Abstract:Abstract: Land registration in Indonesia often encounters challenges in transparency, data integrity, and centralized bureaucracy. Manual and semi-digital systems remain vulnerable to manipulation and delays. The National…
l Land Agency has initiated digitalization, but several challenges remain, particularly in ensuring transparency, efficiency, and security of land ownership data. Blockchain technology offers a potential solution through its decentralized and immutable characteristics. This study adopted a design and development method consisting of system analysis, requirements identification, architecture design, implementation, and black-box testing. The developed decentralized application (DApp) integrates smart contracts, NFTs, and IPFS to manage land certificates. Core functions such as minting, transfer, splitting, and self-custody were implemented and successfully tested, with all scenarios producing expected results. The findings demonstrate that blockchain integration can enhance security, reduce duplication, and streamline land administration. The study contributes a functional prototype with practical implications for modernizing land registration in Indonesia while identifying scalability and regulatory adaptation as areas for further research.
Keywords: blockchain; decentralized application; land registration; NFT; smart contract.
Abstract:Abstract: Ineffective drug demand management can lead to problems such as imbalanced drug distribution, excess stock, or shortages in community health centers. To address this, data mining can be utilized to support the…
planning and control process of drug inventory. Clustering techniques were chosen because they are able to group drug data based on certain characteristics, thus identifying stable and unstable drug supply patterns. This study aims to group drug data at Simpang Kawat Community Health Center in Jambi City, which can be used as a reference in planning drug needs in the next period. Data grouping is divided into three categories: slow-moving, medium-moving, and fast-moving. The research data includes attributes of drug name, initial stock, receipt, inventory, usage, and final stock, with a total of 1758 data sets, which were processed using the CRISP-DM framework through the RapidMiner application. Cluster quality evaluation was carried out using the Davies-Bouldin Index (DBI). The results showed that the K-Means algorithm obtained a DBI value of 0.175, smaller than K-Medoids which obtained a value of 0.354. Because a smaller DBI value indicates better cluster quality, K-Means provides more optimal clustering results than K-Medoids. Through these clustering results, community health centers can utilize drug cluster information to support more efficient drug procurement planning, as well as reduce the risk of excess or shortage of stock.
Keywords: data mining; clustering; k-means; k-medoids; davies-bouldin index
Abstract:The development of digital technology encourages universities to improve effectiveness and efficiency in data management, particularly in recording and reporting faculty performance. Some lecturers still face difficulties…
s in reporting their performance in the SISTER application due to challenges in locating documents scattered across various archives, which often leads to issues such as delays in reporting, low information accuracy, and lack of transparency of faculty performance documents for institutional needs. This study aims to optimize the digitalization of faculty performance documents based on cloud computing using the Agile Unified Process (AUP) approach, which is implemented in the development of a cloud-based system by utilizing Google Drive as the storage medium for digital faculty performance documents. The AUP methodology was chosen for its ability to combine flexible iterative and incremental principles, allowing the system to adapt quickly and continuously to user needs. Testing using Equivalence Partitioning, based on the functional and non-functional requirements of the system, has shown results in accordance with expectations.
Abstract:Abstract: The global transition towards sustainable food systems faces significant challenges in vegetarian food supply chains, including transparency issues, distribution inefficiencies, and quality verification problems.…
s. This research proposes VegeChain development, a decentralized marketplace ecosystem based on smart contracts designed to transform vegetarian food supply chains and accelerate Meatless, Balanced, Green (MBG) program adoption. Using mixed-method methodology integrating blockchain system design, stakeholder analysis, and economic simulation, this research develops a comprehensive technology framework combining blockchain transparency, smart contract automation, and sustainable tokenomics with novel mathematical models. The system implements dynamic pricing algorithms based on Automated Market Maker (AMM) mechanisms, multi-objective optimization for supply chain efficiency, and reputation-based consensus protocols. Simulation results demonstrate that VegeChain implementation can improve supply chain efficiency by 35%, reduce food waste by 28%, and increase consumer trust by 42% measured through validated stakeholder satisfaction surveys (n=456) using 5-point Likert scales with statistical significance p<0.001. Technical innovations include Byzantine Fault Tolerant consensus with 99.9% reliability, gas optimization achieving 67% cost reduction, and real-time quality verification algorithms with 98.7% accuracy.
Keywords: smart contracts; supply chain optimization; automated market makers; blockchain technology; sustainable tokenomics
Abstract:Abstract: The management of veterinary drug stocks at the Veterinary Clinic Technical Implementation Unit (UPTD) of the North Sumatra Province Plantation and Livestock Service faces obstacles in the form of discrepancies…
between supply and demand, resulting in excess stock and budget waste. Uncertain demand for drugs is a factor that complicates decision-making in stock provision. This study aims to optimize drug stock management using the Mamdani fuzzy logic method, which is capable of handling data uncertainty and modeling information linguistically. Three input variables are used, namely initial stock, demand, and number of visits, with the output being the final stock. The process involves fuzzification, inference based on IF–THEN rules, and defuzzification using the centroid method. The results show that the developed system has a good accuracy level with a MAPE value of 17.52%, which means that this model is effective in providing optimal and efficient drug stock recommendations in a veterinary clinic environment.
Keywords: fuzzy mamdani; optimization; animal drug stock.
Abstract:Giving awards is essential to motivate students; however, selecting outstanding students at the junior high school level is often conducted manually and subjectively, which can lead to unfairness and prolonged processing…
time. This study develops a Decision Support System (DSS) that integrates the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to support objective and transparent student selection. A quantitative descriptive approach was employed, with data collected through questionnaires, interviews, and documentation at two state junior high schools in Banjarmasin City. Seven assessment criteria were applied: attendance, behavior, uniform neatness, extracurricular participation, academic grades, competition achievements, and disciplinary records. AHP was used to determine the weight of each criterion, while TOPSIS ranked students based on these weights. The web-based system was developed using PHP and MySQL and evaluated using the Technology Acceptance Model (TAM). Results show that academic grades had the highest weight (28.5%), followed by attendance (22.3%) and competition performance (15.2%). The TAM evaluation yielded average scores of 4.32 for Perceived Ease of Use, 4.40 for Perceived Usefulness, 4.15 for Attitudes Towards Use, and 4.28 for Behavioral Intention to Use. The DSS produces accurate rankings, is well-received by users, and offers an efficient, fair, and replicable solution for data-driven educational governance in the digital era.
Abstract:Abstract: Teacher performance appraisal is a very important aspect in improving the quality of education today, but often occurs during the assessment process of subjectivity constraints and lack of a structured system,…
in this study aims to build a data structure modeling and facilitate the school MAS Islamiyah Hessa Air Genting in the assessment to determine the best teacher transparently and measurably by using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm. The TOPSIS method was chosen because it is able to provide ranking results based on the closeness of alternatives to the ideal solution. In this modeling, assessment criteria data such as pedagogical, professional, personality, social competencies, as well as other indicators such as teacher discipline and achievement are modeled structurally in a relational database. The results show that the designed data structure is able to support the decision-making process efficiently and objectively.
Keywords: data structure; decision support system; teacher assessment; topsis; ranking.
Abstrak: Penilaian kinerja guru merupakan aspek yang sangat penting dalam peningkatan mutu pendidikan saat ini, namun sering terjadi saat proses penilaian kendala subjektivitas dan kurangnya sistem yang terstruktur, dalam penelitian ini bertujuan untuk membangun pemodelan struktur data serta mempermudah pihak sekolah MAS Islamiyah Hessa Air Genting dalam penilaian untuk menentukan guru terbaik secara transparan dan terukur dengan menggunakan algoritma Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Metode TOPSIS dipilih karena mampu memberikan hasil perankingan berdasarkan kedekatan alternatif terhadap solusi ideal. Dalam pemodelan ini, data kriteria penilaian seperti kompetensi pedagogik, profesional, kepribadian, sosial, serta indikator lain seperti kedisiplinan dan prestasi guru dimodelkan secara terstruktur dalam basis data relasional. Hasil penelitian menunjukkan bahwa struktur data yang dirancang mampu mendukung proses pengambilan keputusan secara efisien dan objektif.
Kata kunci: struktur data; topsis; penilaian guru; sistem pendukung keputusan; perangkingan
Abstract:Abstract: The development of information technology encourages businesses to take over digital systems in business operations, even in the sales process. The Point of Sales (POS) system is the leading solution for recording…
ing transactions, managing stock, and creating sales reports efficiently. This study aims to develop a POS application based on a website and make it easier for administrators to manage sales transactions, making them faster and more efficient. This system is made with a structured Agile Development method, requirements, design, development, testing, deployment, and implementation. The framework used is the Laravel framework, with system testing conducted using BlackBox. The test results show that the system is on track and that the efficiency of the transaction and reporting process can be increased. A web-based basis allows users to manage their business more easily in real time because this application is flexible and can be used on various devices.
Keywords: agile model;laravel;point of sales; websites
Abstrak: Pengembangan teknologi informasi mendorong bisnis untuk mengambil alih sistem digital dalam operasi bisnis, bahkan dalam proses penjualan. Sistem Point of Sales (POS) adalah solusi utama untuk merekam transaksi, mengelola stok dan membuat laporan penjualan secara efisien. Tujuan dari penelitian ini adalah untuk mengembangan aplikasi POS berdasarkan situs web dan memudahkan administrator dalam mengelola transaksi penjualan, membuatnya lebih cepat dan lebih efisien. Sistem ini dibuat dengan metode Agile Development yang terstruktur, requirement, design, development, testing, deployment, dan implementation serta kerangka kerja yang digunakan yaitu framework Laravel dengan pengujian sistem menggunakan Blackbox. Hasil pengujian menunjukkan bahwa sistem berada di jalur dan bahwa efisiensi proses transaksi dan pelaporan dapat meningkat. Dengan berbasis web memungkinkan pengguna untuk lebih mudah mengelola bisnisnya secara real time, karena aplikasi ini fleksibel melalui berbagai perangkat.
Kata kunci: model agile;laravel;point of sales;website
Abstract:Abstract: The Ministry of Education, Culture, Research, and Technology, has developed guidelines for the Internal Quality Assurance System or known as SPMI, that is being implemented through the Internal Quality Audit (IQA)…
QA) with the PPEPP cycle, namely Determination (P), Implemen-tation (P), Evaluation (E), Control (P), and Improvement (P). Some universities have implemented IQA with system. The problem is that the system does not line well with the PPEPP cycle, which results in unsatisfactory audit results. The purpose of this study is to evaluate how well the university-owned AQI system features in line the PPEPP cycle and to highlight development opportunities. The method used Feature Oriented Domain analysis (FODA) and Acceptance Testing. This study delivered an analysis of IQA system features that consistent with PPEPP. The FODA results were validated by expert and tested with User Acceptance Test (UAT) with 89.98% user response that the system is acceptable. The research contributes to universities' understanding of the features necessary in the AQI system, which has an impact on the perfection of the university AQI system design in accordance with the PPEPP cycle.
Keywords: FODA; IQA system; PPEPP cycle; SPMI
Abstrak: Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi telah menyusun pedoman Sistem Penjaminan Mutu Internal atau yang dikenal dengan SPMI, yang diimplementasikan melalui Audit Mutu Internal (AMI) dengan siklus PPEPP, yaitu Penetapan (P), Pelaksanaan (P), Evaluasi (E), Pengendalian (P), dan Peningkatan (P). Beberapa perguruan tinggi telah mengimplementasikan AMI dengan sistem. Permasalahannya, sistem tersebut tidak sejalan dengan siklus PPEPP, sehingga hasil audit kurang memuaskan. Tujuan dari penelitian ini adalah untuk mengevaluasi seberapa baik fitur sistem AMI milik perguruan tinggi sejalan dengan siklus PPEPP dan menyoroti peluang pengembangan. Metode yang digunakan adalah analisis Feature Oriented Domain (FODA) dan Acceptance Testing. Penelitian ini menghasilkan analisis fitur sistem AMI yang konsisten dengan PPEPP. Hasil FODA divalidasi oleh ahli dan diuji dengan User Acceptance Test (UAT) dengan 89,98% respon pengguna bahwa sistem dapat diterima. Penelitian ini memberikan kontribusi terhadap pemahaman universitas terhadap fitur-fitur yang diperlukan dalam sistem AMI, yang berdampak pada kesempurnaan desain sistem AMI universitas sesuai dengan siklus PPEPP.
Kata kunci: FODA; siklus PPEPP; sistem AMI; SPMI
Abstract:Abstract: Non-performing loans remain one of the main challenges faced by cooperatives, particularly when the loan eligibility assessment process is still conducted manually. This traditional approach tends to be time consuming,…
nsuming, subjective, and prone to inaccurate decisions. This study aims to develop a predictive model for borrower eligibility using the Support Vector Machine (SVM) algorithm as a more efficient and objective machine learning-based solution. A total of 1,000 loan history records were processed using RapidMiner software, taking into account variables such as salary, years of employment, loan amount, monthly installment, employment status, monthly expenses, number of dependents, housing status, age, and collateral value. The model’s performance was evaluated using a confusion matrix and classification metrics including accuracy, precision, recall, and kappa. The results indicate that the SVM model achieved an accuracy of 90.05%, precision of 90.13%, recall of 90.05%, and f1 score of 90,08%, reflecting a strong performance in classifying borrower eligibility. The application of this method makes a significant contribution to the development of data driven decision support systems within cooperative environments. This finding expands the scientific understanding in the field of microfinance and supports the implementation of artificial intelligence technologies in making decisions that are more precise, rapid, and accurate.
Keywords: cooperative; eligibility prediction; machine learning; non-performing loan; SVM
Abstrak: Kredit macet merupakan salah satu permasalahan utama yang dihadapi koperasi, terutama ketika proses penilaian kelayakan peminjam masih dilakukan secara manual. Pendekatan ini cenderung lambat, subjektif, dan berisiko menghasilkan keputusan yang kurang akurat. Penelitian ini bertujuan untuk membangun model prediksi kelayakan peminjam menggunakan algoritma Support Vector Machine (SVM) sebagai solusi berbasis machine learning yang lebih efisien dan objektif. Sebanyak 1.000 data riwayat pinjaman diolah menggunakan tools RapidMiner dengan mempertimbangkan variabel: gaji, lama bekerja, besar pinjaman, angsuran per bulan, status pegawai, pengeluaran bulanan, jumlah tanggungan, status rumah, umur, dan nilai jaminan. Evaluasi model dilakukan menggunakan confusion matrix dan metrik klasifikasi seperti akurasi, presisi, recall, dan kappa. Hasil menunjukkan bahwa model SVM mencapai akurasi 90,05%, presisi 90,13%, recall 90,05%, dan f1 score 90,08%, yang mencerminkan performa model yang sangat baik dalam mengklasifikasikan kelayakan peminjam. Penerapan metode ini memberikan kontribusi penting dalam pengembangan sistem pendukung keputusan berbasis data di lingkungan koperasi. Temuan ini memperluas wawasan keilmuan di bidang keuangan mikro dan mendukung penerapan teknologi kecerdasan buatan dalam pengambilan keputusan yang lebih tepat, cepat, dan akurat.
Kata Kunci: koperasi; kredit macet; machine learning; prediksi kelayakan; SVM