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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Indonesia Symposium on Computing Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Syntax Literate : Jurnal Ilmiah Indonesia Jurnal ULTIMATICS JURIKOM (Jurnal Riset Komputer) eProceedings of Engineering Community Service Seminar and Community Engagement (COSECANT)
Laksitowening, Kusuma Ayu
Telkom University
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Other

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Perencanaan Corporate Information Factory pada Perguruan Tinggi di Indonesia dengan Mengadopsi Pendekatan Arsitektur Informasi Yanuar Firdaus Arie Wibowo; Kusuma Ayu Laksitowening; Amarilis Putri Yanuarifiani
Indonesia Symposium on Computing Indonesia Symposium on Computing 2015
Publisher : Indonesia Symposium on Computing

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Abstract

Pengukuran tingkat capaian fungsi tridharma yang dijalankan oleh perguruan tinggi diukur dengan penjaminan mutu internal, maupun eksternal dalam bentuk akuntabilitas publik melalui akreditasi. Pemenuhan instrumen penjaminan mutu membutuhkan dukungan data pada setiap kriteria penilaian. Sejalan dengan perkembangan organisasi, kompleksitas data yang dikelola akan semakin meningkat. Pada tingkatan inilah, dibutuhkan sebuah ekosistem informasi yang tepat. Corporate Information Factory (CIF), yaitu konsep yang menggambarkan arsitektur logis intelejensia bisnis dan manajemen bisnis dari data operasional institusi secara terpadu. Penerapan CIF pada perguruan tinggi dapat menjadi solusi dalam pengelolaan data dan informasi di berbagai level. Penerapan CIF membutuhkan tinjauan strategis meng Y. F. A. Wibowo and K. A. Laksitowening, “Arsitektur dan Model Pengembangan Sistem Informasi Terpadu Menuju Tata Kelola dan Penjaminan Mutu Perguruan Tinggi,” Seminar Nasional Menuju Masyarakat Madani dan Lestari. Universitas Islam Indonesia, Yogyakarta, Indonesia, pp. 607–616, 2012. ingat usaha dan sumber daya yang dikeluarkan oleh organisasi. Oleh karena itu, perguruan tinggi perlu mengadopsi pendekatan arsitektur informasi, untuk mendapatkan perspektif yang menyeluruh dan sistematis terhadap kebutuhan perguruan tinggi akan penyediaan dan pengelolaan informasi.  
ANALISA PERBANDINGAN RESPONSE TIME DAN THROUGHPUT PADA XML DAN DBMS SEBAGAI MEDIA PENYIMPANAN DATA Ragil Martha; Yanuar Firdaus; Kusuma Ayu Laksitowening
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2010
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Abstract

In the environment where information exchanges running rapidly, performance becomes a matter that isabsolutely necessary to ensure the accuracy and speed of information delivery. Response time and throughputare two of the performance parameters that could be considered in choosing data storage media. A DBMS is aset of software programs that controls the organization, storage, management, and retrieval of data in adatabase. Along with the development of information technology, the needs of DBMS as storage media would becrucial. In addition to DBMS, there is another data storage format -had a similar structure to that relational-named XML. Nowadays Native XML Databases had been introduced as a new technology of XML. In NativeXML Databases, XML files could be related one to another just like in DBMS. The objective of the research wasto analyze what is best between those two data storage format. The analysis result concluded that DBMS givelower response time and greater throughput.Keywords: Native XML Database, XML, DBMS, response time, throughput
OPTIMASI APLIKASI WEB BERBASIS FRAMEWORK SYMFONY DENGAN TWEAK VIEW DAN TWEAK CACHE Hendriana Mayang Sari; Kusuma Ayu Laksitowening; Hetti Hidayati
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2010
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Abstract

Seiring dengan pesatnya perkembangan aplikasi web saat ini, maka performansi aplikasi adalah isu yangsangat penting untuk diperhatikan oleh developer. Agar dapat terus memenuhi user expectation terhadapperforma aplikasi tanpa menambah resource perangkat keras, maka solusi yang mungkin dilakukan adalahmelakukan optimasi dari sisi scripting aplikasi. Symfony adalah sebuah framework berbasis PHP 5 yangmemfasilitasi developer dengan langkah-langkah optimasi yang dinamakan Tweak Method. Tweak Methoddapat dilakukan dengan 3 cara : Tweak Model, Tweak View, dan Tweak cache. Dalam studi kasus ini penulismengimplementasikan Tweak View dan Tweak cache. Pada Tweak View, langkah optimasi yang dilakukan fokuspada bagaimana mengurangi byte transferred. Sedangkan pada Tweak cache, proses optimasi yang dilakukanadalah mengimplementasikan teknologi PHP Cache yang berfungsi untuk cache opcode dari response.Hasilnya, pengimplementasian Tweak Method pada aplikasi kasus dapat mempercepat Response Time hingga99.26% dan byte transferred hingga 88.05% dari sebelumnya.Kata kunci : performa, optimasi, Tweak Method, Tweak View, Tweak Cache
Temporal Prediction on Students’ Graduation using Naïve Bayes and K-Nearest Neighbor Algorithm Ahmad Marzuqi; Kusuma Ayu Laksitowening; Ibnu Asror
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2919

Abstract

Accreditation is a form of assessment of the feasibility and quality of higher education. One of the accreditation assessment factors is the percentage of graduation on time. A low percentage of on-time graduations can affect the assessment of accreditation of study programs. Predicting student graduation can be a solution to this problem. The prediction results can show that students are at risk of not graduating on time. Temporal prediction allows students and study programs to do the necessary treatment early. Prediction of graduation can use the learning analytics method, using a combination of the naïve bayes and the k-nearest neighbor algorithm. The Naïve Bayes algorithm looks for the courses that most influence graduation. The k-nearest neighbor algorithm as a classification method with the attribute limit used is 40% of the total attributes so that the algorithm becomes more effective and efficient. The dataset used is four batches of Telkom University Informatics Engineering student data involving data index of course scores 1, level 2, level 3, and level 4 data. The results obtained from this study are 5 attributes that most influence student graduation. As well as the results of the presentation of the combination naïve bayes and k-nearest neighbor algorithm with the largest percentage yield at level 1 75.40%, level 2 82.08%, level 3 81.91%, and level 4 90.42%.
Test Case Analysis with Keyword-Driven Testing Approach on Angkasa Website Using Katalon Studio Tools Reynaldi Prama Octavially; Rosa Reska Riskiana; Kusuma Ayu Laksitowening; Dana Sulistyo Kusumo; Monterico Adrian; Nungki Selviandro
Ultimatics : Jurnal Teknik Informatika Vol 13 No 2 (2021): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v13i2.2391

Abstract

Abstract— Testing a software is an important stage of a series of software development. Functional testing of each feature on the Angkasa website is intended to try out the function to match the required specifications. To achieve a functional test result, there are elements of features on the web page that require keywords. These keywords are used to perform actions or actions in running a web page, these keywords will help in making Test Cases for the testing process. Because it takes the right keywords to test on the web. To overcome this problem, this study analyzes the use of the Keyword Driven Testing approach for making Test Cases through the Katalon Studio tools. Keyword Driven Testing is one of the concepts in ISO/IEC/IEEE 29119, namely Keyword Driven Testing in The Test Design Process. The results of the analysis show that making Test Cases with Keyword Driven testing is easier to understand and is fully supported by the Katalon Studio tools. However, when creating test cases, not all keywords can be added automatically, so they need to be added manually.
Predicting Students’ Performance In Basic Algorithms Programming In an E-Learning Environment Using Decision Tree Approach Jonas de Deus Guterres; Kusuma Ayu Laksitowening; Febryanti Sthevanie
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : CV. Ridwan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (206.598 KB) | DOI: 10.36418/syntax-literate.v7i1.5733

Abstract

Predicting the performance of students plays an important role in every institution to protect their students from failures and leverage their quality in higher education. Algorithm and Programming is a fundamental course for the students who start their studies in Informatics. Hence, the scope of this research is to identify the critical attributes which influence student performance in the E-learning Environment on Moodle LMS (Learning Management System) Platform and its accuracy. Data mining helps the process of preprocessing data in a dataset from raw data to quality data for advanced analysis. Dataset set is consisting of student academic performance such as grades of Quizzes, Mid exams, Final exams, and Final projects. Moreover, the dataset from LMS is considered as well in the process of modeling, in terms of constructing the decision tree, such as punctuality submission of Quizzes, Assignments, and Final Projects. Regarding the Basic Algorithm and Programming course, which is separated into two subjects in the first and second semester, thus the research will predict the student performance in the Basic Algorithm and programming course in the second semester based on the Introduction to programming course in the first semester. Decision Tree techniques are applied by using information gain in ID3 algorithm to get the important feature which is the PP index has the highest information gain with value 0.44, also the accuracy between ID3 and J48 algorithm that shows ID3 has the highest accuracy of modeling which is 84.80% compared to J48 82.34%.
Penerapan Metode Collaborative Filtering Untuk Personalized Learning Content Pada Learning Management System (LMS) Muhammad Alfian Fathurrahman; Kusuma Ayu Laksitowening; Dawam Dwi Jatmiko Suwawi
JURIKOM (Jurnal Riset Komputer) Vol 9, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i2.3887

Abstract

The delivery of appropriate learning content can be one of the factors that can increase satisfaction, motivation, and interest of learners during learning sessions. But on the other hand, due to a large amount of learning content available on LMS (Learning Management System) and the difficulty of determining learning content that suits the needs and interests of each learner, it often causes some learning content to be overlooked by them. Therefore, this paper aims to design a personalized learning content system in LMS for learners. The main objective of this study is to provide learning content suggestions or recommendations for learners, based on the course module they previously accessed by applying Collaborative Filtering method. This method is used by utilizing dataset in the form of implicit feedback, obtained from the activities of learners when interacting with LMS. The UAT (User Acceptance Test) results show that the personalization system has been well received by as many as 82.67% of learners based on three aspects, those are interface, user, and system interaction aspects. Moreover, the MAE (Mean Absolute Error) calculation shows that this system has the best accuracy rate at a 10% sparsity level with the lowest average value of 0.4514.
Analysis of Student Performance Based on LMS Activities with Learning Analytics Approach Dawam Dwi Jatmiko Suwawi; Hafizh Jihaad Husni; Kusuma Ayu Laksitowening
JURIKOM (Jurnal Riset Komputer) Vol 8, No 6 (2021): Desember 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v8i6.3721

Abstract

Good performance for a student during a course is important because it can affect the student's final index. However, in general, student performance can only be seen at the end of the semester, so if a student has a poor performance before the course ends, they do not get enough opportunity to improve. Therefore, it is necessary to have an early analysis of students who have poor performance in a course. Since most student learning activities in this pandemic era are currently on the LMS, the LMS activity log can reflect student performance. The main objective of this study is to classify the LMS activity log in a course using a probabilistic classifier algorithm. This study chose Naïve Bayes to classify student performance into three categories – good, satisfactory, and poor. The dataset is separated into two scenarios – the half-semester and the full-semester - in the Modeling and Database Implementation course at Telkom University. The results show that the Naïve Bayes Algorithm successfully predicts student performance early and provides information about students experiencing changes in performance with the highest accuracy of 93%. The practical implication of this study is that teachers can use the LMS activity log for early prediction of student success in passing a course. The learning analytics developed in this study prove that Naïve Bayes has a fairly good performance for small dataset sizes based on recall and accuracy to classify student performance. However, as the study focuses solely on a specific course and small dataset sizes, it lacks generalizability. Therefore, it needs to be tested for other courses and larger dataset sizes.
Capturing Students’ Dynamic Learning Pattern Based on Activity Logs Using Hierarchical Clustering Kusuma Ayu Laksitowening; Made Diva Prasetya; Dawam Dwi Jatmiko Suwawi; Anisa Herdiani
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 1 (2023): February 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i1.4655

Abstract

Students can have various characteristics and learning patterns. By understanding the characteristics and learning pattern of individual students, teachers can provide individualized learning strategies based on students' needs. Students' learning patterns may experience changes depending on their conditions during the learning process. If the learning pattern analysis is only run once, then the progress and changes in student learning patterns throughout the learning process cannot be recognized. On the other hand, periodical analysis is expected to describe the dynamics of student learning patterns from time to time. This research is intended for capturing students' dynamic learning pattern using Hierarchical Clustering. We clustered the learning patterns based on Learning Management Systems (LMS) activity logs. The activity log data were partitioned into several periodical datasets. The results of the periodic clustering indicated that students’ learning patterns varied from one another and changed from time to time. Most students experienced change in learning patterns throughout the semester. The analysis also indicated that learning pattern also has the potential to be improved and maintained.
Implementasi Dan Analisis Konsep Personal Learning Environment Pada Learning Management System Irwinda Putri; Kusuma Ayu Laksitowening; Dawam Dwi Jatmiko Suwawi
eProceedings of Engineering Vol 2, No 2 (2015): Agustus, 2015
Publisher : eProceedings of Engineering

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Abstract

Abstrak Sebagai aplikasi e-learning, Learning Management System (LMS) cenderung lebih  memfasilitasi kebutuhan institusi dimana tools dan konten belajar ditentukan oleh pengajar atau institusi, serta disimpan dan dikelola secara terpusat. Akibatnya, LMS kurang fleksibel bagi pelajar untuk mengelola lingkungan belajarnya sendiri. serta berkolaborasi dan berbagi pengetahuan dengan pelajar lain. Keterbatasan itu  dapat ditangani dalam konsep Personal Learning Environment (PLE) yang memfasilitasi pelajar membangun lingkungan belajarnya sendiri serta mendukung kolaborasi dan berbagi pengetahuan dengan pelajar lain tanpa terikat institusi. Pada penelitian ini, dikemukakan bagaimana konsep PLE dapat diterapkan pada LMS melalui sebuah aplikasi yang mendukung konsep PLE kemudian mengintegrasikannya dengan LMS. Ini memungkinkan pelajar membangun PLE-nya melalui LMS sehingga hal baru yang perlu dipelajari dapat dikurangi. Pada akhir penelitian dilakukan expert evaluation untuk mengetahui kualitas aplikasi dari segi kemudahan navigasi, program bantuan atau tutorial, teknis dan estetika, serta kualitas aplikasi dalam membangun sebuah PLE. Hasil evaluasi menunjukkan bahwa dari sudut pandang expert dua aspek terakhir dinilai sudah cukup baik. Kata kunci: learning management system, personal learning environment, expert evaluation
Co-Authors Ady Purna Kurniawan Ahmad Marzuqi Amarilis Putri Yanuarifiani Amarilis Putri Yanuarifiani Anisa Herdiani Aprianti Putri Sujana Dana Sulistyo Kusumo Dawam Dwi Jatmiko Suwawi Demsy Setiawan Elis Hernawati Febryanti Sthevanie Hafiyy Viazola Aziz Hafizh Jihaad Husni Hendriana Mayang Sari Hetti Hidayati Ibnu Asror Irwinda Putri Jonas de Deus Guterres Made Diva Prasetya Monterico Adrian Muhammad Alfian Fathurrahman Muhammad Fardan Nungki Selviandro Nungki Selviandro Ragil Martha Ramanti Dharayani Reynaldi Prama Octavially Rikman Aherliwan Rudawan Rosa Reska Riskiana Siti Rahmah Amaliah Suryatiningsih Yanuar Firdaus Yanuar Firdaus Arie Wibowo