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All Journal Jurnal Dedikasi Perfecting a Video Game with Game Metrics Jurnal Simantec Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal Informatika: Jurnal Pengembangan IT Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) Fountain of Informatics Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Informatika Universitas Pamulang Jurnal Repositor JIKA (Jurnal Informatika) Tematik : Jurnal Teknologi Informasi Komunikasi Jurnal Nasional Teknik Elektro dan Teknologi Informasi

Gita Indah Marthasari

Universitas Muhammadiyah Malang

Author-ID : 630014

Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Public Health

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Analisis Pengaruh System Quality, Information Quality, Service Quality Terhadap Net Benefit Pada Sistem KRS-Online UMM Fathoni, Muhammad Asrar; Marthasari, Gita Indah; Suharso, Wildan
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 2, No 3, August-2017
Publisher : Universitas Muhammadiyah Malang

Implementasi sistem informasi KRS-online dalam perkuliahan digunakan untuk membantu proses penyusunan KRS oleh setiap mahasiswa Universitas Muhammadiyah Malang. Penelitian ini bertujuan untuk mengukur dan menguji variabel-variabel serta indikator yang mempengaruhi kesuksesan sistem informasi KRS-online UMM. Model penelitian ini mengadopsi model penelitian DeLone and Mclean IS Success. Kuesioner yang disusun dalam penelitian ini disebarkan kepada 100 responden yang memiliki kualifikasi sebagai mahasiswa pengguna sistem KRS-online. Uji validitas dan uji reliabilitas dilakukan untuk memperoleh data yang valid dan reliabel. Hasil penelitian menunjukkan bahwa kualitas sistem memiliki pengaruh yang signifikan terhadap kepuasan pengguna, kualitas informasi memiliki pengaruh yang signifikan terhadap kepuasan pengguna, kualitas layanan memiliki pengaruh yang signifikan terhadap kepuasan pengguna dan kepuasan pengguna memiliki pengaruh yang signifikan terhadap net benefit. Berdasarkan hasil Analisis ditunjukkan bahwa kesuksesan sistem informasi KRS-online UMM memiliki persentase sebesar 70,5% yang artinya kesuksesan sistem informasi KRS-online UMM berada pada tingkatan sukses.

Improvement of Cluster Importance Algorithm with Sentence Position for News Summarization Hayatin, Nur; Marthasari, Gita Indah; Anggraini, Syadza
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Text summarization is one of the ways to reduce large document dimension to obtain important information from the document. News is one of information which usually has several sub-topics from a topic. In order to get the main information from a topic as fast as possible, multi-document summarization is the solution, but sometimes it can create redundancy. In this study, we used cluster importance algorithm by considering sentence position to overcome the redundancy. Stages of cluster importance algorithm are sentence clustering, cluster ordering, and selection of sentence representative which will be explained in the subsections below. The contribution of this research was to add the position of sentence in the selection phase of representative sentence. For evaluation, we used 30 topics of Indonesian news tested by using ROUGE-1, there were 2 news topics that had different ROUGE-1 score between using cluster importance algorithm by considering sentence position and using cluster importance. However, those 2 news topics which used cluster importance by considering sentence position have a greater score of Rouge-1 than the one which only used cluster importance. The use of sentence position had an effect on the order of sentence on each topic, but there were only 2 news topics that affected the outcome of the summary.

PELATIHAN LITERASI DIGITAL PADA PEREMPUAN KELOMPOK BINAAN SEKOLAH IBU ARJOSARI MALANG Sulistyowati, Tutik; Hayatin, Nur; Marthasari, Gita Indah
Jurnal Dedikasi Vol 16 (2019): Mei
Publisher : Direktorat Penelitian dan Pengabdian Kepada Masyarakat

Kurangnya partisipasi dan ketertarikan perempuan terhadap teknologi adalah masalah yang butuh diselesaikan. Hal ini dikarenakan tuntutan era millennial dimana sebagian besar aktifitas manusia dilakukan dengan menggunakan teknologi. Dari latar belakang itulah, maka usulan program pengabdian ini bertujuan untuk memberikan pelatihan literasi digital dalam upaya meningkatkan pemahaman TIK bagi perempuan khususnya ibu rumah tangga agar terampil dan bijak dalam menggunakan teknologi. Adapun mitra yang digandeng adalah ibu-ibu kelompok binaan dari sekolah ibu arjosari. Program ini memberikan pelatihan sekaligus pendampingan terkait dengan literasi digital untuk ibu rumah tangga, meliputi: internet sehat, pengelompokkan batas usia anak dalam menggunakan dan mengakses aplikasi internet, serta filtering berita hoax untuk ibu rumah tangga. Hasil dari evaluasi kegiatan menggunakan kuesionar dapat disimpulkan bahwa semua peserta sepakat kegiatan ini memberi manfaat untuk mendukung kegiatan mereka khususnya meningkatkan pemahaman terkait dengan literasi digital dan ketrampilan untuk memberi keamanan penggunaan ponsel bagi anak-anak.

Optimization of Sentiment Analysis for Indonesian Presidential Election using NaÃ¯ve Bayes and Particle Swarm Optimization Hayatin, Nur; Marthasari, Gita Indah; Nuarini, Lia
JOIN (Jurnal Online Informatika) Vol 5, No 1 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i1.558

Twitter can be used to analyze sentiment to get public opinion about public figures to find a trend in positive or negative responses, especially to analyze sentiments related to presidential candidates in the 2019 election in Indonesia. NaÃ¯ve Bayes (NB) can be used to classify tweet feed into polarity class negative or positive, but it still has low accuracy. Therefore, this study optimizes the NaÃ¯ve Bayes algorithm with Particle Swarm Optimization (NB-PSO) to classify opinions from twitter feeds to get a good accuracy of public figures sentiment analysis. PSO used to select features to find optimization values to improve the accuracy of NaÃ¯ve Bayes. There are four steps to optimize NB using PSO, i.e., initializing the population (swarm), calculate the accuracy value that matched with selected features, selected the best accuracy of classification, and updating position and velocity. From this study, the group of tweets was obtained based on the positive and negative sentiments from the community towards two Indonesia presidential candidates in 2019. The NB-PSO test shows the accuracy result of 90.74%. The result of accuracy increases by 4.12% of the NB algorithm. In conclusion, the inclusion of the Particle Swarm Optimization algorithm for NaÃ¯ve Bayes classification algorithm gives a significant accuracy, especially for sentiment analysis cases.

Quantitative analysis in a heuristic evaluation of web-based encyclopedia for children Gita Indah Marthasari; Nur Hayatin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.20408

Anapedia is a web-based encyclopedia designed specifically for children. The web was built because there are still very few Indonesian-language encyclopedias for children. This paper presents an evaluation of the usability of the Anapedia website developed for children in Indonesia to retrieve information available in a wide range of areas. In the context of usability evaluation of children encyclopedia, this is the first study to analyze usability problems identified by experts during the heuristic inspection on their overall evaluation score. This evaluation, performed by seven usability experts, involved the identification and analysis of usability problems in the selected website. The assessment process was mainly based on the Sirius framework evaluation mechanism. The web considered as having high usability level, but they identified many usability problems for further improvement of the site. The most violated heuristic item was found to be “help” whereas the least violated heuristic item was “labelling” aspect.

PELATIHAN LITERASI DIGITAL PADA PEREMPUAN KELOMPOK BINAAN SEKOLAH IBU ARJOSARI MALANG Tutik Sulistyowati; Nur Hayatin; Gita Indah Marthasari
Jurnal Dedikasi Vol. 16 (2019): Mei
Publisher : Direktorat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/dedikasi.v16i1.10735

Evaluasi Heuristik Website berbasis Framework Sirius dengan Pengaturan Prioritas menggunakan Teknik Moscow Gita Indah Marthasari; Nur Hayatin
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7, No 2: April 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020701662

Kualitas merupakan faktor utama kesuksesan sebuah website. Salah satu karakteristik kualitas perangkat lunak menurut ISO 9126 adalah usabilitas. Pengukuran usabilitas sebuah website adalah hal yang penting mengingat sangat besarnya jumlah website saat ini. Salah satu metode yang dapat digunakan untuk mengevaluasi usabilitas website adalah framework Sirius. Sirius dapat menghasilkan nilai usabilitas global dan daftar elemen antarmuka sistem yang perlu diperbaiki. Namun, elemen-elemen ini belum diatur berdasarkan prioritas pengembang sistem dan hanya mempertimbangkan nilai peningkatan yaitu prosentasi perbaikan nilai usabilitas global jika elemen tersebut diperbaiki. Untuk itu dibutuhkan sebuah teknik untuk memprioritaskan elemen-elemen tersebut berdasarkan sudut pandang pengembang sistem sehingga sesuai dengan sumber daya yang dimiliki oleh pihak pengembang. Salah satu teknik yang dapat digunakan adalah Moscow. Moscow dapat mengelompokkan seluruh kebutuhan ke dalam 4 (empat) kelas berdasarkan tingkat prioritasnya. Penelitian ini melakukan modifikasi terhadap framework Sirius dengan menambahkan tahap perangkingan menggunakan teknik Moscow. Berdasarkan hasil pengujian, penambahan tahap pengaturan prioritas dengan Teknik Moscow memberikan urutan kriteria usability yang lebih baik dalam hal nilai bisnis, resiko, dan biaya pembangunan website. Setiap tim pengembang website yang dianalisis memberikan hasil pengaturan prioritas Moscow yang berbeda-beda. Bagi tim website Lective, kriteria usability paling penting adalah berkaitan dengan aspek labelling, sedangkan bagi pengembang website Seminar Indonesia, aspek paling penting adalah kelompok comprehensibility and ease of interaction. Adapun pengembang website Simkesmas lebih menekankan pada aspek control and feedback. AbstractQuality became the key element for website deployment. Based on the ISO 9126, one of the quality characteristics in software engineering is usability. The usability measurement on a website is an essential topic nowadays along with the incremental growth of it. One of the evaluation methods that can be used for analysing website usability is Sirius Framework. This method can produce global usability values and the list of a user interface element that should be modified. However, those elements have not been adjusted based on developer priority system which only considers the increased value of each element - the percentage of modified global usability value. Therefore, A technique called MoSCoW was introduced for prioritizing those elements from a developer point of views which corresponds to its available resource. MoSCoW can categorize all of the requirements into 4 distinct classes based on priority. This paper was performed for extending the Sirius Framework for implementing the ranking system by using MoSCoW. The experiment results showed that the MoSCoW method for priority adjustment process could produce better usability criteria on business, risk, and cost value during website development.

Content Classification based-on Latent Semantic Analysis and Support Vector Machine (LSA-SVM) Gita Indah Marthasari; Nur Hayatin; Maulidya Yuniarti
Jurnal Transformatika Vol 19, No 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.2745

The diversity of the content of a web page can have a negative impact if used by the wrong user. Almost a half of internet users are children. Therefore, it is important to classify web pages to find out which pages are worthy of being seen by children and that are not feasible. One method that can be used is the Support Vector Machine (SVM) algorithm. SVM is a binary classification whose working principle is to find the best hyperplane to separate the two classes. To obtain better classification accuracy, the SVM is combined with the Latent Semantic Analysis (LSA) algorithm. The data used in this study were taken from the DMOZ web data which has been classified into two categories. The data is then entered into the pre-processing stage for further feature extraction using LSA. The LSA algorithm is used to find out the semantic similarities of words and text contained in web pages. The results of feature extraction are then classified using SVM with RBF kernel. Based on the testing result, we obtain a classification accuracy of 64%.

SISTEM REKOMENDASI PENYEWAAN PERLENGKAPAN PESTA MENGGUNAKAN COLLABORATIVE FILTERING DAN PENGGALIAN ATURAN ASOSIASI Gita Indah Marthasari; Yufis Azhar; Dwi Kurnia Puspitaningrum
Jurnal Simantec Vol 5, No 1 (2015)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v5i1.1008

ABSTRAKE-commerce berbasis web merupakan salah satu media yang efektif dalam jual beli. Banyak usaha yang telah memanfaatkan fasilitas ini. Salah satunya adalah bidang jasa persewaan alat-alat pesta. Untuk memberikan layanan yang lebih baik, e-commerce dilengkapi dengan fitur lain antara lain sistem rekomendasi. Sistem ini memudahkan konsumen menentukan barang untuk dibeli dengan cara menampilkan produk yang terkait dengan salah satu produk lain yang dibeli atau dilihat konsumen. Salah satu mekanisme untuk membangun sistem ini adalah collaborative filtering. Cara kerja collaborative filtering adalah dengan membangun sebuah basis data yang menyimpan produk-produk yang disukai konsumen. Transaksi baru yang dibuat oleh seorang konsumen akan dicocokkan dengan basis data tersebut untuk mengetahui data historis mana yang paling sesuai dengan data baru tersebut. Data historis yang paling sesuai akan ditampilkan sebagai rekomendasi bagi konsumen yang melakukan transaksi tersebut.Salah satu teknik yang dapat digunakan adalah penggalian aturan asosiasi menggunakan Algoritma Apriori. Pada penelitian ini, dibuat sebuah website persewaan alat-alat pesta dengan menerapkan sistem rekomendasi. Sistem rekomendasi dibangun menggunakan aturan-aturan yang dihasilkan oleh Algoritma Apriori. Untuk dapat menampilkan barang rekomendasi digunakan nilai support 20, sedangkan nilai confidence digunakan untuk menentukan N-teratas barang untuk direkomendasikan.Kata kunci : sistem rekomendasi, collaborative filtering, algoritma apriori. ABSTRACTWeb-based e-commerce is an effective media for buying and selling. Many businesses have taken the advantages of this facility. One of them is the party tools rental services. To provide better service, e-commerce is equipped with other features such as a recommendation mechanism. Thismechanism allows consumers specify the goods to be purchased by displaying products that are related to another purchased product or customer visits. One mechanism for establishing this system is collaborative filtering. Collaborative filtering works by building a database that stores the products which are preferred by consumers. New transactions made by a consumer will be matched with the database to find out which data are related the most. The most appropriate historical data to be displayed as a recommendation for consumers who conduct such transactions. One technique that can be used is extracting association rules using Apriori Algorithm. In this study, a website of party tools rental service is created to implement the recommendation system. A recommendation system built using rules generated by Apriori Algorithm. To be able to display items used on the value of the support 20, while the confidence value is used to determine the N-top items to be recommended.Keywords: recommender system, collaborative filtering, apriori algorithm.

ANALISIS DATA PENDIDIKAN TINGGI MENGGUNAKAN PENDEKATAN DATA MINING Gita Indah Marthasari
Jurnal Simantec Vol 5, No 3 (2016)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v5i3.2386

ABSTRAKData mining untuk pendidikan menekankan pada pemanfaatan metode untuk menemukan pengetahuan dari data di lingkungan pendidikan. Bidang ini menggunakan mekanisme transformasi atau inovasi dari pendekatan yang diturunkan dari ilmu statistik, pembelajaran mesin, psikometrik, dan komputasi ilmiah. Penelitian ini mengusulkan sebuah analisis terhadap status keaktifan siswa menggunakan salah satu teknik data mining yaitu association rule mining (ARM). Teknik ARM bertujuan menemukan pola-pola yang merepresentasikan informasi bernilai tinggi bagi para pengambil keputusan di perguruan tinggi. Salah satu algoritma yang umum digunakan dalam ARM adalah Apriori. Algoritma Apriori digunakan untuk mencari aturan-aturan asosiasi yang menarik dari basis data dalam rangka mengekstraksi pengetahuan dari data profil dan data akademik siswa. Aturan-aturan yang ditemukan selanjutnya dianalisis sebagai bahan rekomendasi bagi para pengelola akademik untuk meningkatkan kualitas proses pengambilan keputusan. Selain itu, hasil analisis dapat menjadi acuan bagi arah kurikulum yang mampu memperbaiki kualitas pembelajaran siswa. Uji coba dilakukan dengan melakukan pengaturan terhadap parameter nilai minimal support dan minimal confidence. Berdasarkan hasil analisis diperoleh pengetahuan antara lain adanya hubungan kuat antara asal sekolah mahasiswa dan pekerjaan orang tua terhadap tingkat keaktifan. Selain itu, juga diperoleh pengetahuan tentang nilai minimal mahasiswa tiap semesternya untuk tetap aktif di semester selanjutnya.Kata kunci : Data mining untuk pendidikan, Association Rule Mining, Algoritma apriori, Status keaktifan siswa. ABSTRACT Educational data mining (EDM) concerns with developing methods for discovering knowledge from data that come from educational environments. EDM requires a transformation of existing or innovation of new approaches derived from statistics, machine learning, psychometrics, and scientific computing. In this paper, we propose an analysis of student activity status using one of data mining techniques that are association rule mining (ARM).ARM technique aims at discovering patterns that can provide valuable information for the decision maker in higher education.Apriori algorithm is one of many methods in ARM.We have used Apriori algorithm for finding interesting association rules from the transformed database which can be useful to extract knowledge of students’ profile and academic evaluation. The identified rules are analyzed to offer a helpful and constructive recommendation to the academic planners in higher institutions to enhance their decision-making process.We analyze the data by setting minimal support and minimal confidence value. Based on the experiment, we conclude that the student high school location and parent’s job have a strong correlation with student activity.Moreover, we also acquired a knowledge about student minimal grade point average in a semester to remain active in the next semester.Keywords: Educational data mining, Association rule mining, Apriori algorithm, Students activity status

Co-Authors Abu Hanifah Adam Novrisal Amelia Deastu Amelia Dwi Deastu Anastasia Lidya Maukar Andjani Chaerun Nisha Anggraini, Syadza Ani Tri Wahyuningsih Anik Vega Vitianingsih Arif Rahmadhani Belli Kafilla Gani Briansyah Setyo Wiyono Chita Nauly Harahap Christian Sri Kusuma Aditya Darfian Ardiansyah Diah Risqiwati Dwi Kurnia Puspitaningrum Eko Budi Cahyono Elsyah Ayuningrum Elza Norazizah Evi Dwi Wahyuni Fajarisma Asfiana Putri Fajrur Rahman Suprapto Fakhrul Islami Fathoni, Muhammad Asrar Fatimah Defina Setiti Alhamdani Febri Ayu Fitriani Ferin Reviantika Frengky Prastyo Gita Ismadianti Hanafi Prasetyoko Haris Diyaul Fata Harizal Iqmal Hasan Ilyas Nuryasin Ilyas Nuryasin Imam Halimi Irsandro, Ahmad Karima Maydina Yanti Kresna Arief Nugraha Lailatul Husniah Luqman Hakim M. Isnainur Hidyatullah Mahar Faiqurahman Mairissa Anggraini Maulidya Yuniarti Moh. Taufiq Hidayat Muhammad Alfian Ramadhani Muhammad Asrar Fathoni Muhammad Gufron Muhammad Ilham Muhammad Iqbal Muhammad Iqbal Ramadhan Muhammad Rizky Aviansyah Muhammad Ulfi Nabillah Annisa Rahmayanti Nina Mauliana Noor Fajriah Nirma Dwi Wulansari Nirma Noviasari, Vebrian Nuarini, Lia Nur Hayatin Nur Riyan Sahara Pendi, Wendi Rellanti Diana Kristy Risdianto Risdianto Rizky Irwan Saputra Roni Hadi Wijaya S, Vinna Rahmayanti Silcillya Ayu Astiti Syadza Anggraini Syadza Anggraini Syaifudin Zuhri Tsabitah Ayu Rahmawati Tutik Sulistyowati Vebrian Noviasari Wahyu Andhyka Kusuma Waliyyullah Mufid Wicaksono, Galih Wasis Wildan Suharso Wiyono, Briansyah Setio Yudi Ananta Prasetya Yufis Azhar Zakiyah Mahfudho Zamah Sari Zildan Rahmatullah

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