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All Journal WIDYA TEKNIKA Jurnal Teknologi dan Manajemen Informatika DINAMIKA DOTCOM TEKNOLOGI INFORMASI Prosiding SNATIKA Vol 01 (2011) International conference on Information Technology and Business (ICITB) SMATIKA JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI ILKOM Jurnal Ilmiah Conference on Innovation and Application of Science and Technology (CIASTECH) Journal on Education Jurnal Masyarakat Merdeka (JMM) Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS Jurnal Pendidikan dan Keluarga Buana Information Technology and Computer Sciences (BIT and CS) JATI (Jurnal Mahasiswa Teknik Informatika) Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Community Development Journal: Jurnal Pengabdian Masyarakat Among : Jurnal Pengabdian Masyarakat International Journal of Business, Law, and Education Jurnal Simki Pedagogia JUSTIN (Jurnal Sistem dan Teknologi Informasi) Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) ETAM: Jurnal Pengabdian kepada Masyarakat Prosidia Widya Saintek Jurnal Pengabdian Masyarakat dan Riset Pendidikan El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam Journal of Ekonomics, Finance, and Management Studies JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
MARIFANI FITRI ARISA
Universitas Negeri Yogyakarta
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Expression Detection of Children with Special Needs Using Yolov4-Tiny Sidi, Husri; Rahman, Aviv Yuniar; Marisa, Fitri
ILKOM Jurnal Ilmiah Vol 16, No 3 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i3.1609.221-227

Abstract

This research addresses the challenge of detecting emotional expressions in children with special needs, who often rely on nonverbal communication due to difficulties in verbal expression. Traditional emotion detection methods struggle to accurately recognize subtle emotions in these children, which can lead to communication barriers in educational and therapeutic settings. This study proposes the use of the Yolov4-Tiny model, a lightweight and efficient object detection architecture, to accurately detect four key facial expressions: Angry, Happy, Smile, and Afraid. The dataset consists of 1500 images, evenly distributed across the four expression classes, captured under controlled conditions. The model was evaluated using various metrics, including Confidence, Precision, Recall, F1-Score, and Mean Average Precision (mAP), across different training-to-testing data splits. The results demonstrated that the Yolov4-Tiny model achieved high accuracy, with a perfect mAP of 100% for balanced and slightly imbalanced splits, and a minimum mAP of 93.1% for more imbalanced splits. This high level of performance highlights the model's robustness and potential for application in educational and therapeutic environments, where understanding emotional expressions is critical for providing tailored support to children with special needs. The proposed system offers a significant improvement over traditional methods, enhancing communication and emotional support for this vulnerable population.
Klasifikasi Jenis Kanker Prostat Melalui Citra MRI Menggunakan Pengolahan Citra Digital Putra, Rangga Pahlevi; Marisa, Fitri
Jurnal Teknologi dan Manajemen Informatika Vol. 10 No. 2 (2024): Desember 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v10i2.12666

Abstract

The prostate gland is one of the parts of the male reproductive system. The prostate gland is one of the organs that is not infrequently affected by cancer. Prostate cancer is one of the top diseases that often appears as one of the deadly diseases in the world. Including in Asia, the incidence of prostate cancer patients averages 7.21 per 100,000 men each year. To identify the symptoms of cancer, early detection in men can usually be done through a rectal examination. However, there is another method that utilizes imaging technology, specifically MRI images for prostate cancer, to determine the size of the cancer. By applying image processing methods such as Watershed segmentation and the Multiclass Support Vector Machine method, it is possible to classify the type of prostate cancer through MRI images. From the research conducted, it can be explained that the segmentation results of MRI images for prostate cancer using the Watershed method can show the detected cancer area spots. Meanwhile, the use of the MultiSVM method for classification shows an accuracy result of 90.166% for the polynomial kernel type.
KLASIFIKASI KUALITAS GURU PAUD/TK MENGGUNAKAN METODE DECISION TREE Ulfah Rahamawati, Ulya; Marisa, Fitri; Nurdiyansyah, Firman
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 6 (2024): JATI Vol. 8 No. 6
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i6.11524

Abstract

Penelitian ini bertujuan untuk mengklasifikasi kualitas guru PAUD di Kecamatan Hanau menggunakan metode Decision Tree dengan algoritma C4.5. Kualitas guru PAUD merupakan faktor penting yang memengaruhi perkembangan anak usia dini, sehingga perlu dilakukan evaluasi dan peningkatan kualitas pengajar. Data yang digunakan dalam penelitian ini diperoleh melalui kuesioner yang diisi oleh para guru PAUD di wilayah penelitian. Setelah dilakukan proses preprocessing data, model Decision Tree dibangun untuk mengklasifikasi kualitas guru berdasarkan variabel pendidikan terakhir dan lama pengalaman mengajar. Hasil penelitian menunjukkan bahwa algoritma C4.5 memberikan performa yang baik, dengan akurasi sebesar 83%. Analisis pohon keputusan mengungkapkan bahwa faktor pendidikan terakhir dan lama mengajar merupakan determinan utama yang memengaruhi kualitas kinerja guru PAUD di Kecamatan Hanau. Penelitian ini memberikan wawasan yang dapat digunakan oleh para pengambil kebijakan dalam menyusun program peningkatan kualitas pengajaran di tingkat PAUD, khususnya di wilayah pedesaan seperti Kecamatan Hanau. Selain itu, rekomendasi untuk penelitian selanjutnya adalah menggunakan variasi data yang lebih luas serta mempertimbangkan algoritma lain untuk mencapai akurasi model yang lebih tinggi.
PERBANDINGAN KINERJA METODE KLASIFIKASI CITRA SALIVA FERNING UNTUK DETEKSI MASA SUBUR BERBASIS MACHINE LEARNING Rivaldiknas Gampar, Philipus; Marisa, Fitri; Istiadi, Istiadi
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 6 (2024): JATI Vol. 8 No. 6
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i6.11649

Abstract

Masa subur (ovulasi) pada wanita dewasa adalah periode dalam siklus menstruasi ketika sel telur siap untuk dibuahi. Umumnya terjadi pada hari ke-12 hingga ke-18 dari siklus menstruasi 28-30 hari. Penentuan masa subur biasanya menggunakan metode kalender, namun kurang akurat karena dipengaruhi oleh fluktuasi hormon. Metode kalender seringkali tidak akurat dalam mendeteksi masa subur, sehingga diperlukan metode yang lebih presisi untuk memprediksi ovulasi. Penelitian ini bertujuan untuk mendeteksi ovulasi pada wanita menggunakan analisis citra saliva ferning dengan ekstraksi fitur Gray-Level Co-occurrence Matrix (GLCM) berbasis machine learning. Penelitian menggunakan dua algoritma, yaitu k-nearest neighbor (K-NN) dan Naive Bayes, untuk mengklasifikasikan masa tidak subur (infertile period), masa transisi menuju masa subur (intermediate period), dan masa puncak kesuburan (fertile period). Evaluasi dilakukan berdasarkan akurasi, presisi, dan recall, dengan beberapa rasio pembagian data (split ratio). Pada pengujian dengan split ratio 80:20 dan 90:10, kedua algoritma mencapai akurasi, presisi, dan recall sebesar 100%. Namun, pada pengujian dengan K-NN k=2 dan split ratio 70:30, akurasi turun menjadi 70%, dengan presisi 69% dan recall 55%.
Supporting Start-ups in Indonesia: Examining Government Policies, Incubator Business, and Sustainable Structure for Entrepreneurial Ecosystems and Capital Bernardus, Denny; Arisa, Ma'rifani Fitri; Sufa, Siska Armawati; Suparwata, Dewa Oka
International Journal of Business, Law, and Education Vol. 5 No. 1 (2024): International Journal of Business, Law, and Education
Publisher : IJBLE Scientific Publications Community Inc.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56442/ijble.v5i1.372

Abstract

This research investigates the complex dynamics that shape the sustainability of start-ups in Indonesia, focusing on the influence of government policies, networks, capital structure, entrepreneurial ecosystem, and business incubators. Using Structural Equation Modeling with Partial Least Squares, this study analyzes data collected from 315 sample start-ups across various sectors. The results show significant relationships among the factors studied. Government policy emerges as a critical determinant, impacting business incubators and the broader entrepreneurial ecosystem. Networks and capital structures also play an essential role, in influencing business incubators and the entrepreneurial landscape. This study highlights the interconnectedness of these elements and underscores the importance of a holistic approach to foster sustainable start-ups. Theoretical implications suggest integrating factors in entrepreneurship models, emphasizing the role of policy-driven ecosystem development, network-centric approaches, and consideration of financial dynamics. Practical implications guide policy makers, entrepreneurs, investors, and business incubator managers in shaping a supportive and dynamic start-up ecosystem. While acknowledging limitations, this study contributes valuable insights into entrepreneurship and offers a foundation for future investigations into the sustainability of start-ups in various contexts.
Sistem Rekomendasi Pemilihan Komponen Komputer Menggunakan Metode AHP dan Profile Matching Salmanarrizqie, Ageng; Vitianingsih, Anik Vega; Kristyawan, Yudi; Maukar, Anastasia Lidya; Marisa, Fitri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7643

Abstract

Computers have become one of the technological tools that play a crucial role in enhancing society's productivity. Therefore, many desktop computer users assemble their own computers to achieve computer performance according to their preferences or needs. However, some people lack information about the variations, specifications, and capabilities of each computer component to be assembled. This research offers a recommendation system that is part of a decision support system (DSS) to assist users in providing recommendations for computer components that are being sought and needed based on brand, price, and specifications using the Analytic Hierarchy Process (AHP) and Profile Matching methods. Parameters are based on the processor, motherboard, graphics card (VGA), storage, RAM, power supply, and casing with priority categories based on specifications, price, and brand. Data weighting is done using the Analytic Hierarchy Process (AHP) method, while the Profile Matching method is used for ranking the weighting results. The research results show an accuracy rate of 60% using the Profile Matching method, while the AHP method achieves an accuracy rate of 57%.
Analisa Prediksi Varietas Buah Salak yang Sesuai dengan Lahan Daerah Kabupaten Banjarnegara Menggunakan Algoritma C45 Marisa, Fitri; Maukar, Anastasia L
Jurnal Teknologi dan Manajemen Informatika Vol. 8 No. 1 (2022): Juni 2022
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v8i1.7521

Abstract

Salak is a potential horticultural sector that is a leading commodity in Banjarnegara. Salak fruit varieties have fruit categories that have their advantages. Variants of salak fruit include ivory salak, granulated sugar salak, pondoh salak, and honey salak. Based on data released from the relevant government agencies, further research was carried out related to analyzing and conducting research to predict salak fruit varieties. This variety is suitable for land in every area in Banjarnegara with predictive analysis using the C4.5 algorithm. This method has been widely developed to classify and predict a case with a fairly high degree of accuracy. From this study, researchers hope that it can contribute farmers to determining the type of salak fruit that is most suitable for the land they own so that later the harvest obtained by farmers can be maximized
Analisis Sistem Pembelajaran Daring Berbasis Gamification Collaboration untuk Mendukung Merdeka Belajar Menggunakan Octalysis Framework Maukar, Anastasia Lidya; Vitianingsih, Anik Vega; Marisa, Fitri; Pramudita, Atanasia; Putri, Jessica Ananda; Pramisela, Intan Yosa
Jurnal Teknologi dan Manajemen Informatika Vol. 8 No. 2 (2022): Desember 2022
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v8i2.7855

Abstract

The COVID-19 pandemic has had a major impact on many things. Education, which is one of the important aspects in supporting human life, also felt the impact of the pandemic. Based on Circular Letter Number 4 of 2020 concerning the Implementation of Education Policies during the emergency period of the spread of COVID-19, the government has a policy that face-to-face education is not allowed to be carried out. Therefore, the world of education began to implement distance learning or e-Learning.  In addition to how to teach and learn, there are other things that need to be considered for the success of the process. Another thing is student learning motivation. Changes in the teaching and learning process also have an impact on student learning motivation. In this study, a questionnaire has been distributed to find out the core drive of student learning motivation. Based on a questionnaire that has been filled out by 167 respondents, the core drive that influences students' learning motivation is at a high level. This indicates that the level of student learning motivation during the COVID-19 pandemic is still high.
Klasifikasi Jenis Rumah Adat Malaka Menggunakan Metode Convulational Neural Network (CNN) Nahak, Redemtus; Bura, Audyel Umbu; Araujo, Aprilio Demetrius De; Un, Fransiskus Deni; Ladopurab, Bartolomeus Wadan; Marisa, Fitri; Maukar, Anastasia L
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.10352

Abstract

In Indonesia, there is a rich diversity of cultures, one of which is traditional houses. Traditional houses essentially have the potential to represent the way of life, culture, and local economy. Traditional houses in Indonesia, particularly in the Malaka region, are important cultural symbols that can be regarded as cultural icons in Malaka and Indonesia. They provide a historical perspective, heritage, and reflect the progress of society in a civilization. The Convolutional Neural Network (CNN) method is used in this research. In this study, the CNN algorithm is applied to classify traditional house objects. These traditional house objects are divided into two categories: Kolibein Traditional House and Laleik Traditional House. The objective of this research is to classify traditional houses in Malaka, namely Kolibein Traditional House and Laleik Traditional House, and also to determine the accuracy level of CNN classification results. The previously created model is tested using test data to assess its accuracy. The testing is conducted on 20 data points, with 10 data points in each respective class. The testing results show that the classification of Kolibein and Laleik traditional houses is error- free or very accurate. Based on the model developed for classifying Kolibein and Laleik traditional houses using the Convolutional Neural Network method, it is evident that this method is capable of producing accurate results. The obtained results indicate that the accuracy, based on the classification report using images of Kolibein and Laleik traditional houses, reaches 100%. Therefore, it can be concluded that the constructed CNN model has a high level of accuracy.
KLASIFIKASI JENIS PATUNG MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN) Luruk, Maria Ovalia; Rahman, Aviv Yuniar; Marisa, Fitri
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 12 No 1 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i1.9247

Abstract

Seni patung merupakan hasil pengolahan dari berbagai unsur tersusun dalam harmoni sehingga melahirkan keindahan khas yang disebut seni patung, seni patung pada dasarnya memiliki multi pandang, ruang padat, ruang pandang dan juga keindahan Maka itu perlu dilakukan Klasifikasi terhdapat jenis patung. Dimana pada Penelitian ini bertujuan untuk mengklasifikasikan Jenis jeni Patung menggunakan metode Convolutional Neural Network (CNN) Data dikumpulkan dari sejumlah sampel jenis Patung dibagi menjadi 5 class yaitu Patung Habel Melengkung, Patung Geraba Hebel Melengkung, Patung Gerabah Teracotta, Patung Hebel Melengkung Biarawan, Patung Buah Iblis). Dianalisis menggunakan metode CNN untuk ekstraksi fitur. Hasil penelitian menunjukkan bahwa score akurasi yang tertinggi. Pada pengujian, CNN epoch 10= berbagai pecahan data (split ratio) seperti 90:10 mencapai akurasi sebesar 100%. Selanjutnya, hasil score akurasi yang terendah. Pada Pengujian, epoch 50 = split ratio 10:90 mencapai akurasi sebesar 99,79%.
Co-Authors Addian Nur Rijal Adi Masliardi Ahmad, Sharifah Sakinah Syed Akbar, Ismail Ali muhajir, Ali Alifia Nandira Maharani Anastasia Lidya Maukar Andy Hardianto Anik Vega Vitianingsih Anjani, Sofia Puspa Araujo, Aprilio Demetrius De Arie Restu Wardhani Arisanti, Diah Aviv Yuniar Rahman Badrussalam, Nanda Bagas Imadani Putra, Alif Bambang Amir Alhakim Bura, Audyel Umbu Christine Ulina Tarigan Dahlia Denny Bernardus Dewa Oka Suparwata Dini Kristianti, Dini Domingos Sinorio de Araujo, Domingos Dwi Fita Heriyawati Dwi Purnomo Efendi, Dedi Usman Elok Novita Fatmawati, Amelia Firman Hidayat Firman Nurdiyansyah, Firman Hajar Mukaromah Hamzah Al Imran Hardiyanto, Andy Haryanto, Kurniawan Wahyu Ika Pranita Siregar Indah Dwi Mumpuni Indra Dharma Wijaya, Indra Dharma Istiadi jauhar, afif KRISTIAWAN KRISTIAWAN Kushariyadi Kushariyadi Ladopurab, Bartolomeus Wadan Larasati, Isbalaikana Luruk, Maria Ovalia Margaret Stevani Marilaeta Nurak, Yulita Maukar, Anastasia Maukar, Anastasia L Maukar, Anastasya Lidya Mausa Agrevinna Meidy Diliana Agustin Nahak, Redemtus Neno, Adi nisti, Melita Nova Ch. Mamuaya NURDIANSYAH, FIRMAN Nurfitri, Indah Karminia Pradana, Teguh Pramisela, Intan Yosa Pramudita, Atanasia Prissiani Andi Ningrum Purnamasari, Putri Indah Puspitarini, Erri Wahyu Putra, Dimas Rossiawan Hendra Putra, Rangga Pahlevi Putri, Avira Maresa Putri, Chauliyah Fatma Putri, Jessica Ananda Rena Augia Putrie Rini Agustina Rivaldiknas Gampar, Philipus Rochmawati, Sofi Nur Rosario, Maria Madalena Do Salmanarrizqie, Ageng Sidi, Husri Slamet Riyadi, Slamet Riyadi Sofyan Rachma Danni, Muhammad Sufa, Siska Armawati Sufianto, Dani Suprianto Suprianto Susti Rumianti Ulfah Rahamawati, Ulya Un, Fransiskus Deni Wahyu Iriananda, Syahroni Warda Indadihayati Wardianto, Wardianto Wijaya, Indra Darma Yudi Kristyawan, Yudi