Abstract:Abstract: Information Technology has impacted various sectors, including education. Learning Management Systems (LMS) are designed to facilitate lecturers and students in accessing academic activities such as online learning.…
ning. This study aims to analyze the effectiveness of Learning Management Systems (LMS) among higher education institutions in Indonesia. This analysis is crucial for assessing the effectiveness of LMS use by universities in Indonesia, enabling investments in LMS to yield optimal results. The study employed the D&M IS Success Model and PLS-SEM to evaluate the relationships between various variables, including system, information, service quality, user satisfaction, and benefits. Simple random sampling was used to collect data from 170 universities in Indonesia. This study employed PLS-SEM to investigate the observed variables, including validity and reliability testing, which involves assessing reliability, convergent validity, and discriminant validity. This current study found that all the hypotheses were accepted with p-values below 0,05. These findings contribute to universities paying attention to aspects of system, information, and service quality in Learning Management Systems (LMS) to improve user satisfaction and create a positive perception of benefits. Therefore, this research yields significant results that contribute to higher education in Indonesia, as well as the advancement of knowledge in management information systems.
Keywords: delone and mclean; information system success; LMS; SEM-PLS.
Abstrak: Teknologi Informasi telah memengaruhi berbagai sektor, termasuk pendidikan. Learning Management System (LMS) dirancang untuk memfasilitasi dosen dan mahasiswa dalam mengakses kegiatan akademik seperti pembelajaran daring. Penelitian ini bertujuan untuk menganalisis efektivitas penggunaan Learning Management System (LMS) di perguruan tinggi di Indonesia. Analisis ini penting untuk menilai sejauh mana efektivitas penggunaan LMS oleh universitas-universitas di Indonesia, sehingga investasi dalam LMS dapat mem-berika n hasil yang optimal.Penelitian ini menggunakan model D&M IS Success Model dan metode PLS-SEM untuk mengevaluasi hubungan antara berbagai variabel, termasuk kuali-tas sistem, informasi, layanan, kepuasan pengguna, dan manfaat. Teknik simple random sampling digunakan untuk mengumpulkan data dari 170 perguruan tinggi di Indonesia. Penelitian ini menggunakan PLS-SEM untuk mengkaji variabel-variabel yang diamati, ter-masuk pengujian validitas dan reliabilitas, yang mencakup penilaian reliabilitas, validitas konvergen, dan validitas diskriminan. Hasil dari penelitian ini menunjukkan bahwa semua hipotesis diterima dengan nilai p di bawah 0,05. Temuan ini mendorong universitas untuk memberikan perhatian pada aspek kualitas sistem, informasi, dan layanan dalam penggunaan LMS guna meningkatkan kepuasan pengguna dan menciptakan persepsi posi-tif terhadap manfaatnya. Oleh karena itu, penelitian ini memberikan hasil yang signifikan bagi perguruan tinggi di Indonesia serta turut berkontribusi dalam pengembangan ilmu di bidang sistem informasi manajemen.
Kata kunci: delone and mclean; kesuksesan sistem informasi; LMS; SEM-PLS
Abstract:Face recognition has become a common thing used in the field of surveillance and security in computer technology and image devices. This study aims to identify the usefulness of a person's face on 3 test images. This study…
dy examines the methods of cropping techniques, image enhancement through intensity measurement, and histogram analysis to improve the contrast and distribution of image intensity. In addition, the Viola-Jones algorithm is used to detect key facial features such as eyes, nose, and mouth. The results of the analysis are then applied in the feature evaluation stage, where usually between facial features are applied to measure the ratio of facial proportions. Furthermore, the comparison of proportional ratios of several images was analyzed using bar graphs and line graphs to evaluate the trend and stability of facial proportions. The results showed the best ratio stability with a smaller variation of the on-off ratio of image 2 which is 0.4762 pixels to 0.4983 pixels. Image 2 is the most ideal for face measurement systems based on geometric ratios because it provides more consistent and visible results.
Abstract:Abstract: Air quality in urban areas is becoming an increasingly important issue considering its impact on human health and the environment. The rapid increase in air pollution requires effective methods to predict air quality…
uality in order to take appropriate mitigation measures. This study aims to analyze the use of Neural Network (NN) algorithms in predicting air quality in cities. The method used is the application of the NN model, especially the Multilayer Perceptron (MLP), which is trained using historical air quality data such as dust particle levels (PM10, PM2.5), carbon monoxide (CO) gas, and temperature. The data used in this study came from urban air quality monitoring stations collected over a period of time. The results show that the Neural Network algorithm can provide quite accurate predictions of air quality with a low Mean Absolute Error (MAE) value, showing the effectiveness of the model in predicting f fluctuations in air quality. The conclusion of this study is that Neural Network algorithms, specifically MLPs, are an effective tool for air quality prediction, which can be used as a basis for urban air quality management policies.
Keywords: air quality; neural network; prediction; multilayer perceptron (MLP)
Abstrak: Kualitas udara di perkotaan menjadi isu yang semakin penting mengingat dampaknya terhadap kesehatan manusia dan lingkungan. Peningkatan polusi udara yang pesat memerlukan metode yang efektif untuk memprediksi kualitas udara guna mengambil langkah mitigasi yang tepat. Penelitian ini bertujuan untuk menganalisis penggunaan algoritma Neural Network (NN) dalam memprediksi kualitas udara di perkotaan. Metode yang digunakan adalah penerapan model NN, khususnya Multilayer Perceptron (MLP), yang dilatih menggunakan data kualitas udara historis seperti kadar partikel debu (PM10, PM2.5), gas karbon monoksida (CO), dan suhu. Data yang digunakan dalam penelitian ini berasal dari stasiun pemantauan kualitas udara di perkotaan yang dikumpulkan selama periode waktu tertentu. Hasil penelitian menunjukkan bahwa algoritma Neural Network dapat memberikan prediksi yang cukup akurat terhadap kualitas udara dengan nilai Mean Absolute Error (MAE) yang rendah, menunjukkan efektivitas model dalam memprediksi fluktuasi kualitas udara. Simpulan dari penelitian ini adalah bahwa algoritma Neural Network, khususnya MLP, merupakan alat yang efektif untuk prediksi kualitas udara, yang dapat digunakan sebagai dasar untuk kebijakan pengelolaan kualitas udara di perkotaan
Kata kunci: kualitas udara; neural network; prediksi; multilayer perceptron (MLP)
Abstract:Abstract: The online exam system is used to evaluate student learning, but it has some limitations. Therefore, it is necessary to research the user satisfaction of the system. This study aims to assess user satisfaction…
using the End User Computing Satisfaction (EUCS), Importance Performance Analysis (IPA), and Customer Satisfaction Index (CSI) methods. The results showed that three dimensions, namely, accuracy, ease of use, and timeliness significantly affected user satisfaction, while content and format did not have a significant effect. IPA analysis shows the majority of attributes (12 attributes) are in quadrant II, which indicates moderate satisfaction, 11 attributes in quadrant III, one attribute in quadrant I, and three attributes in quadrant IV. CSI concluded that the online exam system provides satisfactory service with a score of 77.54%.
Keywords: csi; eucs; ipa; online exam system; user satisfaction
Abstrak: Sistem ujian online digunakan untuk mengevaluasi pembelajaran mahasiswa, tetapi sistem ini memiliki beberapa keterbatasan. Karena itulah perlu penelitian kepuasan pengguna sistem tersebut. Penelitian ini bertujuan menilai kepuasan pengguna dengan menggunakan metode End User Computing Satisfaction (EUCS), Importance Performance Analisys (IPA), dan Customer Satisfaction Index (CSI). Hasil riset menunjukkan tiga dimensi yaitu, akurasi, kemudahan penggunaan, dan ketepatan waktu signifikan mempengaruhi kepuasan pengguna, sementara konten dan format tidak berpengaruh signifikan. Analisis IPA menunjukkan mayoritas atribut (12 atribut) berada di kuadran II, yang mengindikasikan kepuasan sedang, 11 atribut di kuadran III, satu atribut di kuadran I, dan tiga atribut di kuadran IV. CSI menyimpulkan sistem ujian online memberikan layanan yang memuaskan dengan skor 77,54%.
Kata kunci: csi; eucs; ipa; kepuasan pengguna; sistem ujian online
Abstract:Abstract: Uterine disease is a serious threat to women's health, which can affect fertility and quality of life. Delayed diagnosis often results in patients not getting optimal early treatment at the H. Abdul Manan Simatupang…
upang Kisaran Regional General Hospital. This study aims to develop a fuzzy logic-based expert system to diagnose uterine disease based on the symptoms experienced by patients. This system receives symptom data as input, then performs analysis using the fuzzy logic method to determine the level of possibility of a disease. The final results produced are an initial diagnosis and treatment recommendations. System testing shows that this method is able to identify uterine disease with fairly good accuracy, where one case showed the possibility of Endometriosis with a confidence level of 63%. With this system, patients can obtain initial information about their health condition, so they can take more appropriate and faster medical steps.
Keywords: expert system; fuzzy logic; uterine disease.
Abstrak: Penyakit rahim merupakan ancaman serius bagi kesehatan wanita, yang dapat berdampak pada kesuburan dan kualitas hidup. Keterlambatan diagnosis sering kali menyebabkan pasien tidak mendapatkan penanganan dini yang optimal di Rumah Sakit Umum Daerah H. Abdul Manan Simatupang Kisaran. Penelitian ini bertujuan untuk mengembangkan sistem pakar berbasis logika fuzzy guna mendiagnosis penyakit rahim berdasarkan gejala yang dialami pasien. Sistem ini menerima data gejala sebagai input, kemudian melakukan analisis menggunakan metode logika fuzzy untuk menentukan tingkat kemungkinan suatu penyakit. Hasil akhir yang dihasilkan berupa diagnosis awal dan rekomendasi penanganan. Pengujian sistem menunjukkan bahwa metode ini mampu mengidentifikasi penyakit rahim dengan akurasi yang cukup baik, di mana salah satu kasus menunjukkan kemungkinan penyakit Endometriosis dengan tingkat kepercayaan sebesar 63%. Dengan adanya sistem ini, pasien dapat memperoleh informasi awal mengenai kondisi kesehatannya, sehingga dapat mengambil langkah medis yang lebih tepat dan cepat.
Kata kunci: fuzzy logic; penyakit rahim; sistem pakar.
Abstract:Abstract: The use of e-learning in non-formal education is increasingly important to support the improvement of access to learning, one of which is through the online platform. This study aims to analyze the quality of online…
nline services using WebQual 4.0 and Im-portance Performance Analysis (IPA) methods to evaluate the suitability between user expectations and perceptions. The research method used a quantitative approach by distributing questionnaires to active users, then analyzed using the WebQual Index to measure the overall quality of the system as well as the IPA to determine improvement priorities. The results showed that the quality of SeTARA Online was relatively good with a WebQual Index value of 0.798. However, there is still a gap between user expectations and satisfaction with a negative gap value of -0.238. The IPA analysis identified indicators in Quadrant I as priority improvements, especially in the aspects of service interaction and information presentation. These findings underscore the need for continuous development of features and technical support to optimize the user experience. The conclusion of this study suggests that there should be improvements in priority indicators to increase user satisfaction, as well as strengthen the effectiveness of online learning. Advanced research can expand variables, compare with other platforms, and combine quantitative and qualitative analysis methods for more comprehensive results.
Keywords: e-learning; importance performance analysis; quality of service; online equivalent; webqual 4.0
Abstract:Abstract: The Halodoc application, as a digital healthcare service platform, has been widely used for various medical purposes, such as doctor consultations, medication purchases, and laboratory services. User interactions…
ns and reviews play a crucial role in enhancing service quality. Sentiment analysis was conducted using the Support Vector Machine (SVM) method to assess user perceptions and satisfaction based on reviews obtained from the Google Play Store platform. The analysis process included data collection, text preprocessing, data transformation using TF-IDF, and training an SVM model to predict sentiment. The model achieved its highest accuracy of 88.32% in the first scenario. However, accuracy slightly decreased in the second and third scenarios, reaching 86.25% and 86.94%, respectively. The analysis results indicated that the model performed best in the first scenario, with the lowest number of prediction errors. Additionally, the model was more accurate in classifying negative and positive sentiments than neutral ones.
Keywords: halodoc application; sentiment analysis; support vector machine algorithm
Abstrak: Aplikasi Halodoc, sebagai platform layanan kesehatan digital, telah banyak digunakan untuk berbagai keperluan medis seperti konsultasi dokter, pembelian obat, dan layanan laboratorium. Interaksi pengguna dan ulasan mereka memiliki peran krusial dalam meningkatkan mutu layanan. Analisis sentimen dilakukan dengan menggunakan metode Support Vector Machine (SVM) untuk mengetahui persepsi dan kepuasan pengguna berdasarkan ulasan yang diperoleh dari Platform Google Play Store. Proses analisis mencakup pengumpulan data, pra-pemrosesan teks, transformasi data menggunakan TF-IDF, dan pelatihan model SVM untuk memprediksi sentimen. Hasil pelatihan model dengan akurasi tertinggi sebesar 88,32% pada skenario pertama. Akurasi sedikit menurun pada skenario kedua dan ketiga, masing-masing sebesar 86,25% dan 86,94%, Hasil analisa menunjukkan bahwa model memiliki performa terbaik pada skenario pertama dengan jumlah kesalahan prediksi terkecil. Selain itu, model cenderung lebih akurat dalam mengklasifikasikan sentimen negatif dan positif dibandingkan netral..
Kata kunci: algoritma support vector machine; analisis sentimen; aplikasi halodoc
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…
ding 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
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…
velop 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
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…
ms 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.