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Compiler
Published by Institut Teknologi Dirgantara Adisutjipto
ISSN : 22523839     EISSN : 25492403     DOI : 10.28989/compiler
Core Subject : Science,
Computer Science & IT
Jurnal "COMPILER" dengan ISSN Cetak : 2252-3839 dan ISSN On Line 2549-2403 adalah jurnal yang diterbitkan oleh Departement Informatika Sekolah Tinggi Teknologi Adisutjipto Yogyakarta. Jurnal ini memuat artikel yang merupakan hasil-hasil penelitian dengan bidang kajian Struktur Diskrit, Ilmu Komputasi , Algoritma dan Kompleksitas, Bahasa Pemrograman, Sistem Cerdas, Rekayasa Perangkat Lunak, Manajemen Informasi, Dasar-dasar Pengembangan Perangkat Lunak, Interaksi Manusia-Komputer, Pengembangan Berbasis Platform, Arsitektur dan Organisasi Komputer, Sistem Operasi, Dasar-dasar Sistem,Penjaminan dan Keamanan Informasi, Grafis dan Visualisasi, Komputasi Paralel dan Terdistribusi, Jaringan dan Komunikasi, Desain, Animasi dan Simulasi Pesawat Terbang. Compiler terbit setiap bulan Mei dan November.
Arjuna Subject : -
Articles 423 Documents
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Power Usage Monitoring Simulator for Estimating Usage Tariffs and Carbon Emission Levels at STO Bogor Based on IoT Kusumaningrum, Nurwijayanti; Syafdi, Rizky
Compiler Vol 13, No 2 (2024): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v13i2.2602

Abstract

In this modern era, the efficiency of electricity usage has become one of the main concerns in the efforts toward sustainable energy management. The limitations in monitoring electricity usage have become a challenge for technicians, resulting in inefficiencies in data collection and discrepancies between the actual power usage and manual recordings. This research aims to design and develop a prototype of an Internet of Things (IoT)-based electricity usage monitoring tool to monitor electricity consumption in real-time, provide usage cost estimates, and measure the emission levels generated by the devices being used. It also facilitates data recording, accelerates decision-making, and improves electricity management with high accuracy, with a margin of error of 0.8% for power calculations and 0.5% for total power calculations. This allows for accurate measurement of voltage, load, power, and total power. The data obtained is used to calculate electricity tariffs based on actual consumption, such as a subscription fee of IDR 127,134, a rate per kWh of IDR 528.76, and a tax of 4%, resulting in a total cost of IDR 132,768 for 0.366 kWh usage over 60 minutes. The use of electronic devices also increases carbon emissions, with a 69% increase in the first 10 minutes and 28% in 60 minutes, highlighting the importance of environmental awareness and wise electricity usage.
Automated Testing to Evaluate Employee Attendance System Performance Using Gtmetrix Hafizhah, Nurul; Hidayat, Ahmad Tri
Compiler Vol 13, No 2 (2024): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v13i2.2685

Abstract

The employee attendance system is an important component in human resource management that functions to efficiently record and monitor employee attendance. With the increasing reliance on information technology, it is essential to ensure optimal performance and a satisfying user experience. It is important for companies to ensure that this system functions well and responsively. This study aims to evaluate the performance of an employee attendance system through automated testing using the website performance analysis tool GTMetrix. By adopting automated testing using GTMetrix on this system to measure and analyze its performance, this research also offers an objective and efficient approach to identifying performance bottlenecks. The results of this research can serve as a reference for information system developers in designing and implementing a more optimal employee attendance system. In addition, the research also provides insights into the importance of optimizing website performance in the context of business applications. The results of the performance and structure testing analysis on this system using GTMetrix achieved an A grade with a performance score of 100% and a structure score of 100%. This research emphasizes the importance of automated testing as a tool to enhance and improve the performance of information systems, thereby meeting user needs and supporting more effective human resource management.
An Innovation Study on Luggage Wheel Design for Seamless Travel Kurudirek, Abdullah; Kurudirek, Melek Azra; Kurudirek, Kadriye Afra
Compiler Vol 14, No 1 (2025): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i1.2819

Abstract

In this paper, a new suitcase study that will enable people to travel comfortably in every aspect is emphasized, and prototype examples are handled. This study reveals the latest innovations in suitcase design aimed at improving travel efficiency and eliminating wheel malfunctions that may occur in the suitcases carried by passengers (especially breakages during loading and unloading in the cargo section). Considering current design trends and the smoothness of travel, as well as the joy of passengers being able to securely retrieve their suitcases from the conveyor belts at their destinations, this research identifies the key features that contribute to enhanced mobility and comfort. This study employs a mixed-methods approach combining both qualitative user feedback and quantitative data to evaluate performance. A total of 60 participants (30 male, 30 female) were included in real-world testing scenarios, while durability tests were conducted under controlled laboratory conditions. Both quantitative and qualitative results indicate that the newly developed suitcase design outperformed standard wheels, especially within the 20–32 kg weight range, in terms of comfort, usability, durability, and overall user satisfaction.. Previous research findings indicate that modern design features such as ergonomic handles and lightweight materials significantly enhance travel comfort and efficiency. In this research, the latest wheel designs are expected to contribute to these findings. Throughout this research, we will look at two separate prototype examples to illustrate these cutting-edge concepts simply and understandably. Therefore, this article provides insights for designers, manufacturers, and travellers interested in maintaining the robust functionality of suitcases.
An IoT-Based Motorcycle Security System Using Arduino and Android for Theft Prevention Rakhmadi, Aris; Aji, Doni Kurnia; Rosad, Safiq; Azis, Abdul; Wahyusari, Retno
Compiler Vol 14, No 1 (2025): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i1.2889

Abstract

Motorcycle theft remains a prevalent issue, especially in urban areas, where traditional security measures such as mechanical locks and ignition keys are easily bypassed. This research presents an IoT-based motorcycle security system integrating Arduino, Bluetooth communication, and an Android application to enhance theft prevention. The system employs an Arduino Uno microcontroller, HC-05 Bluetooth module, and SW-420 vibration sensor to detect unauthorized access and trigger security mechanisms. Users can remotely monitor and control their motorcycles via an Android application, which allows engine immobilization and alarm activation functions. The system was tested for hardware performance, Bluetooth connectivity, and software reliability. Results indicate that Bluetooth communication remains stable within a 10-meter range, the vibration sensor effectively detects unauthorized movements, and real-time commands between the application and Arduino execute with minimal latency. Cost analysis suggests that the system, with a total hardware cost of Rp 223,000, is an affordable and effective solution for motorcycle security. Despite some range limitations, the study demonstrates the feasibility of IoT-based security enhancements. Future improvements include GPS tracking and GSM communication for extended monitoring. This research contributes to developing innovative, cost-effective, and user-friendly vehicle security solutions.
On the Chromatic Number of Cycle Books Graph Santoso, Jaya
Compiler Vol 14, No 1 (2025): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i1.2930

Abstract

Graph coloring is a fundamental topic in graph theory, with various applications in scheduling, networking, and optimization problems. In this study, we investigate the chromatic number of the cycle books graph , a structured graph formed by attaching multiple cycles to a common path . We establish that the chromatic number of    depends on the parity of . Specifically, we prove that if  is even, the chromatic number is , while if  is odd, the chromatic number is . These results provide a deeper understanding of coloring properties in book-like graphs and contribute to the broader study of chromatic numbers in structured graph families. The findings may be extended to other variations of book graphs and related topologies in future research.
Enhancing Sentiment and Emotion Classification with LSTM-Based Semi-Supervised Learning Husaini, Rochmat; Cahyana, Nur Heri; Wisnalmawati, Wisnalmawati; Mardiana, Tri; Fauziah, Yuli
Compiler Vol 14, No 1 (2025): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i1.2965

Abstract

The evolution of sentiment analysis has increasingly relied on semi-supervised learning (SSL) models, particularly due to their efficiency in utilizing large amounts of unlabeled data. This study employed four Indonesian datasets—Ridife (sentiment classification), Emotion Indonlu (emotion classification), Sentiment Indonlu (sentiment classification), and Hate Speech (offensive content detection). The LSTM model was trained using labeled data and used to generate pseudo-labels for unlabeled data across three iterations. The performance of the pseudo-labels was evaluated using Random Forest, Logistic Regression, and Support Vector Machine (SVM). The LSTM model demonstrated varying effectiveness across different datasets. For the Sentiment Ridife dataset, LSTM achieved an accuracy of 70.23%, slightly lower than Random Forest but higher than Logistic Regression and SVM. In the Sentiment IndoNLU dataset, LSTM's accuracy was 86.12%, showing strong performance but slightly below Random Forest and Logistic Regression. The Emotion IndoNLU dataset revealed similar performance across models, while the Hate Speech dataset saw LSTM perform well with an accuracy of 86.49%. The results indicate that while LSTM-based SSL can effectively generate pseudo-labels and enhance model performance, its performance varies depending on the dataset and task. This study underscores the need for further research into optimizing pseudo-labeling techniques and exploring advanced NLP models to improve sentiment and emotion analysis in diverse languages.
Software Defects Predictions using SQL Complexity and Naïve Bayes Subali, Made Agus Putra; Sugiartha, I Gusti Rai Agung; Adnyana, I Made Budi; Putra, I Putu Aditya; Subawa, Made Dai
Compiler Vol 14, No 1 (2025): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i1.2979

Abstract

Software defects result in unreliable software, therefore predicting software defects is an effort to produce quality software. In this study, we used the naïve bayes method because it has the appropriate characteristics of the data used. The data used include NASA MDP datasets and datasets from the calculation of the sql complexity method on eight software modules. The use of two datasets was carried out because in the NASA MDP datasets there were no attributes that paid attention to the use of sql commands, therefore in the datasets from the eight software modules the sql complexity attribute was included which paid attention to the level of complexity of the use of sql commands in each module. The prediction results of this study were evaluated by considering the values of accuracy, precision, recall, and f-measure. Based on these results, the accuracy results of CM1 were 88%, PC2 was 97%, and KC3 was 78%.
Implementation of Extreme Programming and Simple Additive Weighting for Web-Based Sales and Product Preference Analysis in Traditional Herbal Businesses Sumardiono, Sumardiono; Priyadi, Wiwit; Wicaksono, Harjunadi; Santosa, Hadi; Sambath, Khoem; Liefalza, Andi Daffa
Compiler Vol 14, No 1 (2025): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i1.2966

Abstract

The rapid development of information technology encourages UMKM to adopt digital solutions to improve business effectiveness. This study aims to design a web-based herbal medicine sales information system at UMKM Griya Jamoe Klasik using the Extreme Programming (XP) method and implementing the Simple Additive Weighting (SAW) algorithm to analyze the best-selling herbal medicine products. The research approach used is quantitative descriptive, with data collection methods through observation, interviews, and questionnaires to 10 respondents over a period of one week. The criteria used in the analysis include price, taste, efficacy, and texture, each given a certain weight. The results of the SAW algorithm application show that the "Wedang Kencur" product is the best-selling herbal medicine with a preference value of 0.92, followed by "Wedang Mpon-mpon" at 0.85 and "Kunyit Asam" at 0.79. The system built is able to automate transaction recording, facilitate sales monitoring, and support accurate and fast data-based decision-making. This research contributes to increasing the competitiveness of UMKM in the digital era. Recommendations for further research are to expand the number of respondents, integrate online payment features, and develop mobile-based applications to reach a wider market.
K-Means Clustering On Rice Harvest Data For Planting Season Recommendation In Subak Cepaka, Tabanan Dewi, Ni Made Cahyani; Hidayat, Ahmad Tri
Compiler Vol 14, No 2 (2025)
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i2.3504

Abstract

The Subak farming system in Tabanan Regency, Bali, is vital as a primary rice granary but faces challenges in determining optimal planting patterns. Planting decisions based only on inherited experience often do not match climate conditions, reducing productivity and increasing crop failure risks. This study implements the K-Means Clustering algorithm on five years of historical rice harvest data (2020–2024) to generate accurate planting season recommendations. Monthly data were analyzed and grouped into three categories: rainy, dry, and transitional seasons. The clustering results were integrated into a mobile application that provides farmers with accessible recommendations through an interactive interface and visualization. The effectiveness of the clustering model was evaluated using the Silhouette Score, which indicated good separation and cohesion among clusters, while efficiency was assessed through processing time and algorithm simplicity, confirming that K-Means performed the task with minimal computational cost. This system enables farmers to make data-driven planting decisions, optimize productivity, and support sustainable food security in Bali.
Sentiment Analysis of Opinions on the Performance of the Governor of West Java in 2025 on Social Media X Using LSTM Safaat, Muhammad Apipudin; Ekawati, Nia
Compiler Vol 14, No 2 (2025)
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i2.3152

Abstract

The rise of political discourse on Indonesian social media platforms such as X (formerly Twitter) creates opportunities and challenges for policymakers. Existing sentiment analysis methods often fail to handle informal language, slang, and sarcasm, leading to frequent misclassification that may misguide governance decisions. This study aims to establish the first benchmark for three-class sentiment analysis (positive, neutral, negative) in Indonesian political discourse using a Long Short-Term Memory (LSTM) model with culture-specific preprocessing. A dataset of 1,002 tweets on the performance of the Governor of West Java (Feb–May 2025) was collected, normalized for slang and typos, and enriched with a political lexicon. Manual annotation achieved high agreement (κ = 0.82). An LSTM model with 128 units and 30% dropout was trained and evaluated. Results show 95.88% training accuracy but only 36.32% validation accuracy, indicating severe overfitting. Misclassifications (42%) mainly stemmed from sarcasm and contextual ambiguity, with the lowest precision in the positive class (31%). The study contributes by (1) providing the first benchmark for Indonesian political sentiment, (2) demonstrating the value of culture-specific preprocessing, and (3) offering policy insights into latent dissatisfaction hidden in neutral tweets. Limitations include small dataset size and lack of sarcasm-aware mechanisms, suggesting future exploration of hybrid and transformer-based models.

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