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Analisis Simulasi Goodness Of Fit (GOF) pada Uji Model Penerimaan E-Learning Uswatun Hasanah; Ismarmiaty Ismarmiaty; Adam Bachtiar
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2017
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk menguji dan  menganalisis kecocokan model secara keseluruhan (goodness of fit) pada penerimaan e-learning. Hasil pengujian dan analisis model ini akan digunakan untuk mengevaluasi penerimaan e-learning yang telah diterapkan oleh para dosen di STMIK Bumigora Mataram. Penggunaan e-learning di perguruan tinggi dimaksudkan untuk mendukung kelancaram kegiatan proses pembelajaran. Namun pada kenyataannya di lapangan, penggunaan e-learning di perguruan tinggi tersebut belum maksimal jika dilihat dari frekuensi pengguna yang sangat kecil. Hal ini bisa ditinjau dari besarnya perbandingan pengguna dengan jumlah dosen dan mahasiswa secara keseluruhan. Model penerimaan e-learning dibentuk berdasarkan Technology Acceptance Model (TAM) dan dianalisis menggunakan Structural Equation Modelling (SEM) yang dibantu dengan perangkat lunak AMOS diperoleh Goodness Of Fit (GOF) artinya model dapat diterima melalui pengujian model secara struktural, analisis faktor konfirmatori (CFA) dari indikator variabel eksogen dan endogen serta analisis model secara keseluruhan. Selanjutnya, model ini dapat digunakan untuk menemukan evaluasi penerimaan e-learning sebagai sistem perkuliahan di STMIK Bumigora Mataram.
IMPLEMENTASI ALGORITMA FREQUENT PATTERN-GROWTH TERHADAP POLA MAHASISWA LULUSAN DENGAN RAPIDMINER Ria Rismayati; Ismarmiaty Ismarmiaty
Jurnal Informatika dan Rekayasa Elektronik Vol. 4 No. 2 (2021): JIRE NOVEMBER 2021
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v4i2.384

Abstract

This research aims to analyze the patterns formed from interconnected items using existing data mining techniques related to the graduation data of students of the S1 Informatics Engineering study program at STMIK Bumigora Mataram. The Undergraduate Informatics Engineering Study Program is one of the study programs at the Bumigora College of Management and Informatics (STMIK) which was founded on November 23, 1993. One of the factors that is considered influencing graduation is the preparation of a thesis for final year students. The number of graduates produced is inversely proportional to the use of graduate data for institutional advancement. This shows that the graduate data has not been maximally used which is used as material or input, especially for the study program to develop a thesis implementation management system to make it more effective and efficient. This study uses the association rule with the calculation of the FP-Growth Algorithm. FP-Growth is part of the association technique in data mining, where an alternative algorithm can be used to determine the data set that appears most frequently in a data set. The steps taken were (a) data collection, (b) selecting data, (c) applying the FP-Growth method, (d) implementing the software and (e) testing the results. From the test results obtained the output of 24 rules, which are then taken 8 strong association rules that have a high level of trust and are supported by a percentage of the overall data with a value of lift ratio> 1. The conclusion is that the students graduated with Mr. RA has a good thesis score between the 70-80 range and comes from the competence of Computer Networks with a 100% confidence level and is supported by 14.4% of the overall data, in line with graduate students with Mr. BK with a satisfactory thesis score between the range 80-90 which comes from Multimedia competence with a confidence level of 94.1% and is supported by 12.1% of the overall data with an infinite lift ratio value of 2.4
Analisis Sentimen dan Pemodelan Topik Pariwisata Lombok Menggunakan Algoritma Naive Bayes dan Latent Dirichlet Allocation Ni Luh Putu Merawati Putu; Ahmad Zuli Amrullah; Ismarmiaty
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (379.611 KB) | DOI: 10.29207/resti.v5i1.2587

Abstract

Lombok Island is one of the favorite tourist destinations. Various topics and comments about Lombok tourism experience through social media accounts are difficult to manually identify public sentiments and topics. The opinion expressed by tourists through social media is interesting for further research. This study aims to classify tourists' opinions into two classes, positive and negative, and topics modelling by using the Naive Bayes method and modeling the topic by using Latent Dirichlet Allocation (LDA). The stages of this research include data collection, data cleaning, data transformation, data classification. The results performance testing of the classification model using Naive Bayes method is shown with an accuracy value of 92%, precision of 100%, recall of 84% and specificity of 100%. The results of modeling topics using LDA in each positive and negative class from the coherence value shows the highest value for the positive class was obtained on the 8th topic with a value of 0.613 and for the negative class on the 12th topic with a value of 0.528. The use of the Naive Bayes and LDA algorithms is considered effective for analyzing the sentiment and topic modelling for Lombok tourism.
Penerapan Computational Thinking pada Pelajaran Matematika di Madratsah Ibtidaiyah Nurul Islam Sekarbela Mataram Apriani Apriani; Ismarmiaty Ismarmiaty; Dyah Susilowati; Kartarina Kartarina; Wiya Suktiningsih
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 1 No 2 (2021): ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1183.963 KB) | DOI: 10.30812/adma.v1i2.1017

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This service activity aims to contribute knowledge to teachers to be able to understand and implement computational thinking in the subjects they are taught. The lack of trained personnel and the lack of understanding in implementing computational thinking gives the Bebras Bureau the opportunity to contribute. This is in line with Mendikbud's desire to implement computational thinking in the children's education curriculum as a provision for more innovative learning to answer the needs of the industrial era 4.0. Computational thinking is the process of thinking in formulating a problem and its solution so that the solution can be represented in a form that can be executed by an information-processing agent. The implementation of the service was carried out on the Mathematics subject teacher at Nurul Islam Mataram Elementary School. The implementation stages consist of planning, preparation, socialization, training, and evaluation. The results of the evaluation showed that most of the teacher participants agreed to apply the results of the training to students and most participants agreed to join the follow-up programs from Bebras. It is hoped that this activity can run continuously and be supported positively by the parties involved.
Sehat Berinternet untuk Anak Sekolah Selama Masa Pandemi di SD IT Ulul Albab Ria Rismayati; Ismarmiaty Ismarmiaty
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 2 No 1 (2021): Juli 2021
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (932.684 KB) | DOI: 10.30812/adma.v2i1.1197

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The impact of the Covid 19 pandemi, which began in 2020, has changed almost all aspects of life, especially teaching and learning activities. Teaching and learning activities which are generally carried out face-to-face, during this pandemi, were implemented online or online using the internet media. The use of the internet among ustadz, ustadzah and students of SD IT Ulul Albab is not an obstacle, especially as children in this era grow up with the internet which has become an important part of the surrounding environment and the internet is easily accessed at home, school and other public facilities. From every facility obtained from the internet, of course, it produces 2 sides that are positive and negatif, and to reduce the negatif impact of activities that involve the internet, there is a need for assistance, direction and socialization of the internet in a healthy and safe manner. In the service that was carried out at SD IT Ulul Alabini, it was given assistance and socialization to ustadz and ustadzah in representing healthy internet access which would then be passed on to their students. From this service, an evaluation was also carried out by distributing questionnaires related to the results of the socialization carried out in conveying the material, that the participants of this service gained added value to utilize the internet media in a healthy manner as a learning tool for 89% of the participants who attended.
Pendampingan Proses Pembuatan Soal Berbasis Computational Thinking kepada Guru pada Guru-Guru Tingkat SD dan SMP Kecamatan Sakra, Kabupaten Lombok Timur Ni Ketut Sriwinarti; Apriani Apriani; Diah Supatmawati; Kartarina Kartarina; Ismarmiaty Ismarmiaty
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 2 No 2 (2022)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v2i2.1568

Abstract

Thinking about computing or Computational Thinking (CT) is one of the problem solving techniques that is very important today to prepare the next generation to be competitive in this digital economy era. This skill teaches students how to think the way scientists think, to solve real-world problems. In training or familiarizing children with CT, this can be done by including or adding CT to the learning strategy. The intended strategy can be related to the packaging of the material, the learning media used, or an interesting learning model that can familiarize children with CT. The learning media used are expected to help children understand the subject matter. For early childhood, learning media has a vital role in learning. This is because at that age children are still at the stage of learning while playing. On August 6, 2019, Bumigora University signed a charter of cooperation with the coordination of the national committee (National Board Organization (NBO) bebras Indonesia), where for the next 5 (five) years Bumigora University will become a partner in realizing PANDAI students . PANDAI, is the name chosen as the movement to socialize CT, which stands for Pengjar Digital Era Indonesia. The PANDAI Movement training in collaboration with Bumigora University is also the first teacher training to be held in the entire West Nusa Tenggara region, involving approximately 400 elementary and junior high school teachers. Service activities related to Computational Thinking have been carried out. The results of the implementation have been evaluated with the results that most of the teacher participants agreed to apply the results of the training related to Computational Thinking to students and also most of the participants agreed to join the follow-up programs from Bebras. The implementation stage for students is still unable to carry out the service team due to the current pandemic situation, but with the continuation of the activities carried out by the UBG bureau with NBO Bebras. It is hoped that this activity can run continuously and be supported positively by the parties involved.
Lexicon Based Sentiment Analysis pada Trending Topic di Nusa Tenggara Barat Ismarmiaty; Maria Nuzurana Asti; Ahmad Ashril Rizal
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 3 No 2 (2022): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : E-Jurnal Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/j-icom.v3i2.6136

Abstract

This study aims to find trending topics and conduct sentiment analysis on trending topics related to the province of West Nusa Tenggara. This analysis uses tweet data from January 1, 2019 to December 31, 2020. The method used is Lexicon Based with the python programming language. The research stages consist of crawling the dataset, preprocessing, finding trending topics, lexicon based sentiment analysis & confusion matrix test and visualization. The conclusion from the analysis related to trending topics is that the top ten trending topics that emerged include: (1) COVID-19, (2) Wistan's brother, (3) MotoGP, (4) Rimpu Culture, (5) Baturotok Village fire, ( 6) The throwing of the factory by four housewives, (7) Rocky Gerung, (8) #onehealthKIPM, (9) after the NTB earthquake, and (10) the arrival of Sandiaga Uno to Bima. Sentiment analysis results show that several topics tend to lead to positive sentiment, including: 2nd, 3rd, 4th, 5th, 8th topics, 9th and 10th topics. While the 1st topic is related to COVID-19, the 6th and 7th tend to lead to negative sentiment. The test accuracy value is above 80% and the average score for all topics is 100% on accuracy, 100% on precision and 100% on recall.
Analisis Penerapan Metode MOORA untuk Memprediksi Tren Penjualan Barang di CV. Light Auto Gayatri Ramadhani; Kartarina Agustin; Ismarmiaty Ismarmiaty; Ni Ketut Sriwinarti
Riset, Ekonomi, Akuntansi dan Perpajakan (Rekan) Vol 3 No 2 (2022): Riset, Ekonomi, Akuntansi dan Perpajakan(Rekan )
Publisher : Program Study Akuntansi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/rekan.v3i2.2388

Abstract

Teknologi informasi pada dunia bisnis dimanfaatkan sebagai strategi untuk meraup keuntungan dan memperkecil resiko kerugian. Semakin berkembangnya teknologi informasi semakin bertambah juga kemampuan komputer untuk membantu dalam memberikan solusi dari permasalahan yang dihadapi. Salah satunya adalah sistem pendukung keputusan berbasis komputer. Prediksi merupakan hasil dari aktivitas memprediksi, meramal ataupun memperkirakan nilai masa mendatang misalnya memprediksi stok benda satu tahun ke depan. Barang ialah produk yang berwujud fisik, sehingga dapat dilihat, diraba atau dijamah, dipegang, disimpan, dipindahkan serta diproses isinya. Tujuan penelitian ini adalah hasil analisa dari penelitian ini digunakan untuk membantu admin dalam memprediksi tren penjualan barang di CV. Light Auto. Metode yang diterapkan pada penelitian ini model waterfall meliputi analisis kebutuhan, perancangan, implementasi dan pengujian sistem. Hasil perhitungan pengujian kepuasan pengguna memiliki skor 94 menggunakan metode MOORA yang menyatakan pengguna puas menggunakan aplikasi
Ensemble Implementation for Predicting Student Graduation with Classification Algorithm Ria Rismayati; Ismarmiaty Ismarmiaty; Syahroni Hidayat
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 1 No 1 (2022): March 2022
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (420.941 KB) | DOI: 10.30812/ijecsa.v1i1.1805

Abstract

Graduating on time at the higher education level is one of the main targets of every student and university institution. Many factors can affect a student's length of study, the different character of each student is also an internal factor that affects their study period. These characters are used in this study to classify data groups of students who graduated on time or not. Classification was chosen because it is able to find a model or pattern that can describe and distinguish classes in a dataset. This research method uses the esemble learning method which aims to see student graduation predictions using a dataset from Kaggle, the data used is a IPK dataset collected from a university in Indonesia which consists of 1687 records and 5 attributes where this dataset is not balanced. The intended target is whether the student is predicted to graduate on time or not. The method proposed in this study is Ensemble Learning Different Contribution Sampling (DCS) and the algorithms used include Logistic Regression, Decision Tree Classifier, Gaussian, Random Forest Classifier, Ada Bost Classifier, Support Vector Coefficient, KNeighbors Classifier and MLP Classifier. From each classification algorithm used, the test value and accuracy are calculated which are then compared between the algorithms. Based on the results of research that has been carried out, it is concluded that the best accuracy results are owned by the MLPClassifier algorithm with the ability to predict student graduation on time of 91.87%. The classification model provided by the DCS-LCA used does not give better results than the basic classifier of its constituent, namely the MLPClassifier algorithm of 91.87%, SVC of 91.64%, Logistic Regression of 91.46%, AdaBost Classifier of 90.87%, Random Forest Classifier of 90.45% , and KNN of 89.80%.
Penguatan kemampuan computational thinking pada pemberdayaan guru dan siswa Sekolah Dasar di Pulau Lombok Ismarmiaty; Kartarina Agustin; Miftahul Madani; Ni Ketut Sriwinarti; Zainuddin; Dyah Supatmiwati
Transformasi: Jurnal Pengabdian Masyarakat Vol. 18 No. 2 (2022): Transformasi Desember
Publisher : LP2M Universitas Islam Negeri Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20414/transformasi.v18i2.5034

Abstract

[Bahasa]: Kepala Pusat Kurikulum dan Pembelajaran Kementerian Pendidikan dan Kebuda-yaan menyatakan bahwa computational thinking merupakan salah satu kompetensi baru yang akan masuk dalam sistem pembelajaran anak Indonesia. Salah satu strategi efektif untuk menerapkan computational thinking di sekolah adalah dengan memperkenalkan dan memberi pelatihan kepada guru tentang implementasi computational thinking di mata pelajaran yang mereka ajarkan. Biro Bebras Universitas Bumigora berusaha untuk mengimplementasikan computational thinking di wilayah Nusa Tenggara Barat melalui kegiatan pemberdayaan guru dan siswa dalam kemampuan computational thinking. Metode yang digunakan dalam program pengabdian kepada masyarakat ini adalah Asset Based Community Development. Kegiatan pengabdian ini terdiri beberapa tahapan antara lain adalah persiapan kegiatan, sosialisasi pengenalan computational thinking, pelatihan computational thinking, mini challenge & Lomba Bebras Nasional dan Evaluasi. Kesimpulan dari pengabdian ini adalah bahwa persentase pencapaian jumlah sekolah, peserta guru maupun peserta siswa belum memenuhi target namun berada pada rerata 78%. Selain itu, hasil kuisioner evaluasi menyatakan bahwa kepuasan partisipan terhadap kegiatan pemberdayaan kemampuan computational thinking dianggap sesuai dengan kebutuhan pekerjaan mengajar guru, sesuai dengan kebutuhan pelatihan dan memberikan manfaat secara pengetahuan dan keterampilan di bidang pekerjaan. Salah satu faktor eksternal yang dihadapi oleh Biro Bebras Universitas Bumigora adalah kesiapan perangkat teknologi dan kemampuan literasi digital. Saran perbaikan terhadap kegiatan adalah terkait dengan perbaikan strategi pemberdayaan dengan menyusun perencanaan matang untuk dapat melakukan kegiatan yang berdampak lebih luas secara geografis dan juga pengembangan soal yang lebih bervariasi pada mata pelajaran sekolah dasar. Kata Kunci: Bebras, Biro Bebras Universitas Bumigora, Computational Thinking [English]: The Center for Curriculum and Learning of the Ministry of Education and Culture stated that computational thinking is the new competency that will be implemented in the Indonesian education system. An effective way to implement computational thinking in schools is by introducing and training the teachers on implementing computational thinking in the subjects. The Bebras Bureau of Bumigora University sought to implement computational thinking in education in the West Nusa Tenggara region by empowering teachers and students in computational thinking skills. The method used in this community service program method was Asset Based Community Development (ABCD). The stages of this program were activity preparation, socialization of computational thinking introduction, computational thinking training, mini challenge & National Bebras Competition and Evaluation. The result shows that the achievement percentage for the number of schools, teacher participants and student participants has yet to meet the target but is at an average of 78%. In addition, the results of the teacher evaluation questionnaire stated that the program was considered by the needs of teaching jobs and training needs and provided benefits in terms of knowledge and skills in the field of work. One of the external factors faced by the Bebras Bureau at Bumigora University is the readiness for technological devices and digital literacy capabilities. The recommendation for improvement of this program is an effort to improve the empowerment strategy through careful planning so that it will have a wider impact. In addition, it is necessary to develop various questions in elementary school subjects. Keywords: Bebras, Bumigora University Bureau, Computational Thinking