cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Andy Sapta
Contact Email
sapta@royal.ac.id
Phone
-
Journal Mail Official
lppm_stmik@royal.ac.id
Editorial Address
-
Location
Kab. asahan,
Sumatera utara
INDONESIA
JURTEKSI
Published by STMIK Royal Kisaran
ISSN : 24071811     EISSN : 25500201     DOI : -
Core Subject : Science,
Computer Science & IT
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) is a scientific journal which is published by STMIK Royal Kisaran. This journal published twice a year on December and June. This journal contains a collection of research in information technology and computer system.
Arjuna Subject : -
Articles 685 Documents
 63   64   65   66   67 
MICROCONTROLLER IMPLEMENTATION ON ULTRASONIC SENSOR BASED AUTOMATIC TRASH CAN SYSTEM Wanayumini, Wanayumini; Isnaini, Fitri; lvindra, Farhan A; Wardana, Revo
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 1 (2024): Desember 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i1.3646

Abstract

Abstract : Waste management in Sei Beluru Village faces challenges due to population growth and increasing waste volume. This research aims to design and implement an automatic waste bin system based on microcontroller using Arduino Uno. The research uses experimental method with hardware and software development stages including system design, component integration, and testing. The developed system integrates HCSR-04 sensors for waste volume detection, infrared sensors for object presence detection, and servo motors for automatic opening-closing mechanism. Test results show that the system successfully detects waste levels with high accuracy and operates the opening-closing mechanism effectively. The implementation of this system proves effective in optimizing waste management in Sei Beluru Village by reducing physical interaction and preventing waste accumulation. Keywords : arduino uno; HCSR-04 sensor; automatic waste bin; HCSR-04 sensor; microcontroller; waste management.  Abstract : Waste management in Sei Beluru Village faces challenges due to population growth and increasing waste volume. This research aims to design and implement an automatic waste bin system based on microcontroller using Arduino Uno. The research uses experimental method with hardware and software development stages including system design, component integration, and testing. The developed system integrates HCSR-04 sensors for waste volume detection, infrared sensors for object presence detection, and servo motors for automatic opening-closing mechanism. Test results show that the system successfully detects waste levels with high accuracy and operates the opening-closing mechanism effectively. The implementation of this system proves effective in optimizing waste management in Sei Beluru Village by reducing physical interaction and preventing waste accumulation. Keywords : arduino uno; HCSR-04 sensor; automatic waste bin; HCSR-04 sensor; microcontroller; waste management. 
PREDICTING OF BREAST CANCER RISK USING MACHINE LEARNING WITH FEATURE SELECTION THROUGH XGBOOST Al Azhar, Cahya Mutiara; Pujiono, Pujiono
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 2 (2025): Maret 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3661

Abstract

Abstract: Breast cancer is the leading cause of death for women globally, exacerbated by late detection. This study proposes a breast cancer risk prediction framework using XGBoost with SelectKBest feature selection. It aims to improve the accuracy and efficiency of early detection through exploratory data analysis, coding, SMOTE to address class imbalance, and feature selection (k=29). As a result, the XGBoost model achieved 98.1% accuracy, 98.1% recall, 98.1% f1-score, and 98.2% precision on test data, highlighting the importance of feature selection. These results are promising in patient prioritization (triage) for further examination, helping medical personnel identify high-risk patients, thus improving resource allocation efficiency. These findings validate SelectKBest and pave the way for the development of a machine learning-based clinical decision support system for breast cancer early detection workflows. This research contributes significantly to the application of machine learning to support early breast cancer detection.            Keywords: breast cancer; feature selection; machine learning; risk prediction; XGBOOST.  Abstrak: Kanker payudara menjadi penyebab utama kematian wanita global, diperparah deteksi yang terlambat. Penelitian ini mengusulkan kerangka prediksi risiko kanker payudara menggunakan XGBoost dengan seleksi fitur SelectKBest. Tujuannya meningkatkan akurasi dan efisiensi deteksi dini melalui analisis data eksploratif, pengkodean, SMOTE untuk mengatasi ketidakseimbangan kelas, dan seleksi fitur (k=29). Hasilnya, model XGBoost mencapai akurasi 98.1%, recall 98.1%, f1-score 98.1%, dan presisi 98.2% pada data uji, menyoroti pentingnya seleksi fitur. Hasil ini menjanjikan dalam penentuan prioritas pasien (triage) untuk pemeriksaan lebih lanjut, membantu tenaga medis mengidentifikasi pasien berisiko tinggi, sehingga meningkatkan efisiensi alokasi sumber daya. Temuan ini memvalidasi SelectKBest dan membuka jalan bagi pengembangan sistem pendukung keputusan klinis berbasis machine learning untuk alur kerja deteksi dini kanker payudara. Penelitian ini berkontribusi signifikan dalam penerapan machine learning untuk mendukung deteksi dini kanker payudara. Kata kunci: kanker payudara; pembelajaran mesin; prediksi risiko ; seleksi fitur; XGBOOST. 
DEVELOPMENT OF VIRTUAL REALITY APPLICATION FOR DESKTOP COMPUTER ASSEMBLY Sapta, Andy; Mansur, Hamsi; Hakim, Abdul; Agung, Muhammad; Dalu, Zaudah Cyly Arrum
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 1 (2024): Desember 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i1.3680

Abstract

Abstract: Both hardware and software technologies offer their advantages in helping to facili- tate student learning activities. Virtual reality technology allows users to interact directly with  the virtual reality environment, giving the effect of a pleasant learning sensation because it pro- vides direct experience for students to actively do desktop computer assembly practicum inde- pendently and guided. This research is R & D (Research and Development), which aims to pro- duce a product as a desktop computer assembly virtual reality learning application. This re- search procedure adapts the Lee & Owens development model. The subjects of this research  were students at the Open University, Makassar State University, and Lambung Mangkurat  University. The results showed that using Virtual Reality in desktop computer assembly can  provide extraordinary experiences to users, bridging the gap between the real and virtual worlds.  This is achieved through specially designed hardware to create a virtual environment that re- sembles the actual reality or even creates an entirely new reality.  Keywords: desktop computer; assembly; virtual reality     Abstrak: Teknologi perangkat keras (hardware) maupun lunak (software) menawarkan  keunggulannya dalam membantu memfasilitasi aktivitas belajar dan pembelajaran ma- hasiswa. Teknologi virtual reality memiliki kemampuan bagi penggunanya untuk dapat  melakukan interaksi langsung dengan lingkungan realitas maya, memberi efek sensasi  pembelajaran yang menyenangkan karena memberikan pengalaman langsung bagi ma- hasiswa untuk aktif melakukan pratikum perakitan computer desktop secara mandiri  maupun terbimbing. Penelitian ini adalah R & D (Research and Development) yang ber- tujuan untuk menghasilkan suatu produk yaitu berupa aplikasi pembelajaran virtual real- ity perakitan computer desktop. Prosedur penelitian ini mengadaptasi model pengem- bangan Lee & Owens. Subjek penelitian ini adalah mahasiswa pada Universitas Ter- buka,  Universitas  Negeri  Makassar,  dan  Unibversitas  Lambung  Mangkurat.  Hasil  penelitian diperoleh bahwa penggunaan Virtual Reality dalam perakitan computer desk- top mampu memberikan pengalaman luar biasa kepada pengguna, menjembatani jurang  antara dunia nyata dan dunia maya. Hal ini dicapai melalui penggunaan perangkat keras  yang dirancang khusus untuk menciptakan lingkungan virtual yang menyerupai realitas  sebenarnya atau bahkan menciptakan realitas yang sama sekali baru. Kata kunci: computer desktop; perakitan; virtual reality  
DIAGNOSING ANDROID-BASED VIRUS INFECTIONS IN CHILDREN USING NAIVE BAYES KH, Musliadi; Kaharuddin, Kaharuddin; Syafrinal, Ilwan
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 2 (2025): Maret 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3685

Abstract

Abstract: Infectious diseases are one of the most common health problems in children because they have immature immune systems. Children are more susceptible to infections caused by bacteria, viruses, fungi, and protozoa. Some common infectious diseases in children include fever, acute respiratory infections (ARI), pneumonia, acute gastroenteritis (GAE), measles, chickenpox, and diphtheria. The limited number of pediatricians and the difficulty of accessing health facilities in remote areas hinder children's health services. To overcome this, an Android-based expert system is needed using the Naïve Bayes method to help diagnose infectious diseases in children earlier. The research method used is the Software Development Life Cycle (SDLC), where Black Box is used for internal testing, and PSSUQ is used to measure user satisfaction. The data set used was 1320 taken from a local hospital. The test results show that all the main features work as expected without any errors. The implementation of the system in diagnosing diseases went well and based on end-user feedback from 74 respondents, the system obtained a user satisfaction score of 6.40, where users felt that the system was easy to use, efficient, and provided clear and useful information. Keywords: expert system; infectious disease; naïve bayes; PSSUQ; SDLC  Abstrak: Penyakit menular merupakan salah satu masalah kesehatan yang paling umum terjadi pada anak-anak karena mereka memiliki sistem kekebalan tubuh yang belum matang. Anak-anak lebih rentan terhadap infeksi yang disebabkan oleh bakteri, virus, jamur, dan protozoa. Beberapa penyakit infeksi yang umum terjadi pada anak-anak antara lain demam, infeksi saluran pernapasan akut (ISPA), pneumonia, gastroenteritis akut (GEA), campak, cacar air, dan difteri. Keterbatasan jumlah dokter spesialis anak dan sulitnya akses ke fasilitas kesehatan di daerah terpencil, menjadi kendala pada pelayanan kesehatan anak. Untuk mengatasi hal tersebut, diperlukan sistem pakar berbasis Android menggunakan metode Naïve Bayes untuk membantu mendiagnosis penyakit infeksi pada anak-anak lebih dini. Metode penelitian yang digunakan adalah Software Development Life Cycle (SDLC), di mana Black Box untuk pengujian internal, dan PSSUQ untuk mengukur kepuasan pengguna. Data set yang digunakan adalah 1320 yang diambil dari rumah sakit setempat. Hasil pengujian menunjukkan bahwa seluruh fitur utama berjalan sesuai harapan tanpa kesalahan. Implementasi sistem dalam mendiagnosa penyakit berjalan dengan baik dan berdasarkan umpan balik pengguna akhir dari 74 responden, sistem memperoleh skor kepuasan pengguna sebesar 6,40, di mana pengguna merasa sistem ini mudah digunakan, efisien, serta menyediakan informasi yang jelas dan bermanfaat. Kata kunci: naïve bayes; penyakit menular; PSSUQ; SDLC; sistem pakar
REAL - TIME FACE DETECTION USING MATLAB HAAR CASCADE ALGORITHM Jannah, Miftahul; Wanayumini, Wanayumini; Ardana, Abdul Aziz; Selase, Septinur; Nurliana, Nurliana
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 3 (2025): Juni 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i3.3692

Abstract

Abstract: Face detection remains a challenging task in computer vision due to real-world factors such as uneven lighting, varying viewpoints, distance, and occlusion. This study aims to develop and evaluate a real-time facial feature detection application (detecting face, eyes, nose, and mouth) using MATLAB and a webcam. Detection is performed using the Viola-Jones Cascade Classifier method through the vision.CascadeObjectDetector function. Key parameters that were adjusted include the MergeThreshold (ranging from 4 to 50 depending on the feature) and MinSize (based on estimated feature size within the frame). However, this study does not include tuning of other parameters such as FalseAlarmRate, which constitutes a limitation of the employed method. The adjustment of these parameters proved significant in improving detection accuracy and robustness under varying lighting conditions. Nevertheless, the system still encounters difficulties in detecting facial features in the presence of occlusion. This study also has the potential to serve as a foundation for further developments in face recognition, emotion detection, or biometric authentication.            Keywords: computer vision; haar cascade; MATLAB Abstrak: Deteksi wajah merupakan tantangan dalam visi komputer karena dipengaruhi oleh kondisi nyata seperti pencahayaan tidak merata, sudut pandang, jarak, dan obstruksi. Penelitian ini bertujuan untuk mengembangkan dan menguji aplikasi deteksi fitur wajah secara real-time (wajah, mata, hidung, dan mulut) menggunakan MATLAB dan kamera webcam. Deteksi dilakukan dengan metode Viola-Jones Cascade Classifier melalui fungsi vision.CascadeObjectDetector. Parameter penting yang disesuaikan adalah MergeThreshold (antara 4 hingga 50 tergantung fitur), MinSize (mengikuti estimasi ukuran fitur dalam frame). Namun, penelitian ini tidak mencakup penyesuaian parameter lain seperti FalseAlarmRate, yang menjadi salah satu keterbatasan metode yang digunakan. Penyesuaian parameter ini terbukti signifikan dalam meningkatkan akurasi deteksi dan ketahanan terhadap variasi kondisi pencahayaan. Namun, sistem masih mengalami kesulitan mendeteksi fitur wajah jika terjadi obstruksi. Penelitian ini juga berpotensi menjadi dasar untuk pengembangan lebih lanjut dalam face recognition, emotion detection, atau biometric authentication.  Kata kunci: visi computer; haar cascade; MATLAB 
AHP-TOPSIS AND ANOVA METHOD APPROACH IN SOFTWARE DEVELOPMENT CRITERIA SELECTION ACCORDING TO ISO 12207:2017 Fadilla, Rizqi Mirza; Ariatmanto, Dhani
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 3 (2025): Juni 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i3.3698

Abstract

Abstract: The rapid development of information technology has increased the demand for high-quality software, necessitating a structured development process. ISO/IEC/IEEE 12207:2017 serves as an international standard encompassing organizational, technical, and project support processes, differing from ISO 9001, which focuses more generally on quality management. This study employs a Multi-Criteria Decision Making (MCDM) approach by integrating the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). AHP determines the weight of ISO 12207:2017 criteria through pairwise comparisons, while TOPSIS ranks software development activities based on these weights. To validate the results, Analysis of Variance (ANOVA) is applied. The findings indicate that the Software Requirements Definition Process has the highest priority weight (0.169), followed by Implementation (0.101) and Operation (0.095). Software Configuration Management is identified as the most critical activity with the highest TOPSIS score (0.221). ANOVA confirms the reliability of expert evaluations, showing no significant differences. This study provides a structured decision-making framework based on ISO 12207:2017, helping optimize software project management while ensuring alignment with international standards and industry best practices.            Keywords: AHP; TOPSIS; ANOVA; ISO 12207:2017  Abstrak: Perkembangan teknologi informasi meningkatkan permintaan perangkat lunak berkualitas tinggi, sehingga diperlukan proses terstruktur dalam pengembangannya. ISO/IEC/IEEE 12207:2017 menjadi standar internasional yang mencakup proses organisasi, teknis, dan pendukung proyek, berbeda dengan ISO 9001 yang lebih umum pada manajemen kualitas. Penelitian ini menggunakan Multi-Criteria Decision Making (MCDM) dengan mengintegrasikan Analytic Hierarchy Process (AHP) dan Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). AHP menentukan bobot kriteria ISO 12207:2017 melalui perbandingan berpasangan, sementara TOPSIS memeringkat aktivitas pengembangan berdasarkan bobot tersebut. Untuk validasi, Analysis of Variance (ANOVA) diterapkan. Hasil penelitian menunjukkan bahwa Proses Definisi Kebutuhan Perangkat Lunak memiliki bobot tertinggi (0,169), diikuti Implementasi (0,101), dan Operasi (0,095). Manajemen Konfigurasi Perangkat Lunak menjadi aktivitas paling kritis dengan skor TOPSIS tertinggi (0,221). ANOVA mengonfirmasi keandalan penilaian para ahli tanpa perbedaan signifikan. Penelitian ini memberikan kerangka kerja pengambilan keputusan berbasis ISO 12207:2017, membantu optimalisasi manajemen proyek perangkat lunak, serta memastikan keselarasan dengan standar internasional dan praktek terbaik industri. Kata kunci: AHP; TOPSIS; ANOVA; ISO 12207:2017
AI-BASED ALGORITHMS FOR NETWORK SECURITY: TRENDS, PER-FORMANCE, AND CHALLENGES Marison, Sihol; Silvanus, Silvanus; Rusdiah, Rudi
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 2 (2025): Maret 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3699

Abstract

Abstract: The advancement of network security faces growing challenges as cyberattacks become more sophisticated. Traditional rule-based systems struggle with zero-day attacks and obfuscation techniques. This study examines the development trends of AI-based algo-rithms, particularly machine learning and deep learning, in threat detection. A literature review evaluates AI-driven approaches, including support vector machines, random for-est, deep neural networks, convolutional neural networks, and reinforcement learning. Findings show that AI enhances detection accuracy, adaptability, and reduces false posi-tives. Machine learning efficiently classifies known attacks, while deep learning excels in identifying complex patterns such as distributed denial-of-service and advanced persis-tent threats. Unsupervised learning improves anomaly detection without labeled data. However, AI models require high-quality data, substantial computational resources, and remain vulnerable to adversarial attacks. Despite these challenges, AI provides a dynam-ic and adaptive security solution, surpassing traditional systems. Future research should enhance AI scalability and resilience for evolving cybersecurity threats. Keywords: anomaly detection; artificial intelligence; deep learning; machine learning; network security Abstrak: Perkembangan keamanan jaringan menghadapi tantangan yang semakin besar seiring meningkatnya kompleksitas serangan siber. Sistem berbasis aturan tradisional kesulitan mendeteksi zero-day attack dan teknik penyamaran. Penelitian ini mengkaji tren pengembangan algoritma berbasis AI, khususnya machine learning dan deep learning, dalam deteksi ancaman. Literature review mengevaluasi pendekatan berbasis AI, termasuk support vector machines, random forest, deep neural networks, convolutional neural networks, dan reinforcement learning. Hasil penelitian menunjukkan bahwa AI meningkatkan akurasi deteksi, adaptabilitas terhadap ancaman baru, serta mengurangi false positive. Machine learning efektif mengklasifikasikan serangan yang telah diketahui, sementara deep learning unggul dalam mengenali pola kompleks seperti distributed denial-of-service dan advanced persistent threats. Unsupervised learning meningkatkan deteksi anomali tanpa memerlukan data berlabel. Namun, AI masih bergantung pada data berkualitas tinggi, sumber daya komputasi besar, dan rentan terhadap adversarial attack. Meskipun demikian, AI menawarkan solusi keamanan yang lebih dinamis dan adaptif dibandingkan sistem tradisional. Penelitian selanjutnya perlu difokuskan pada peningkatan skalabilitas dan ketahanan AI dalam menghadapi ancaman siber yang terus berkembang. Kata kunci: deteksi anomali; jaringan keamanan; kecerdasan buatan; pembelajaran dalam; pembelajaran mesin
FORECASTING POPULATION GROWTH IN TANJUNG TIRAM USING LEAST SQUARE METHOD Rainah, Rainah; Nofriadi, Nofriadi; Muhazir, Ahmad
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 3 (2025): Juni 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i3.3707

Abstract

Abstract: The rapid population growth in Tanjung Tiram District, primarily driven by increased in-migration, demands an accurate forecasting system to support effective and sustainable development planning. This study aims to predict population growth in Tanjung Tiram District in 2024 using the Least Square method. The analysis covers birth, arrival, and migration data from 2019 to 2023. The results show that the Least Square method successfully predicts 936 births, 104 arrivals, and 142 migrations in 2024, with a very low error rate: MAPE for births is 0.01%, arrivals 0.12%, and migrations 0.04%. These research demonstrate that the Least Square method can effectively support data-driven development policies and improve the accuracy of public service distribution planning.         Keywords: forecasting; least square method; population growth; tanjung tiram.  Abstrak: Pertumbuhan penduduk yang pesat di Kecamatan Tanjung Tiram, terutama akibat peningkatan migrasi masuk, menuntut adanya sistem prediksi yang akurat untuk mendukung perencanaan pembangunan yang efektif dan berkelanjutan. Penelitian ini bertujuan untuk memprediksi pertumbuhan penduduk di Kecamatan Tanjung Tiram pada tahun 2024 menggunakan pendekatan metode Least Square. Data yang dianalisis mencakup jumlah kelahiran, kedatangan, dan perpindahan penduduk dari tahun 2019 hingga 2023. Hasil penelitian menunjukkan bahwa metode Least Square mampu memprediksi jumlah kelahiran sebesar 936 jiwa, kedatangan 104 jiwa, dan perpindahan 142 jiwa pada tahun 2024, dengan tingkat kesalahan yang sangat rendah: MAPE untuk kelahiran sebesar 0,01%, kedatangan 0,12%, dan perpindahan 0,04%. Penelitian ini membuktikan bahwa metode Least Square dapat digunakan secara efektif untuk mendukung penyusunan kebijakan pembangunan yang berbasis data dan memperkuat akurasi distribusi layanan publik.Kata kunci: metode least square; peramalan; pertumbuhan penduduk; tanjung tiram.
DESIGN OF AN INTERNET OF THINGS-BASED WATER LEVEL MONITORING SYSTEM Rienandie, Naufal Fakhrie; Pramudita, Resa
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 2 (2025): Maret 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3713

Abstract

Abstract: Conventional water reservoir filling systems often cause inefficiencies due to delays in monitoring or failure of the float system which results in overflowing water from the reservoir. this research aims to develop an ESP32-based water level monitoring and control system by utilising IoT technology and ultrasonic sensors, this system can facilitate users in monitoring water levels and automating pump control. this research uses the experimental method, starting from system design to system testing and analysis, as well as testing which includes sensor accuracy, system response, and communication stability with the IoT server. based on the results obtained. The test results show that the system has an average accuracy rate of 98.4% with an average response time of 1.8 seconds. based on the results obtained, this system shows a positive accuracy value and response time in its application. Keywords: blynk; internet of things; monitoring; water level  Abstrak: Sistem pengisian tandon air secara konvensional sering kali menimbulkan ketidakefisienan karena keterlambatan dalam pemantauan atau kegagalan sistem pelampung yang mengakibatkan meluapnya air dari tandon. penelitian ini bertujuan untuk mengembangkan sistem monitoring dan kontrol ketinggian air berbasis ESP32 dengan memanfaatkan teknologi IoT dan sensor ultrasonik, sistem ini dapat memudahkan pengguna dalam memonitoring ketinggian air dan mengotomatisasi kontrol pompa. Penelitian ini menggunakan metode eksperimen, mulai dari perancangan sistem hingga pengujian dan analisis sistem, serta pengujian yang meliputi akurasi sensor, respon sistem, dan kestabilan komunikasi dengan server IoT. Hasil pengujian menunjukkan bahwa sistem memiliki tingkat akurasi rata-rata sebesar 98,4% dengan waktu respon rata-rata 1,8 detik. berdasarkan hasil yang diperoleh, sistem ini menunjukkan nilai akurasi dan waktu respon yang positif dalam pengaplikasiannya. Kata kunci: blynk; internet of things; pemantauan; tingkat air 
OPTIMIZATION OF INCENTIVE GIVING THROUGH MULTI-CRITERIA DECISION ANALYSIS APPROACH Helmiah, Fauriatun; Siregar, Iqbal Kamil
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 2 (2025): Maret 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3723

Abstract

Abstract: This research aims to optimize the provision of incentives to employees (sales team) in a company using a multi-criteria approach. Many companies face challenges in determining criteria and mechanisms for providing incentives that are effective and fair to improve work performance and motivation. The multi-criteria approach used is Multi-Attribute Utility Theory (MAUT) which can assess various aspects of employee performance comprehensively and objectively. Factors considered include productivity, quality of work, attendance, innovation and overall turnover. The research results show that the multi-criteria approach provides a more comprehensive and accurate assessment, so that companies can develop a more transparent and effective incentive system. Implementation of this approach is expected to increase employee motivation and productivity, help companies achieve their business goals more efficiently, and provide long-term benefits in the form of increased employee loyalty and competitiveness in the field.Keywords: optimization; incentives; multi criteria; maut method         Abstrak: Penelitian ini bertujuan untuk mengoptimalkan pemberian insentif kepada karyawan (tim sales) di sebuah perusahaan dengan menggunakan pendekatan multikriteria. Banyak perusahaan menghadapi tantangan dalam menentukan kriteria dan mekanisme pemberian insentif yang efektif dan adil untuk meningkatkan kinerja dan motivasi kerja. Pendekatan multikriteria yang digunakan adalah  Multi-Attribute Utility Theory (MAUT) dapat mengevaluasi berbagai aspek kinerja karyawan secara menyeluruh dan objektif. Faktor-faktor yang dipertimbangkan meliputi produktivitas, kualitas kerja, kehadiran, inovasi dan omset keseluruhan. Hasil penelitian menunjukkan bahwa pendekatan multikriteria memberikan penilaian yang lebih komprehensif dan akurat, sehingga perusahaan dapat mengembangkan sistem insentif yang lebih transparan dan efektif. Implementasi pendekatan ini diharapkan dapat meningkatkan motivasi dan produktivitas karyawan, membantu perusahaan mencapai tujuan bisnisnya dengan lebih efisien, serta memberikan manfaat jangka panjang berupa peningkatan loyalitas karyawan dan daya saing di lapangan.Kata kunci: optimalisasi; insentif; multi kriteria; metode maut

Page 65 of 69 | Total Record : 685

 63   64   65   66   67 

Filter by Year

2017 2025


Reset
Filter By Issues
All Issue Vol. 12 No. 1 (2025): Desember 2025 Vol. 11 No. 4 (2025): September 2025 Vol 11, No 3 (2025): Juni 2025 Vol. 11 No. 3 (2025): Juni 2025 Vol 11, No 2 (2025): Maret 2025 Vol. 11 No. 2 (2025): Maret 2025 Vol. 11 No. 1 (2024): Desember 2024 Vol 11, No 1 (2024): Desember 2024 Vol 10, No 4 (2024): September 2024 Vol. 10 No. 4 (2024): September 2024 Vol 10, No 3 (2024): Juni 2024 Vol. 10 No. 3 (2024): Juni 2024 Vol. 10 No. 2 (2024): Maret 2024 Vol 10, No 2 (2024): Maret 2024 Vol 10, No 1 (2023): Desember 2023 Vol. 10 No. 1 (2023): Desember 2023 Vol. 9 No. 4 (2023): September 2023 Vol 9, No 4 (2023): September 2023 Vol 9, No 3 (2023): Juni 2023 Vol 9, No 2 (2023): Maret 2023 Vol 9, No 1 (2022): Desember 2022 Vol 8, No 3 (2022): Agustus 2022 Vol 8, No 2 (2022): April 2022 Vol 8, No 1 (2021): Desember 2021 Vol 7, No 3 (2021): Agustus 2021 Vol 7, No 2 (2021): April 2021 Vol 7, No 1 (2020): Desember 2020 Vol 6, No 3 (2020): August 2020 Vol 6, No 2 (2020): April 2020 Vol 6, No 1 (2019): December 2019 Vol 5, No 2 (2019): Juni 2019 Vol 5, No 1 (2018): Desember 2018 Vol 4, No 2 (2018): Juni 2018 Vol 4, No 1 (2017): Desember 2017 More Issue