METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi

ANALYZING LECTURER PERFORMANCE FACTORS FROM COURSE EVALUATION SURVEYS USING K-MEANS CLUSTERING AND C4.5 CLASSIFICATION

2025-08-29T14:46:50+07:00

One of the quality of education of a college can be seen from the quality of the performance of the lecturers in the

higher education tridharma namely education, research, and development and community service. This study

aims to analyze the lecturer performance factors based on the course evaluation survey on the tridharma of higher

education in the implementation of academic evaluations and decision making for lecturers in the Computer

Science study program, Pakuan University. The research method applies a combination of two data mining

methods, namely k-means clustering and C4.5 classification used in the assessment of the performance of

lecturers, especially in the process of education and college teaching which includes pedagogical, professional,

personality and social competencies. The results of the K-means clustering mining process were assessed by

learning, namely 5 sufficient lecturer clusters, 16 good cluster lecturers and 14 excellent cluster lecturers. C 4.5

classification is used to see the connectedness of factors such as learning, publication, education, PKM, support.

This study shows that publication criteria are the most influential factors in the performance assessment of

lecturers. Testing the level of accuracy using the K-fold Cross Validation method with 5-fold Cross Validation is

80.00% and 7-fold Cross Validation which is 82.86%.

IMPLEMENTASI K-MEANS RFM DAN HOLT-WINTERS EXPONENTIAL SMOOTHING ADDITIVE DALAM SISTEM BUSINESS INTELLIGENCE UNTUK STRATEGI PENGELOLAAN PELANGGAN PADA PERUSAHAAN TRANSPORTASI.

2025-08-28T15:42:37+07:00

The growth of customer data in the transportation industry drives the need for analytical systems capable of segmenting customers objectively and strategically. This study aims to apply the K-Means Clustering method based on the Recency, Frequency, and Monetary (RFM) model for customer segmentation and utilize the Holt-Winters Exponential Smoothing Additive method to forecast passenger numbers. The dataset comprises 10,440 customer transactions from PT XYZ during the 2022–2024 period. RFM values were calculated, normalized, and processed using the K-Means algorithm to produce three customer clusters: Loyal, Regular, and Passive. Subsequently, the Holt-Winters method was employed to forecast passenger numbers, achieving the smallest Mean Absolute Percentage Error (MAPE) of 6.88%, indicating a high level of accuracy. The results were visualized through an interactive dashboard using Tableau, enabling management to make data-driven decisions. This research demonstrates that integrating segmentation and forecasting methods into a Business Intelligence system can enhance the effectiveness of marketing strategies and the operational efficiency of the company.

RANCANG BANGUN SISTEM INFORMASI KLINIK BERBASIS WEB DENGAN LARAVEL

2025-09-04T10:12:22+07:00

Pengelolaan data pasien, dokter, dan pemeriksaan di Klinik Lestari Mandiri sebelumnya masih dilakukan secara manual, yang sering kali menyebabkan keterlambatan pencatatan dan kesalahan data. Untuk mengatasi permasalahan tersebut, dikembangkan sebuah sistem informasi klinik berbasis web menggunakan framework Laravel dan database MySQL. Pengembangan sistem melalui beberapa tahapan, yaitu analisis kebutuhan, perancangan sistem, implementasi, pengujian, dan pemeliharaan. Sistem ini dirancang dengan antarmuka yang sederhana dan mudah digunakan agar sesuai dengan kebutuhan staf klinik. Hasil pengujian menunjukkan bahwa sistem dapat berjalan dengan baik dan memenuhi fungsi utama seperti pencatatan data pasien, pengelolaan dokter, dan hasil pemeriksaan. Selain itu, sistem ini juga dapat dikembangkan lebih lanjut dengan penambahan fitur seperti laporan otomatis, pengingat jadwal kontrol, dan manajemen stok obat. Dengan adanya sistem informasi ini, proses administrasi klinik menjadi lebih efisien, akurat, dan mendukung pelayanan yang lebih baik kepada pasien.

MODEL PENGUKURAN KINERJA RANTAI PASOK BERBASIS GREEN SCOR DAN FUZZY AHP: STUDI KASUS PT. ARTERIA DAYA MULIA

2025-08-18T12:43:07+07:00

Supply chain performance measurement plays a crucial role in supporting operational continuity and corporate competitiveness, especially in meeting the demands for efficiency, effectiveness, and environmental sustainability. Imbalances in supply chain management can lead to resource waste, environmental pollution, and decreased customer satisfaction. PT. Arteria Daya Mulia, a rope manufacturing company, currently lacks a supply chain performance measurement system that fully incorporates sustainability aspects. This study aims to design a performance measurement model based on the Green SCOR framework and the Fuzzy AHP method as a strategic decision-making tool that considers sustainability dimensions. Performance indicators were determined according to the five main Green SCOR processes (Plan, Source, Make, Deliver, and Return), comprising 14 KPIs developed through literature review and field validation. Data were collected through observations, interviews, and questionnaires, then processed using the Fuzzy AHP method to obtain the priority weight of each indicator. The results show that the total supply chain performance score is 88, calculated by combining the weights with the Snorm de Boer values. Several indicators demonstrated excellent performance with a maximum Snorm value (100). However, one critical indicator was identified with the lowest Snorm value—% Error-free Return Shipped in the Return process—scoring 0.02 with a final SCM score of 0.0008, indicating the need for immediate improvement. The developed information system also generates automatic improvement recommendations based on the measurement results. This model is expected to assist the company in monitoring, evaluating, and continuously improving supply chain performance.

IMPLEMENTASI LOGIKA FUZZY MAMDANI DALAM SISTEM PENILAIAN KESEHATAN MAKANAN KEMASAN BERDASARKAN LABEL NUTRITION FACTS

2025-09-03T12:44:06+07:00

The growth of the packaged food industry has increased the need for an easy-to-understand health assessment system for consumers, especially those with limited nutrition literacy. This study develops a Mamdani fuzzy logic-based decision support system to evaluate the healthiness of packaged foods using Nutrition Facts labels. The system processes nutritional parameters such as fat, sugar, salt, fiber, protein, fruit/vegetable/nut content, and calorie content, converting them into linguistic categories like "low," "moderate," and "high" for easier interpretation by lay users. It effectively handles uncertainties and ambiguities in nutrition data, providing classifications like "Unhealthy," "Healthy," or "Very Healthy." Implemented through a web platform using Python and Flask, the system was tested with five food samples, achieving an 80% agreement with the official NutriScore classification. This indicates the potential of the system as a reliable, practical tool to help consumers make quicker and more accurate dietary decisions and improve nutrition awareness.

EVALUATING THE EFFECTIVENESS OF DISTILBERT FOR SENTIMENT ANALYSIS OF PLAYER FEEDBACK IN GAME DEVELOPMENT

2025-08-18T12:51:05+07:00

Real-time sentiment analysis (SA) plays an increasingly vital role in enhancing player experience through emotion-aware game design. By enabling systems such as dynamic difficulty adjustment, adaptive non-playable character (NPC) behavior, and responsive narrative progression, SA allows games to respond intelligently to player emotions. This study investigates the effectiveness of DistilBERT, a lightweight transformer-based language model, for multi-label emotion classification using the GoEmotions dataset, which includes 27 fine-grained emotion categories. The model’s performance was evaluated in terms of classification accuracy and computational efficiency. Experimental results reveal that DistilBERT delivers surprisingly strong performance despite its reduced size, making it a viable candidate for real-time applications in resource-constrained environments. These findings indicate that lightweight transformer models can support emotionally adaptive gameplay without significant trade-offs in latency or accuracy. Future work will focus on integrating DistilBERT into a live game environment to assess its impact on player engagement and real-time system responsiveness.

PENERAPAN METODE FUZZY TIME SERIES CHEN DALAM SISTEM PERAMALAN PRODUKSI UNTUK OPTIMALISASI PENGADAAN BAHAN BAKU PADA PERUSAHAAN MANUFAKTUR

2025-08-18T12:38:05+07:00

Fluctuating and dynamic production demands require manufacturing companies to adopt adaptive, data-driven planning systems. However, in manufacturing companies producing plastic ropes such as twine, nets, and yarn, production planning is still conducted manually without a systematic quantitative approach. This study aims to design a production forecasting system using the Fuzzy Time Series Chen method, which can address uncertainty in time series data. Monthly production data from January 2022 to December 2024 were used for testing. The results show that this method provides good forecasting accuracy, with MAPE values of 30.15% for twine, 17.89% for nets, and 16.91% for yarn. The production estimates for January 2025 are 70,162 units (twine), 50,599 units (nets), and 81,315 units (yarn). These findings indicate that the FTS Chen method can improve efficiency and accuracy in production planning.

PEMANFAATAN GOOGLE EARTH ENGINE DAN ALGORITMA RANDOM FOREST UNTUK PEMETAAN LAHAN PERKEBUNAN JERUK

2025-03-06T10:28:35+07:00

This study employed Google Earth Engine (GEE) and the Random Forest algorithm to map citrus plantations in Silimakuta District, Simalungun Regency, North Sumatra. As a major citrus production center—reaching 840,000 quintals in 2023—the region faces challenges in producing accurate and efficient maps of plantation distribution. By processing Sentinel-2 and Sentinel-1 satellite imagery in GEE, this study provides a more detailed and reliable mapping solution. The Random Forest model achieved a land-cover classification accuracy of 97% and a Kappa coefficient of 96.3%, demonstrating the method’s effectiveness for land mapping. This approach can overcome existing limitations in land data and deliver visual information useful for increasing citrus plantation productivity in the region. Therefore, the combined use of Google Earth Engine and the Random Forest algorithm shows strong potential to support more optimal and sustainable land management.

PENGEMBANGAN APLIKASI MANAJEMEN DATA BUKU MENGGUNAKAN APLIKASI VISUAL STUDIO CODE DENGAN FRAMEWORK LARAVEL

2025-05-29T10:18:14+07:00

The management of book data in libraries or bookstores often faces challenges in terms of efficiency and data accuracy. This research aims to develop a book management application using Visual Studio Code with the Laravel framework as an effective and user-friendly digital solution. The research method used is software development research with a prototyping approach. The results of the study indicate that this application simplifies book data management, including recording, editing, and deleting data with a user-friendly and responsive interface. In conclusion, the use of Laravel in the development of book management applications provides significant benefits in enhancing the productivity of book data management.

FEW-SHOT LEARNING FOR AML CELL CLASSIFICATION USING PROTOTYPICAL NETWORKS

2025-09-08T16:15:41+07:00

Accurate blood cell classification is crucial for diagnosing Acute Myeloid Leukemia (AML) but limited medical data poses challenges for traditional machine learning models. This study presents a Few-Shot Learning (FSL) framework utilizing a Prototypical Network architecture with a ResNet-34 backbone to classify AML blood cell types from microscopic images. In this study, we utilize datasets consisting of 15 morphologically distinct cell classes. A 15-way, 5-shot, 5-query episodic setup was adopted to simulate data-scarce conditions. Evaluation via 5-fold cross-validation yielded strong performance, with an average accuracy of 97.76%, precision of 98.78%, recall of 96.55%, and F1-score of 97.76%. FSL training times were consistent (4.22–4.26 minutes per fold), and t-SNE along with confusion matrices confirmed the model’s ability to distinguish similar cell types. To validate the approach, its performance was compared with a conventional supervised CNN using the same ResNet-34 backbone. The FSL model outperformed the CNN across all metrics such as accuracy (98.32% vs. 77.25%), precision (98.55% vs. 76.87%), recall (98.31% vs. 78.66%), and F1-score (98.33% vs. 75.26%), while also requiring far less training time (~4.24 min/fold vs. ~420 min total). These results highlight the promise of FSL based methods for accurate, efficient, and scalable hematologic diagnostics in data limited settings.

RANCANG BANGUN APLIKASI HELP DESK BERBASIS WEB DI PT TRI STAR SURYA GEMILANG PURWOKERTO MENGGUNAKAN METODE DESIGN THINKING

2025-08-18T12:52:59+07:00

This research aims to design and develop a web-based Help Desk application at PT Tristar Surya Gemilang Purwokerto using the Design Thinking method. The application is designed to enhance efficiency and transparency in managing complaints and expedite problem resolution through an integrated system. The research follows four main stages: Empathize, Define, Prototype, and Testing, focusing on user needs to create an effective solution. The results of the Blackbox Testing show that the application successfully meets the expected functionality for both admins and users, with features that align with user requirements. The developed system is expected to improve the IT team's performance in handling complaints and technical issues within the company.

PERANCANGAN INTERFACE APLIKASI INFORMASI RUANG KELAS KOSONG BERBASIS MOBILE DENGAN METODE USER-CENTERED DESIGN (UCD)

2025-09-03T12:59:27+07:00

Perkembangan teknologi informasi di lingkungan pendidikan tinggi menuntut efisiensi dalam pengelolaan sumber daya akademik, termasuk penyediaan informasi ruang kelas kosong. Mahasiswa dan dosen sering mengalami kesulitan dalam mencari ruang yang tersedia karena sistem manual dan antarmuka yang tidak ramah pengguna. Penelitian ini bertujuan merancang antarmuka aplikasi informasi ruang kelas kosong berbasis web dengan pendekatan User-Centered Design (UCD) untuk meningkatkan User Experience (UX). Metode penelitian yang digunakan adalah kualitatif dengan pendekatan observasi dan wawancara terhadap calon pengguna guna memahami kebutuhan, ekspektasi, dan konteks penggunaan aplikasi. Hasil dari perancangan ini berupa prototipe antarmuka aplikasi yang terdiri dari tampilan splash screen, login, halaman utama, serta profil pengguna. Desain ini menitikberatkan pada kemudahan navigasi, kejelasan informasi, dan keterlibatan pengguna dalam seluruh proses perancangan. Dengan menerapkan metode UCD, aplikasi diharapkan dapat memberikan solusi efektif terhadap permasalahan pencarian ruang kelas yang kosong secara real-time.

Kata kunci- Aplikasi, Sistem Informasi Akademik, User Experience, User-Centered Design

PREDIKSI KEHADIRAN PESERTA RAKORNAS APTIKOM MENGGUNAKAN METODE LEAST SQUARE

2025-09-04T11:16:42+07:00

APTIKOM (Asosiasi Pendidikan Tinggi Informatika dan Komputer) merupakan asosiasi yang mewadahi Perguruan Tinggi Indonesia yang memiliki rumpun Ilmu Komputer dan Teknologi Informasi yang berperan dalam pengembangan kurikulum, standar pendidikan dan sertifikasi professional di bidang Teknologi Informasi (TI).Prediksi jumlah kehadiran peserta Rakornas APTIKOM dapat memberikan perkiraan jumlah peserta di tahun selanjutnya untuk memudahkan panitia penyelenggara Rakornas dalam merencanakan kegiatan secara lebih terukur dan berbasis data dengan menggunakan metode Least Square. Hasil prediksi dianalisis dan dikategorikan menjadi tingkat keaktifan berdasarkan frekuensi kehadiran peserta. Hasil evaluasi model menunjukkan bahwa metode Least Square dapat digunakan secara efektif untuk memprediksi pola kepesertaan dan menghasilkan analisis kategori yang bermanfaat sebagai dasar pengambilan keputusan oleh pihak APTIKOM.