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FEATURE ALIGNMENT OF THE INTERNAL QUALITY AUDIT SYSTEM BASED ON PPEPP Jollyta, Deny; Hajjah, Alyauma; Mukhsin, Mukhsin; Prihandoko, Prihandoko
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 11, No 3 (2025): Juni 2025
Publisher : Universitas Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i3.3896

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) 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

Transfer Learning Model Evaluation on CNN Algorithm: Indonesian Sign Language System (SIBI) Jollyta, Deny; Prihandoko, Prihandoko; Johan, Johan; Ramdhan, William; Santoso, Erick
Journal of Applied Business and Technology Vol. 6 No. 2 (2025): Journal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/jabt.v6i2.213

In Indonesia as much as elsewhere, the deaf can communicate using sign language. The Indonesian Sign Language System (SIBI) is one of the sign language systems used in Indonesia. A model produced by the Convolutional Neural Network (CNN) method can be used in computer science for the recognition of sign language. By using the Transfer Learning paradigm, CNN's performance may be enhanced. However, not many researches have been conducted to assess the effectiveness of transfer learning on sign language models, particularly those that use the TensorFlow library. In fact, the evaluation results can influence the selection of the transfer learning model together with CNN. This study aims to evaluate the efficacy of using the CNN model for SIBI sign language through Transfer Learning. The data used are images of 24 SIBI alphabets and are processed through the TensorFlow library. The images will be recognized through the transfer learning performance of 6 models, namely VGG16, VGG19, Resnet50, Desenet121, Inception-V3 and MobileNet-V2. The results of the study found that through the TensorFlow library, Mobilenetv2 had the highest accuracy of 78% after 20 epochs.

Penerapan Linear Discriminant Analysis Untuk Meningkatkan Kinerja Algoritma Support Vector Machine Gusrianty, Gusrianty; Fenly, Fenly; Jollyta, Deny; Erlin, Erlin; Putri, Ramalia Noratama; Oktariana, Dwi
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.8772

Obesity is a complex chronic disease influenced by various factors, such as genetic, environmental, and lifestyle, which is characterized by excess body weight due to the excessive accumulation of body fat. With the rapid advancement of technology and digitalization across all sectors, data has become increasingly vital, as large datasets generate valuable information. However, a key challenge in data analysis is addressing redundancy, noise, and high dimensionality, which can affect the performance of machine learning algorithms. This study aims to investigate the effectiveness of combining Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) in enhancing the accuracy and efficiency of high-dimensional data classification, particularly in predicting obesity levels. LDA is employed to reduce data dimensionality while retaining the most relevant features, whereas SVM is utilized as the classification algorithm to predict obesity levels based on patterns identified within the dataset. The research was conducted using a dataset consisting of 779 training samples and 195 testing samples. The results reveal that the combination of LDA and SVM achieved a classification accuracy of up to 99%, with a 50% reduction in data dimensionality and a computation speed of 0,0696 second. Moreover, computation time was significantly reduced, indicating that LDA not only facilitates data simplification but also improves the overall efficiency of the classification process.

Cluster Analysis Based on McKinsey 7s Framework in Improving University Services Jollyta, Deny; Oktarina, Dwi; Gusrianty; Astri , Renita; Kadim, Lina Arliana Nur; Dasriani, Ni Gusti Ayu
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

The epidemic of Covid-19 has impacted all aspects of human life, including education. Academic and administrative services for academic community are suffering, as a result of the fact that not all universities are able to provide online services to help break the chain of Covid-19 distribution. This is due to a lack of human competencies to use technology and a lack of information technology resources, necessitating the development of new strategies by universities to address these flaws. The goal of this study is to develop a university service strategy based on McKinsey 7s cluster results on the part that is having issues based on questionnaire data. The questionnaire is organized on seven McKinsey elements. The Manhattan distance calculation and the K-Medoids algorithm results demonstrated that the structure, system, skill and staff are all part of elements that clustered in k=2 and has to be addressed in aiding services during the Covid-19 pandemic. The McKinsey 7s showed that universities service enhancements may be achieved by combining clustering techniques and McKinsey framework.

IMPLEMENTASI AGILE DEVELOPMENT BERBASIS WEB BASED PADA SISTEM INVENTORY Akwilla, Hiskia; Jollyta, Deny
Jurnal Manajamen Informatika Jayakarta Vol 4 No 1 (2024): JMI Jayakarta (February 2024) Seleksi Paper SENATIKA-4 (October 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v4i1.1317

The inventory management at the Aeng store causes errors in the recognition of revenue and inventory calculation, making process inefficient and incurring losses. The purpose of this research is to analyze the needs required by Aeng Stores as well as design the application of the inventory system of good that can facilitate in carrying out the recording of sales and purchase reports, recording inventory reports, and recording supplier data. The test method used is the Black Box, which tests the software based on its external appearance and functionality, not the source code of the program. The results of this study show that applying Agile Development Method to inventory management brings many benefits. These include making inventory management processes more efficient, improving inventory accuracy, reducing excessive costs, and increasing responsiveness in a rapidly changing business environment. The conclusions derived from the tests that have been carried out, using Agile Development Method can be a fairly effective and efficient way for the Aeng Store to manage store inventory.

CLASSIFICATION OF FAKE NEWS IN INDONESIAN LANGUAGE USING SUPPORT VECTOR MACHINE METHOD Tandiano, Andreas Halim; Jollyta, Deny
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 2 (2024): Maret 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.v10i2.2895

Abstract: Since information and communication technology has become ingrained in our daily lives, it has become easier to access information. However, there are some concerns. One of them is about fake news. The aim of this study is to develop an Indonesian system for detecting false news by utilizing news headlines. The methods used are linear kernel support vector ma- chine and n-gram. According to the findings of the performance test that was carried out, the linear kernel support vector machine model employing the term frequency inverse document frequency unigram feature performs better than utilizing bigram. The precision value generated from the model performance test is 1.00. This means that the degree of accuracy in matching the requested information regarding fake news detection with the answers provided by the system is very good. Then the recall value generated is 0.99. This means the linear kernel support vector machine model using unigram news features is very effective for detecting fake news according to the text classification approach. Keywords: classification; fake news; n-gram; support vector machine Abstrak: Dengan adanya integrasi teknologi informasi dan komunikasi dalam kehidupan mem- buat kemudahan dalam mengakses informasi. Walaupun demikian, terdapat kekhawatiran akan beberapa hal. Salah satu di antaranya adalah berita palsu. Tujuan penelitian ini adalah merancang sistem deteksi berita palsu berbahasa Indonesia berdasarkan judul berita. Metode yang digunakan adalah Support Vector Machine kernel linier dan n-gram. Berdasarkan hasil uji performa, model Support Vector Machine kernel linier yang menggunakan fitur term frequency inverse document frequency unigram menunjukkan kinerja yang lebih baik dibandingkan bi- gram. Nilai precision yang dihasilkan dari uji performa model sebesar 1,00. Ini berarti derajat akurasi dalam mencocokkan informasi yang diminta mengenai deteksi berita palsu dengan ja- waban yang diberikan oleh sistem sangat baik. Kemudian nilai recall yang dihasilkan sebesar 0,99. Ini berarti model Support Vector Machine kernel linier dengan menggunakan fitur berita unigram sangat efektif untuk mendeteksi berita palsu menurut pendekatan teks klasifikasi. Kata kunci: klasifikasi; berita palsu; n-gram; support vector machine

FEATURE ALIGNMENT OF THE INTERNAL QUALITY AUDIT SYSTEM BASED ON PPEPP Jollyta, Deny; Hajjah, Alyauma; Mukhsin, Mukhsin; Prihandoko, Prihandoko
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.v11i3.3896

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) 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

Menciptakan Collaborative Learning Guru dan Peserta Didik Melalui Aplikasi Padlet Pada Sekolah Menengah Atas Pekanbaru Jollyta, Deny; Nasien, Dewi; Nora Marlim, Yulvia; Gustientiedina, Gustientiedina; Adiya, M. Hasmil; Mukhsin, Mukhsin; Rahmadian Yuliendi, Rangga; Kamal, Ahmad; Hajjah, Alyauma; Johan, Johan
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 8 No. 2 (2025): April 2025
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v8i2.3682

Collaborative Learning requires teachers and students to maintain an engaging learning environment at all times. Problems emerge when teachers, notably high school teachers in Pekanbaru, employ learning material that do not support this. Teachers' creativity is pushed to constantly update how they present materials and evaluate students' knowledge in order to foster a collaborative and pleasurable learning environment. This community service project will help Pekanbaru high school instructors create collaborative and real-time learning tools. The Community Service Team employed an observation strategy to get a sense of learning at Santa Maria High School, which served as an example school. The proposed solution is technologically based, making use of the Padlet application. The Community Service Team offers training methods on smartphones and computers to help people grasp Padlet. The community effort resulted in a polished Padlet that teachers may use to study with students at any time. It is intended that studying using the Padlet application would boost teacher innovation and student learning results at Santa Maria High School, as well as high schools around Pekanbaru.Keywords: Teacher; padlet; collaborative learning; learners;SMA. Abstrak: Pembelajaran Kolaboratif (Collaborative Learning) mengarahkan guru dan peserta didik dalam suasana belajar yang interaktif setiap saat. Permasalahan muncul pada saat media pembelajaran yang digunakan guru tidak mendukung hal tersebut, termasuk guru-guru Sekolah Menengah Atas (SMA) di Pekanbaru. Kreativitas guru ditantang untuk selalu memperbaharui cara penyampaian materi, cara mengevaluasi pemahaman peserta didik hingga penilaian, demi terciptanya suasana belajar yang kolaboratif dan menyenangkan. Kegiatan pengabdian ini bertujuan untuk membantu guru SMA di Pekanbaru dalam mempersiapkan bahan pembelajaran yang kolaboratif dan real time. Tim Pengabdian melakukan metode observasi untuk mendapatkan gambaran pembelajaran melalui SMA Santa Maria yang dijadikan sebagai sekolah sampel. Metode yang diusulkan berbasis teknologi melalui pemanfaatan aplikasi Padlet. Untuk memudahkan pemahaman Padlet, Tim Pengabdian menggunakan metode pelatihan, baik melalui komputer maupun smartphone. Hasil pengabdian adalah Padlet jadi yang dapat digunakan guru dalam pembelajaran bersama peserta didik setiap waktu. Diharapkan pembelajaran melalui aplikasi Padlet mampu meningkatkan kreativitas guru dan hasil belajar peserta didik SMA Santa Maria khususnya dan SMA di Pekanbaru umumnya.Kata kunci: guru; padlet; pembelajaran kolaboratif; peserta didik; SMA.

Optimisation Best Sales Assessment Using aCombination of Rank Order Centroid and Additive Ratio Asessment Algorithms Yulvia Nora Marlim; Erlin; Susanti, Wilda; Jollyta, Deny; Oktarina, Dwi
INOVTEK Polbeng - Seri Informatika Vol. 9 No. 2 (2024): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/0d6dw147

Employee assessment in a company is one of the tricks used to improve employee performance, so that it can be profitable for the company. One of the methods used to determine the best employees is to use a decision support system (DSS). By using DSS, decision making becomes faster, more accurate, efficient and effective. This study was used to determine the best sales at PT Surya Asia Abadi. By combining the Rank Order Centriod (ROC) Algorithm and Additive Ratio Assessment (ARAS) in the DSS, it can produce a better level of prediction accuracy and decision making based on the processed data. Where in this study using 6 (six) variables and 7 (seven) alternatives. The ROC algorithm is used to find the weight of each variable, and the weight obtained from the ROC is then processed using the ARAS algorithm to obtain alternative rankings. The purpose of this study is to make it easier for the Company to determine the best employees with more accurate results. The research results showed that the highest ranking was achieved by alternative AL3 with a value of 0.884 and the lowest was obtained by alternative AL1 with a value of 0.684.

Data Mining Earthquake Prediction with Multivariate Adaptive Regression Splines and Peak Ground Acceleration Dadang Priyanto; Bambang Krismono Triwijoyo; Deny Jollyta; Hairani Hairani; Ni Gusti Ayu Dasriani
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 3 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i3.3061

Earthquake research has not yielded promising results because earthquakes have uncertain data parameters, and one of the methods to overcome the problem of uncertain parameters is the nonparametric method, namely Multivariate Adaptive Regression Splines (MARS). Sumbawa Island is part of the territory of Indonesia and is in the position of three active earth plates, so Sumbawa is prone to earthquake hazards. Therefore, this research is important to do. This study aimed to analyze earthquake hazard prediction on the island of Sumbawa by using the nonparametric MARS and Peak Ground Acceleration (PGA) methods to determine the risk of earthquake hazards. The method used in this study was MARS, which has two completed stages: Forward Stepwise and Backward Stepwise. The results of this study were based on testing and parameter analysis obtained a Mathematical model with 11 basis functions (BF) that contribute to the response variable, namely (BF) 1,2,3,4,5,7,9,11, and the basis functions do not contribute 6, 8, and 10. The predictor variables with the greatest influence were 100% Epicenter Distance and 73.8% Magnitude. The conclusion of this study is based on the highest PGA values in the areas most prone to earthquake hazards in Sumbawa, namely Mapin Kebak, Mapin Rea, Pulau Panjang, and Pulau Saringi.

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