah. Redaksi mengajak peneliti, praktisi, dan mahasiswa untuk menulis perkembangan keilmuan di bidang yang berkaitan dengan sistem informasi/teknologi informasi. Jurnal Ilmu Komputer Ruru (JIKR) diterbitkan 2 (dua) kali setahun pada bulan Januari dan Juli. Jurnal ini berisi artikel penelitian dan kajian ilmiah.
Model Simulasi Interaktif untuk Pelatihan Reviewer Akademik Berbasis AI dan Visualisasi Benchmarking
Penelitian ini bertujuan untuk mengembangkan dan menguji efektivitas Model Simulasi Interaktif untuk Pelatihan Reviewer Akademik berbasis Artificial Intelligence (AI) dan visualisasi benchmarking dalam meningkatkan kompetensi penilaian artikel ilmiah. Metode penelitian menggunakan pendekatan Research and Development (R&D) yang dipadukan dengan desain kuasi-eksperimen. Subjek penelitian terdiri atas calon reviewer akademik dari berbagai perguruan tinggi yang dibagi ke dalam kelompok eksperimen dan kelompok kontrol. Instrumen yang digunakan meliputi rubrik penilaian artikel ilmiah, tes kompetensi reviewer, lembar observasi, dan angket persepsi pengguna. Data dianalisis menggunakan uji statistik deskriptif dan inferensial untuk mengukur perbedaan peningkatan kompetensi antar kelompok. Hasil penelitian menunjukkan bahwa model simulasi interaktif berbasis AI secara signifikan meningkatkan kemampuan peserta dalam aspek identifikasi kebaruan, ketepatan metodologi, konsistensi sitasi, dan objektivitas rekomendasi. Fitur visualisasi benchmarking membantu peserta membandingkan hasil penilaian mereka dengan standar reviewer berpengalaman, sehingga memperkuat refleksi kritis dan akurasi evaluasi. Peningkatan skor kompetensi pada kelompok eksperimen lebih tinggi dibandingkan kelompok kontrol. Simpulan penelitian ini menunjukkan bahwa Model Simulasi Interaktif berbasis AI dan visualisasi benchmarking efektif sebagai inovasi pelatihan reviewer akademik. Model ini tidak hanya meningkatkan kualitas penilaian ilmiah, tetapi juga mendukung standarisasi dan transparansi proses review di lingkungan akademik
Copyright (c) 2025 Andi Pratama, Liske Lasmian Napitupul (Author) https://creativecommons.org/licenses/by-sa/4.0
Integrasi Bahasa Daerah dalam Antarmuka Sistem Informasi Desa: Studi UX Multibahasa dan Lokalitas
Penelitian ini bertujuan untuk menganalisis dan merancang integrasi bahasa daerah dalam antarmuka Sistem Informasi Desa (SID) guna meningkatkan pengalaman pengguna (User Experience/UX) berbasis multibahasa dan lokalitas. Studi ini menggunakan pendekatan mixed-method dengan desain eksploratori-sekuensial yang melibatkan analisis kebutuhan pengguna, perancangan prototipe antarmuka multibahasa, serta pengujian usability kepada perangkat desa dan masyarakat. Instrumen penelitian meliputi kuesioner System Usability Scale (SUS), wawancara semi-terstruktur, observasi penggunaan sistem, dan analisis komparatif sebelum dan sesudah integrasi bahasa daerah. Hasil penelitian menunjukkan bahwa integrasi bahasa daerah pada elemen navigasi, label menu, dan pesan sistem secara signifikan meningkatkan pemahaman pengguna, menurunkan tingkat kesalahan input, serta mempercepat waktu penyelesaian tugas. Nilai rata-rata SUS meningkat dari kategori “cukup” menjadi “baik” setelah penerapan antarmuka multibahasa berbasis lokalitas. Selain itu, pengguna menunjukkan tingkat kepercayaan dan keterlibatan yang lebih tinggi terhadap sistem. Temuan ini menegaskan bahwa pendekatan UX berbasis konteks budaya dan linguistik lokal berkontribusi positif terhadap efektivitas dan inklusivitas layanan digital desa. Penelitian ini merekomendasikan pengembangan standar desain antarmuka SID yang adaptif terhadap keberagaman bahasa daerah sebagai strategi transformasi digital yang berorientasi pada masyarakat
Copyright (c) 2025 Volvo Sihombing (Author) https://creativecommons.org/licenses/by-sa/4.0
Audit Keamanan Template OJS terhadap Potensi Eksploitasi Metadata dan Tampilan Dinamis
Penelitian ini bertujuan untuk mengaudit keamanan template Open Journal Systems (OJS) terhadap potensi eksploitasi metadata dan manipulasi tampilan dinamis yang dapat berdampak pada integritas informasi jurnal. Metode yang digunakan adalah pendekatan audit keamanan berbasis analisis kerentanan, pengujian input metadata, simulasi serangan injeksi pada elemen dinamis, serta evaluasi konfigurasi template dan sanitasi data. Pengujian dilakukan pada beberapa skenario manipulasi metadata, termasuk penyisipan skrip, perubahan struktur tampilan, dan eksploitasi parameter dinamis. Hasil penelitian menunjukkan bahwa kelemahan utama terletak pada validasi input yang tidak konsisten, mekanisme escaping yang kurang optimal, serta konfigurasi template yang memungkinkan interpretasi kode berbahaya. Temuan penting mengindikasikan bahwa eksploitasi metadata dapat memengaruhi tampilan halaman, mengganggu integritas konten, dan berpotensi membuka celah serangan lanjutan. Simpulan penelitian menegaskan perlunya penerapan sanitasi input yang ketat, pembaruan template secara berkala, serta penguatan mekanisme keamanan sisi server untuk meminimalkan risiko eksploitasi dan menjaga keandalan sistem publikasi ilmiah.
Copyright (c) 2025 Rahmat Syahputra, Polmetra Polmetra, Fricles A. Sianturi (Author) https://creativecommons.org/licenses/by-sa/4.0
Pengembangan Sistem Review Otomatis Berbasis Logika Visual untuk Artikel Ilmiah Multidisiplin
Penelitian ini bertujuan mengembangkan sistem review otomatis berbasis logika visual untuk meningkatkan kualitas, konsistensi, dan efisiensi proses penilaian artikel ilmiah multidisiplin. Tantangan utama dalam review artikel multidisiplin adalah perbedaan struktur penulisan, terminologi, serta standar evaluasi yang sering menimbulkan subjektivitas dan inkonsistensi. Metode penelitian menggunakan pendekatan pengembangan sistem dengan integrasi pemrosesan bahasa alami, aturan logika visual, dan analisis pola dokumen. Dataset artikel ilmiah dari berbagai bidang dianalisis melalui tahap praproses teks, ekstraksi fitur struktural dan semantik, serta pemodelan logika visual untuk mengidentifikasi kelengkapan komponen artikel, kesesuaian format, dan potensi anomali. Sistem kemudian diuji melalui eksperimen komparatif terhadap proses review manual. Hasil penelitian menunjukkan bahwa sistem mampu meningkatkan konsistensi evaluasi, mempercepat proses penyaringan awal artikel, serta mengurangi kesalahan identifikasi struktur dokumen. Visualisasi logika yang dihasilkan membantu reviewer memahami hubungan antarbagian artikel secara intuitif. Simpulan penelitian menegaskan bahwa sistem review otomatis berbasis logika visual merupakan solusi efektif untuk mendukung proses evaluasi artikel ilmiah multidisiplin yang lebih objektif, sistematis, dan efisien.
Copyright (c) 2025 Fricles A. Sianturi (Author) https://creativecommons.org/licenses/by-sa/4.0
Model Visualisasi Metadata Jurnal Ilmiah Berbasis AI untuk Deteksi Duplikasi dan Ketidakkonsistenan
Penelitian ini bertujuan mengembangkan model visualisasi metadata jurnal ilmiah berbasis kecerdasan buatan (AI) untuk mendeteksi duplikasi dan ketidakkonsistenan data secara otomatis, cepat, dan akurat. Permasalahan utama dalam pengelolaan jurnal ilmiah adalah tingginya potensi redundansi metadata, perbedaan format penulisan, serta inkonsistensi informasi yang dapat menurunkan kualitas pengindeksan dan integritas publikasi. Metode penelitian menggunakan pendekatan pengembangan sistem yang menggabungkan teknik pemrosesan bahasa alami, pencocokan pola berbasis pembelajaran mesin, dan visual analytics. Dataset metadata jurnal dikumpulkan dari berbagai sumber, kemudian diproses melalui tahap normalisasi, ekstraksi fitur, dan pemodelan deteksi anomali. Model divisualisasikan dalam dashboard interaktif untuk memudahkan identifikasi pola duplikasi dan ketidaksesuaian data. Hasil penelitian menunjukkan bahwa model mampu meningkatkan akurasi deteksi duplikasi metadata secara signifikan, mempercepat proses verifikasi editorial, serta menurunkan tingkat kesalahan pencatatan metadata. Visualisasi yang dihasilkan membantu pengguna memahami hubungan data secara intuitif dan mendukung pengambilan keputusan berbasis bukti. Simpulan penelitian menegaskan bahwa integrasi AI dan visualisasi metadata merupakan solusi efektif untuk meningkatkan kualitas pengelolaan jurnal ilmiah, efisiensi kerja editorial, serta konsistensi data publikasi.
Copyright (c) 2025 Fricles A. Sianturi, Ismail M. Sianturi (Author) https://creativecommons.org/licenses/by-sa/4.0
PEMANFAATAN ALGORITMA APRIORI UNTUK PENINGKATAN EFISIENSI PRODUKSI AKUAKULTUR DI SUMATERA UTARA
Aquaculture is a crucial sector for supporting food security and the economy in North Sumatra Province. However, aquaculture production in this region faces several challenges, such as low production efficiency and suboptimal resource utilization. This study aims to optimize aquaculture production by applying the Apriori Algorithm and Association Rule Method. A case study was conducted at the North Sumatra Provincial Department of Marine Affairs and Fisheries. Aquaculture production data, including fish species, feed, environmental conditions, and farming techniques, were collected and analyzed using the Apriori Algorithm. This algorithm was used to identify significant patterns and relationships among these factors that could enhance production. The results of the study show that the application of the Apriori Algorithm successfully identified the most effective factor combinations for improving aquaculture production. For instance, it was found that a certain combination of feed types with specific environmental conditions resulted in a significant increase in production. These findings provide valuable insights for strategic decision-making in the management and development of the aquaculture sector in North Sumatra. Thus, this research contributes to the sustainability and productivity improvement of aquaculture in the region, and offers a scientific basis for more effective planning and policy implementation in the aquaculture sector
Application of Apriori Algorithm with associative rules
Copyright (c) 2024 Fricles A Sianturi (Author) https://creativecommons.org/licenses/by-sa/4.0
PREDIKSI PENETAPAN TARIF PENERBANGAN MENGGUNAKAN AUTO-ML DENGAN ALGORITMA RANDOM FOREST
With so many airlines competing with each other, airlines are competing to become the consumer/market's main choice, but to achieve this, there is no airline strategy that can predict the price of airline tickets according to market needs. To meet the needs of airlines, we need a way to determine the price of airline tickets according to market needs with the help of the influence of technology and information. This research method was carried out using Google Collaboratory as a media to create a data model with the Random Forest, Logistic Regression and Gradient Boosting Regressor algorithms. In this study, the model that produced the highest R2 value and the lowest RMSE was a random forest with an R2 value of 83.91% and an RMSE of $175.9. However, from the three models, Random Forest got a change in accuracy of 1.96% to 85.87. To assist in predicting the determination of flight fares, airline companies can more easily and be alert to determine flight fares that are in accordance with the market. Therefore, Random Forest can be declared better than Logistic Regression and Gradient Boosting models. The Random Forest model that has been created can be used to predict in real-time using Machine Learning.
Copyright (c) 2025 Ruli Herdiana (Author) https://creativecommons.org/licenses/by-sa/4.0
EVALUASI PENGALAMAN PENGGUNA MAHASISWA TERHADAP SISTEM INFORMASI SIASAT: PENDEKATAN DENGAN USER EXPERIENCE QUESTIONNAIRE
This research aims to analyze student user experience on the Satya Wacana Information System (SIASAT) using the User Experience Questionnaire (UEQ). UEQ is a measurement method from the aspect of its use and the aspect of the experience, including a compressive impression using a questionnaire scale. The UEQ has 26 questions that must be filled out by respondents, where the questions cover 6 aspects, including attractiveness, efficiency, perspicuity, dependability, stimulation, and novelty. The UEQ questionnaire in this study used data from 54 active SWCU student respondents who understood the use of the Satya Wacana Academic Information System (SIASAT) well. The final results of the tests carried out obtained data for the scale of attractiveness, efficiency, dependability, and stimulation to get a normal evaluation category. Meanwhile, the novelty scale gets a negative evaluation category and the perspicuity scale gets a positive evaluation category. Then for the results of the benchmark evaluation, the majority got the Bad category which includes a scale of attractiveness, efficiency, dependability, stimulation, and novelty. Only one scale that gets the Above Average category (Good Enough) is perspicuity.
Satya Wacana Information System (SIASAT)
Copyright (c) 2025 Saeful Anwar (Author) https://creativecommons.org/licenses/by-sa/4.0
MEMAHAMI PASAR KUE TRADISIONAL DJAJE MELALUI ANALISIS STP: SEGMENTATION, TARGETING, POSITIONING
In this study, the digital marketing strategy uses STP (Segmentation, Targeting, Positioning) analysis by determining target consumers such as those aged 22-60 years who are in the Denpasar and surrounding areas and have an interest in religious events such as weddings, celebrations, and others. Implementation of the digital marketing strategy by implementing it on existing digital platforms such as Facebook, Instagram, WhatsApp Business, website, and Google Business Profile. Another strategy used is to advertise on Facebook and Instagram as well as websites. In addition to using the online method, offline also adds the number of resellers. The results of the research conducted after applying STP (Segmentation, Positioning, Targeting) analysis on the various platforms used, namely the increasing number of sales from October 2021 to March 2022.
Analysis STP (Segmentation, Targeting, Positioning)
Copyright (c) 2025 Nurul Baikhaq (Author) https://creativecommons.org/licenses/by-sa/4.0
MENINGKATKAN MOTIVASI BELAJAR SISWA SMA MENGGUNAKAN MEDIA BELAJAR INSTRUCTIONAL GAMES
Games that are interesting and fun to play make the interest of students to prefer playing games rather than studying. Submission of teaching materials in a conventional way will be boring to be followed by students in class. It is necessary to improve teaching methods that are able to attract students' interest in learning to be motivated in participating in teaching and learning activities. The design of interactive learning media with the instructional games model aims to increase the interest of students so that they can receive teaching materials in a good and fun way. The method used in this research is Research and Development (R&D). To analyze students' learning motivation, a field survey questionnaire was used which was given to 33 students of Class XI SMA Negeri 1 Plered. There has been an increase of 8.22%, where the initial motivation of students is at the percentage of 62.88% increasing to a percentage of 71.10%, which can also be interpreted that the use of interactive instructional games learning media is able to increase student learning motivation.
Copyright (c) 2024 Fauzi Faisal Nugraha, Eryan Ahmad Firdaus (Author) https://creativecommons.org/licenses/by-sa/4.0
OPTIMALISASI PENJUALAN KUE TRADISIONAL DJAJE DENGAN PENDEKATAN STP
Djaje is a traditional cake business that has been established in 2017. The products sold by Djaje are various wet snacks. The initial strategy used was only offline, such as leaving cakes to resellers, but as the number of competitors increased, Djaje's sales decreased. This study uses a qualitative descriptive method by explaining the results obtained using analysis STP (Segmentation, Targeting, Positioning). The purpose of this study was to determine the results of implementing digital marketing strategies in improving traditional cakes. Results implementation of the implemented strategy by adjusting the content of photos, descriptions, posts, and advertisements using analysis STP (Segmentation, Targeting, Positioning) as a basis. By using various digital platforms to reach more potential consumers, Djaje has succeeded in making cake sales increase in sales from October 2021 to March 2022
Copyright (c) 2024 Ismali Marzuki Sianturi (Author) https://creativecommons.org/licenses/by-sa/4.0
Copyright (c) 2025 Asriyanik (Author) https://creativecommons.org/licenses/by-sa/4.0
APLIKASI PENILAIAN KINERJA PERAWAT UNGGULAN MENGGUNAKAN PENDEKATAN SAW
Evaluating nurse performance is a critical aspect of human resource management in the healthcare sector. This study aims to develop a decision support system that assists management in determining the best-performing nurses using the Simple Additive Weighting (SAW) method. SAW is chosen for its simplicity and capability to handle various evaluation criteria. In this research, nurse performance data were collected from multiple sources, including supervisory reports, patient feedback, and peer assessments. Each evaluation criterion was assigned a weight according to its importance, and the nurse performance scores were calculated using the SAW formula. The process involves normalizing the criteria scores and then aggregating them to generate a composite performance score for each nurse, The main challenges addressed in this study include the subjectivity and inconsistency often associated with manual performance evaluations. By employing the SAW method, the study seeks to minimize biases and ensure a fair assessment of all nurses based on predefined and weighted criteria. This method was chosen because it can perform a ranking process based on criteria and weights and is able to determine the best alternative. System design with Context Diagram, HIPO, DAD and ERD. Application results are nurse reports, overall selection and selection of the best nurses. The results of the functionality test are proven to be successful and the Validity Test has been proven to be 100% valid.
IMPLEMENTASI ALGORITMA DECISION TREE C4.5 DENGAN IMPROVISASI MEAN DAN MEDIAN PADA DATASET NUMERIK
A decision tree algorithm or commonly called a decision tree is a classification method of data mining. The decision tree has one type of algorithm model, namely the C4.5 algorithm. The C4.5 decision tree algorithm is easy to understand because it has a tree-like structure in general. The C4.5 algorithm in handling quantitative data is often less efficient and effective. So to minimize information loss and time complexity, we can improvise the dataset on the numeric attributes when Preprocessing the data. Improvisation is done by using the mean and median on the numerical attributes to get a threshold value for implementing the C4.5 algorithm from the training data. Evaluation of the system used in this study uses a confusion matrix. Confusion matrix as a benchmark for testing the classification method using data testing. In this study, the dataset is partitioned into three scenarios. In scenario 1 with 70% training data and 20% testing data, the highest accuracy is 75%. The improvisation of the mean and median on the numerical attributes in the C4.5 algorithm can use in this scenario.
Copyright (c) 2025 Bagus Sudirma (Author) https://creativecommons.org/licenses/by-sa/4.0
PERBANDINGAN ALGORITMA C5.0 DAN REGRESI LINEAR UNTUK PREDIKSI KELULUSAN MAHASISWA
Technological advances supported by human knowledge have a very good influence on data and information storage technology, including in predicting student graduation (Graduation Prediction) on time, by applying several existing algorithms. In this study, researchers used the C5.0 Algorithm and Linear Regression. The concept of the research is to compare two algorithms, namely C5.0 and Linear Regression to the case of graduating students on time. Based on the length of study, students who graduated correctly amounted to 651 (91%) with a male gender of 427 students and a female gender of 224 students while those who did not pass (late) correctly amounted to 64 (9%) with a male gender totaling 53 students and female gender totaling 11 students from 2017-2020. Comparison results The R2 score from the C5.0 algorithm reached 96.85% (training) and 93.72% (testing) while the R2 score from the Linear Regression reached 33.31% (training) and 40.30% (testing).
Copyright (c) 2024 Petti Sijabat, Agustina Simangunsong (Author) https://creativecommons.org/licenses/by-sa/4.0
EVALUASI KINERJA METODE ANALYTICAL HIERARCHY PROCESS (AHP) DALAM PENELUSURAN ASET PADA LINGKUNGAN BISNIS STUDI KASUS PADA INDUSTRI PERBANKAN
Asset tracing is an important activity in business management, especially in the banking industry where asset management has direct implications for a company's financial health and sustainability. In this context, this study aims to evaluate the performance of the Analytical Hierarchy Process (AHP) method in asset tracing, with case studies in the banking industry. This study adopts a quantitative approach by applying AHP in selecting asset tracing priorities in the banking business environment. Asset-related data, such as value, risk, and strategic importance, are collected and analyzed to support the decision-making process. Furthermore, AHP is applied to determine the relative weighting of the relevant criteria and generate a rating for each asset based on the assessment of those criteria. The results of the performance evaluation of the AHP method in asset tracing in the banking industry show that this approach provides a systematic and structured framework for decision making. By using AHP, asset ratings can be determined more objectively and transparently, reducing the risk of errors and misappropriations in resource allocation. In addition, AHP allows management to prioritize asset tracing based on the company's business objectives and strategic needs. In conclusion, the performance evaluation of the AHP method in asset tracing in the business environment, especially in the banking industry, shows the potential to improve the efficiency and effectiveness of asset management. With a structured, data-driven approach like AHP, companies can optimize resource usage and reduce the risk of loss caused by assets that are not strategically optimized.
Copyright (c) 2024 Jurnal Ilmu Komputer Ruru https://creativecommons.org/licenses/by-sa/4.0
PENGEMBANGAN MODEL FUZZY TSUKAMOTO UNTUK EVALUASI KELAYAKAN DAN KEEFEKTIFAN PENERAPAN KELUARGA BERENCANA ALAMI (KBA) DALAM KONTEKS KESEHATAN REPRODUKSI
The implementation of Natural Family Planning (KBA) has become an increasingly considered approach in an effort to improve reproductive health. However, evaluation of the feasibility and effectiveness of KBA implementation requires a systematic and comprehensive approach. In this study, we introduce the development of the Fuzzy Tsukamoto model as a tool to evaluate the feasibility and effectiveness of implementing KBA in the context of reproductive health. The Fuzzy Tsukamoto model is used to evaluate various factors that affect the feasibility and effectiveness of implementing KBA, including social, economic, health, and user satisfaction aspects. The fuzzy approach allows us to deal with uncertainty and complexity in the data associated with these evaluations, as well as to integrate expert knowledge into the decision-making process. This research will cover the stages of Fuzzy Tsukamoto's model development, including the identification of input and output variables, the establishment of fuzzy rules, and the implementation of a fuzzy inference system. We will collect data from KBA-related case studies or surveys to train and test the developed model. In addition, we will also perform a sensitivity analysis to evaluate the reliability and robustness of the model to parameter variations. It is hoped that the results of this study will provide valuable guidance for reproductive health practitioners, policy makers, and other relevant parties in assessing and improving the implementation of KBA. By utilizing the Fuzzy Tsukamoto model, it is hoped that the feasibility and effectiveness evaluation of KBA can be carried out in a more holistic and trustworthy manner, thus encouraging efforts towards better reproductive health overall.
Penggabungan Mapbox dan Google Maps dalam Sistem Informasi Geografis untuk Memperkaya Fitur Tambahan
The use of geographic information systems (GIS) is increasingly widespread in various applications that utilize geographic data to support decision making and spatial analysis. In GIS development, integration between various mapping platforms is key to enriching features and meeting diverse user needs. This paper discusses the merger between Mapbox and Google Maps in a geographic information system to add additional features that enrich the user experience. Mapbox and Google Maps are two popular and powerful mapping platforms, each with its own advantages and disadvantages. In this study, we propose the integration of these two platforms in one geographic information system. This integration allows users to access a wide array of features and data provided by Mapbox and Google Maps simultaneously, thereby increasing the flexibility and analytical capabilities of GIS. By combining the strengths of Mapbox and Google Maps, the developed geographic information system can present a variety of geographic information more comprehensively and accurately. Users can benefit from excellent features from both platforms, such as rich and interactive data visualization, accurate navigation, and integration with other services such as public transportation and location search. It is expected that the incorporation of Mapbox and Google Maps in this geographic information system can make a positive contribution in the development of location-based applications and support various activities that require efficient and effective analysis and visualization of geographic data.
PENERAPAN DIGITAL SIGNATURES UNTUK OTENTIKASI DAN KEAMANAN DATA BERBASIS LOKASI GPS PADA APLIKASI MOBILE
In an era where mobile applications are becoming increasingly important in everyday life, data security and authentication is an aspect that cannot be ignored. Especially in the context of applications that utilize GPS location information, the need to ensure the authenticity and integrity of data becomes crucial. In this study, we introduce an approach to implementing digital signatures to improve data security and authentication in mobile applications based on GPS location. The digital signatures method is used to sign location data generated by GPS devices on mobile applications. This digital signing process allows verification of the authenticity and integrity of that location data. In addition, digital signatures also make it possible to verify the identity of the user or entity that generated the data, thus preventing the possibility of data forgery or other security attacks. This research will include the implementation of a digital signatures-based security system on mobile applications that utilize GPS location services. We will analyze the performance of the system in ensuring the authenticity and integrity of data, as well as measure the overhead incurred by the digital signing process. In addition, we will also test the security of the system by testing for possible attacks or security breaches that may occur. The results of this study are expected to make a significant contribution in strengthening data security and authentication in location-based mobile applications, as well as provide guidance for the practical implementation of digital signatures in this context. Thus, mobile applications that utilize GPS location information can operate with a higher level of security, increasing user confidence in the application.
Optimizing K-Means Algorithm With Elbow And Silhouette Methods For National Exam Score Data Clustering
The national examination is an evaluation system for basic education standarts that supports student graduation. In accordance with the regulations of the Government of the Republic Indonesia, the evaluation of learning outcomes aims to evaluate the achievement of national graduate students. As the data obtained by the author, namely the National Vocational Exam Value Data for the Vocational High School in Central Java Province for the class of 2019. But the data displayed is still random and less information. Then data mining techniques are needed to classify which schools is carried out using the k-means clustering method and using elbow and silhouette optimization, with optimum k obtained K=3 and K=2 with calculations using RStudio tools. It is expected to produce the best cluster for the grouping