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All Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Bumigora Information Technology (BITe) Teknomatika (Jurnal Teknologi dan Informatika) Mitra Mahajana: Jurnal Pengabdian Masyarakat ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Jurnal Ilmiah Pengabdian dan Inovasi Seminar Nasional Aplikasi Iptek (SINAPTEK) Jurnal Edukasi dan Pengabdian kepada Masyarakat (JEPKM) Jurnal Karya untuk Masyarakat (JKuM)
Ayu Dasriani, Ni Gusti
Faculty Of Engineering And Design, Universitas Bumigora
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Nursing Public Health Social Sciences Other

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Feature Extraction in Eye Images Using Convolutional Neural Network to Determine Cataract Disease Fitra Rizki Ramdhani; Khasnur Hidjah; Muhammad Zulfikri; Hairani Hairani; Mayadi Mayadi; Ni Gusti ayu Dasriani; Juvinal Ximenes Guterres
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 4 No. 2 (2025): September 2025
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v4i2.5064

Abstract

The eye is one of the vital human senses and serves as the main organ for vision. One of the visual impairments that requires special attention is blindness, and cataracts are a major cause of it. A cataract is a condition in which the eye’s lens becomes cloudy due to changes in the lens fibers or materials inside the capsule. This cloudiness blocks light from entering the eye and reaching the retina, significantly interfering with vision. Early detection of cataracts is essential to prevent blindness. An efficient image-based classification model is needed for cataract detection. This study aims to test the Convolutional Neural Network (CNN) model for early cataract detection by exploring the use of several optimization algorithms: Adaptive Moment Estimation (Adam), Root Mean Square Propagation (RMSprop), Adaptive Gradient Algorithm (AdaGrad), and Stochastic Gradient Descent (SGD). The research method follows an experimental approach, where eye image datasets are trained using the same CNN architecture but with different parameter configurations. The results show that the Adam optimizer, with a data split of 70% for training, 15% for validation, and 15% for testing over 50 epochs, produced the best results, achieving accuracies of 94%, 93%, and 93%, respectively. Other optimizers performed reasonably well but could not match Adam's stability and accuracy. The implication of this research is that the choice of optimizer and hyperparameter configuration plays a crucial role in improving the performance of image-based cataract detection models.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2005.51 KB) | DOI: 10.59934/jaiea.v1i1.45

Abstract

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.
Pelatihan Dasar-Dasar Kepemimpinan Organisasi Anggriani, Rini; Cahyadi, Irwan; Khairunnisa; Dasriani, Ni Gusti Ayu; Hijjah, Khasnur; Wardhana, Helna
Jurnal Ilmiah Pengabdian dan Inovasi Vol. 3 No. 2 (2024): Jurnal Ilmiah Pengabdian dan Inovasi (Desember)
Publisher : Insan Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57248/jilpi.v3i2.482

Abstract

The basics of organizational leadership training aim to equip participants with the knowledge, skills and attitudes necessary to become effective leaders in an organizational context. The activity method uses a lecture approach, interactive discussion sessions, and training according to existing conditions. In this training, participants are taught the basic principles of leadership including effective communication, decision making, and understanding various leadership styles in organizations. Indicators of success are shown by the high enthusiasm of participants in participating in activities which is also marked by increased knowledge and skills of participants regarding the basics of leadership. This training activity has an impact on improving individual and team performance, developing organizational culture and increasing overall organizational competitiveness. With the development of the right skills, leaders can lead an organization toward achieving greater goals and create a work environment that grows positively, productively, innovatively, and collaboratively.
E-Alert Application in Facing Earthquake Disaster Apriani Apriani; Sandi Justitia Putra; Ismarmiaty Ismarmiaty; Ni Gusti Ayu Dasriani
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 19 No. 2 (2020)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v19i2.670

Abstract

Disaster is a phenomenon that has a destructive effect and arises with or without predictions that always accompany human life. This damaging impact can be in the form of loss of life and / or property loss so that it disrupts the natural and social order. Lombok is one of the islands in the group of islands in West Nusa Tenggara. The island of Lombok is flanked by two large faults, the Flores Back Arc Thrust (FBAT) which extends north of Nusa Tenggara to Bali and Megathrust on the south of Lombok. Seeing from the great potential of earthquake disasters that can occur at any time on the island of Lombok, it is necessary to prepare disaster mitigation well in order to minimize the impact of earthquake disaster risk. From the problems outlined, the researchers plan to create a mobile-based earthquake e-standby application. This study aims to create a mobile-based earthquake e-alert application that can be used to view the latest earthquake information, information for determining the nearest evacuation location and educational media related to earthquake disaster awareness. The stages of the research use the prototype development method with stages, namely the study of literature, collection of needs, data collection, needs analysis, design, prototype implementation, prototype evaluation, implementation and testing and conclusions. The conclusion of this research is the construction of a mobile-based earthquake e-alert application. This application is useful for improving, understanding and public awareness of the risk of earthquake disasters and as an educational media to create disaster resilient communities
Pengembangan Sistem Aplikasi Cerdas Memprediksi Penjualan Mebel Berbasis website Ni Gusti Ayu Dasriani; Anthony Anggrawan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 21 No. 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v21i1.1276

Abstract

Industri mebel di Indonesia merupakan usaha yang memiliki laju perkembangan sangat pesat. Konsumen memilih menggunakan mebel hasil dari industri karena mebel produksi industri memiliki inovasi disain yang indah. Mebel berperan juga sebagai sumber pemasukan keuangan negara di Indonesia terutama penjualan kepada konsumen negara lain. Karenan terjadi kompetisi yang begitu ketat antar industri mebel, keadaan ini berimplikasi produsen mebel berusaha secara ketat dalam menciptakan produksi yang bermutu dan memenuhi selera konsumen. Permasalahannya adalah produsen masih mengelola data atau mendapatkan informasi hasil produksi dalam system manual. Karenanya tujuan dari penelitian ini adalah membangun sistem aplikasi komputer cerdas website untuk memprediksi penjualan mebel. Perancangan dan pembuatan system ini menggunakan metodologi Waterfall. Metode yang digunakan untuk mengklasifikasi data penjualan barang mebel dengan metode K-Nearest Neightbor (KNN). KNN merupakan metode untuk mengektraksi data mining yang bisa berguna dalam prediksi penjualan. Hasil yang dicapai yaitu dihasilkannya system prediksi penjualan barang dan juga laporan prediksi penjualan barang dalam bentuk lembar kerja (Spreadsheet) sehingga membantu pimpinan perushaan dalam usahanya. Kesimpulan dari penelitian yang dilakukan menggunakan metode KNN cocok digunakan untuk mengklasifikasi data penjualan barang mebel. Hal ini tersebut dibuktikan dengan tingkat akurasi yang mencapai 90% pada proses pengujian menggunakan confussion matrik.
Klasterisasi Lokasi Promosi PMB Dengan Fuzzy C-means Masa Pandemi Covid 19 Ni Gusti Ayu Dasriani; Mayadi Mayadi; Anthony Anggrawan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 21 No. 2 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v21i2.1832

Abstract

Pandemi Covid-19 saat ini merupakan bencana besar bagi global, covid 19 merupakan penyakit yang sangat merugikan dan memiliki dampak negative bagi global, resiko yang diakibatkan oleh Pandemi Covid-19 tidak hanya berpengaruh pada aspek kesehatan, tetapi juga berpengaruh pada berbagai lini kehidupan seperti dampak PHK dan merumahkan pekerja. Bukan hanya berdampak sektor ekonomi, transportasi dan pertanian, Pandemi Covid-19 ini sangat merugikan bagi dunia pendidikan. Selama pandemi covid 19 penurunan pendaftaran sangat berdampak terhadap dunia Pendidikan sehingga diperlukan strategi untuk bisa memancing minat calon mahasiswa untuk mendaftar. Berdasarkan permasalahan tersebut peneliti mencoba melakukan penelitian terkait strategi promosi di tengah pandemi covid 19 untuk menarik minat calon mahasiswa untuk mendaftar ke universitas. Metode yang digunakan menggunakan metode Fuzzy C-means dengan proses pembobotan menggunakan RFM (Recency, Frequency, Monetary). Dari hasil evaluasi dengan data pemetaan didapatkan peningkatan pendaftar dimana untuk tahun 2020 pendaftar sebanyak 365 dan untuk tahun 2021 mengalami peningkatan sebanyak 1169 pendaftar.
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

Abstract

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.
Intelligent System for Internet of Things-Based Building Fire Safety with Naive Bayes Algorithm Ni Gusti Ayu Dasriani; Sirojul Hadi; Moch Syahrir
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i1.3581

Abstract

Population growth is increasing every year. Population growth causes an increase in population density in a country. The largest population density is in urban areas. Fires in a city with a high population density will potentially cause greater damage. Material and non-material losses due to fire can be caused by not functioning maximally early warning systems, especially fire detection. In addition, other factors, such as system errors in detecting fires, can potentially cause fires. This research aims to build an intelligent system that can minimize building fire detection errors to reduce user material losses. The intelligent system can classify fire potential into four classifications, namely ”very dangerous,” ”dangerous,” ”alert,” and ”safe.” The method used in this research is Research and Development (R&D) with artificial intelligence using the Na¨ıve Bayes method, which has been integrated with the Internet of Things (IoT). This research shows that the Na¨ıve Bayes algorithm can be used to classify fire potential, proven by the overall system testing accuracy of 93.33% with an error of 6.77%.
Pengenalan Pemikiran Computational Thinking untuk Guru MI dan MTs Pesantren Nurul Islam Sekarbela Wiya Suktiningsih; Diah Supatmiwati; Ni Gusti Ayu Dasriani; Apriani; Ismarmiaty
Jurnal Karya untuk Masyarakat (JKuM) Vol 2 No 1: JANUARI 2021
Publisher : Universitas Tarakanita

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36914/m8y03m85

Abstract

Computational Thinking (CT) adalah konsep berpikir secara komputasi dalam menyelesaikan suatu masalah. Saat ini para guru di MI dan MTs Pesantren Nurul Islam belum menerapkan CT dalam proses pembelajarannya. Metode pembelajaran dalam CT mencakup 4 pilar utama, yaitu: Dekomposisi, Abstraksi, Algoritma dan Pengenalan Pola. CT melatih siswa untuk berpikir secara komputasi sambil memecahkan masalah di semua disiplin ilmu. Berpikir Komputasi adalah suatu konsep proses berpikir yang melibatkan suatu perumusan masalah dalam menemukan solusinya, seperti cara berpikir suatu system computer atau mesin yang berkerja secara efektif. Metode pembelajaran CT membentuk siswa menjadi kreatif dan inovatif, serta mampu berkomunikasi dan berkolaborasi. Saat ini CT tidak hanya dapat diterapkan di bidang teknik informatika, akan tetapi dapat diintegrasikan dengan bidang keilmuan lain seperti Bahasa Indonesia, Bahasa Inggris, Matematika dan IPA. Program kegiatan pengabdian masyarakat ini memperkenalkan konsep CT untuk guru MI dan MTs di Pondok Pesantren Nurul Islam - Pagesangan Mataram. Dengan harapan guru dapat memasukkan CT ke dalam kurikulum pembelajaran yang diajarkan, supaya siswa mampu menyelesaikan masalah menggunakan konsep berpikir computational thinking, dan terkonsep secara alamiah menggunakan CT, hingga pemasalahan dapat diselesaikan secara efektif dan optimal.
Co-Authors . Apriani Anggarawan, Anthony Anggriani, Rini Anthony Anggrawan Apriani Apriani Astri , Renita Bintang Rizki Maulana Cahyadi, Irwan Dadang Priyanto Dafa Awanta Deny Jollyta Dewi, Puspita Diah Supatmiwati Dwi Oktarina Dyah Susilowati Erwin Suhendra Felicia Natalie Fedrich Fitra Rizki Ramdhani Gusrianty Hairani Hairani Helna Wardhana Herawati, Baiq Candra Hijjah, Khasnur I Gde Dharos Santana Dharma I Made Yadi Dharma Ibrahim, Isra Dewi Kuntary Irwan Cahyadi Ismarmiaty Ismarmiaty Jean Suciasti Gunawan Juvinal Ximenes Guterres Kadim, Lina Arliana Nur Kartarina, Kartarina Khairan marzuki Khairunnisa Khasnur Hidjah Mayadi Mayadi Mayadi Mayadi Muhammad Zulfikri Nurul Hidayah Pariandi, Lalu Ahmad Gede Raden Bagus Faizal Irani Sidharta Raden Bagus Faizal Irany Sidharta Raden Bagus Faizal Irany Sidharta Rini Anggriani Rini Anggriani Riyana Rizki Yuliatin Sandi Justitia Putra Sandi Justitia Putra Sirojul Hadi Siti Soraya Syahrir, Moch. Triwijoyo, Bambang Krismono Wiya Suktiningsih