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All Journal AMIKOM ICT AWARD 2010 TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Informasi dan Ilmu Komputer Pro Bisnis Telematika Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal Sains dan Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan ILKOM Jurnal Ilmiah RESEARCH : Computer, Information System & Technology Management JURTEKSI Jurnal Teknologi Terpadu Jurnal Pengabdian Kepada Masyarakat (Mediteg) Indonesian Journal of Electrical Engineering and Computer Science Madani : Indonesian Journal of Civil Society Jurnal Algoritma Jurnal Pengabdian Mitra Masyarakat (JPMM)
Yuli Purwati
Universitas Amikom Purwokerto
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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PROGRAM PENDAMPINGAN FORMULASI INOVASI RISET PADA PUSAT STUDI MEDIA, GAME, DAN MOBILE UNIVERSITAS AMIKOM PURWOKERTO UNTUK MENINGKATKAN JUMLAH LUARAN PENELITIAN Yuli Purwati; Rujianto Eko Saputro; Sarmini Sarmini; Ria Indriyani; Rizqi Aulia Widianto
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 6, No 4 (2022): Desember
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v6i4.10962

Abstract

ABSTRAKRendahnya jumlah gagasan inovasi riset berdampak pula pada rendahnya jumlah kolaborasi riset antara mahasiswa dengan dosen anggota pusat studi Media, Game, dan Mobile. Selain itu, permasalahan ini juga berdampak pada rendahnya jumlah publikasi ilmiah penelitian dari hasil kolaborasi riset antara dosen dengan mahasiswa di bidang Media, Game, dan Mobile. Kegiatan ini bertujuan untuk mendampingi dosen anggota pusat studi dalam merumuskan inovassi riset pada pusat studi Media, Game dan Mobile di Universitas Amikom Purwokerto. Ada tiga tahapan dalam pelaksanaan kegiatan yaitu tahap persiapan, implementasi dan evaluasi. Kegiatan pendampingan dilakukan secara daring dengan menghadirkan narasumber dari Universiti Teknikal Malaysia (UTeM) dan diikuti oleh 11 dosen dari pusat studi. Hasil dari kegiatan webinar yang telah terlaksanan yaitu adanya peningkatan jumlah judul/ide inovasi riset yang ditawarkan untuk kolaborasi riset antara mahasiswa dengan dosen anggota Pusat Studi Media, Game, dan Mobile pada skema MB-KM Riset penyelenggara FIK di Semester Genap Tahun Akademik 2021/2022 sebanyak 5 ide/Judul dan di Semester Ganjil Tahun Akademik 2022/2023 sebanyak 29 ide/judul. Kata kunci: pendampingan; pusat studi; game; kolaborasi; riset ABSTRACTThe low number of research innovation ideas also impacts the low number of research collaborations between students and lecturers: members of the Media, Game, and Mobile Research Group. In addition, this problem also impacts the low number of scientific research publications resulting from research collaborations between lecturers and students in the fields of Media, Games, and Mobile. This activity aims to assist the lecturers in formulating research innovations at the Media, Game, and Mobile research group on Universitas AMIKOM Purwokerto. There are three stages in the implementation of activities: preparation, implementation, and evaluation. Mentoring activities were conducted online by presenting the main speaker from Universiti Teknikal Malaysia Melaka (UTeM) and were attended by 11 lecturers from study centers. The results of the webinar activities that have been carried out are an increase in the number of titles/innovation research ideas offered for research collaboration between students and lecturers of the Center for Media, Game, and Mobile Studies in the MB-KM Research scheme FIK organizers in the Even Semester of the 2021/2022 Academic Year as many as 5 ideas/titles and the Odd Semesters of the 2022/2023 Academic Year as many as 29 ideas/titles. Keywords: accompaniment; study center; games; collaboration; research
DECISION SUPPORT AND MONITORING SYSTEMS FOR HUMANITARIAN PROGRAMS USING FORWARD CHAINING METHOD Purwati, Yuli; Pambudi, Aldi Setia
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 7 No 2 (2022): JITK Issue February 2022
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1226.006 KB) | DOI: 10.33480/jitk.v7i2.2813

Abstract

One of the covid-19 pandemic impacts is the emergence of new social problems. Humanitarian agencies are helping the government's role to overcome various social issues that arise through its humanitarian programs. One of which is with the MSR program from Aksi Cepat Tanggap Purwokerto. With increasing social problems and the complexity of improving data collection due to the covid-19 pandemic, the methods' limitations previously using paper will be difficult, and the limits of people who have the expertise to make decisions related to the submission of prospective beneficiaries. A decision support system is needed to provide suggestions of results under the rules that have will determining and monitoring and filing systems to provide convenience in managing data collection.
Feature Selection Technique to Improve the Instances Classification Framework Performance for Quran Ontology Yuli Purwati; Fandy Setyo Utomo; Nikmah Trinarsih; Hanif Hidayatulloh
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1195

Abstract

The Al-Quran is the sacred book of Muslims, and it provides God's word in the form of orders, instructions, and guidelines for people to follow to have happy lives both here and in the afterlife. Several earlier research has used ontologies to store the knowledge found in the Quran. The previous study focused on extracting the relationship between classes and instances or the "is-a relation" by classifying instances based on the referenced class. Based on the performance testing of the instances classification framework, the test results show that Support Vector Machine (SVM) with Term Frequency-Inverse Document Frequency (TF-IDF) and stemming operation had dropped the accuracy value to 65.41% when the test data size was increased to 30%. Likewise, with BPNN with TF-IDF and stemming operations. In the Indonesian Quran translation dataset with a test data size of 30%, the accuracy value drops to 57.86%. Instances classification based on the thematic topics of the Qur'an aims to connect verses (instances) to topics (classes) to get an overall picture of the topic and provide a better understanding to users. This study aims to apply the feature selection technique to the instances classification framework for the Al-Quran ontology and to analyze the impact of applying the feature selection technique to the framework with a small dataset and training data. The instances classification framework in this study consists of several stages: text-preprocessing, feature extraction, feature selection, and instances classification. We applied Chiq-Square as a technique to perform feature selection. SVM and BPNN as a classifier. Based on the experiment results, it can be concluded that the feature selection implementation using Chi-Square increases the value of precision, f-measure, and accuracy on the test data size from 40% to 60% in all datasets. The feature selection using Chi-Square and SVM classifier provides the highest precision value with a test data size of 60% on the Tafsir Quran dataset from the Ministry of Religious Affairs Indonesia: 64.36%. Furthermore, the feature selection implementation and BPNN classifier also increase the highest accuracy value with a test data size of 60% in the Quranic Tafsir dataset from the Ministry of Religion of the Republic of Indonesia: 63.09%.
MUSIC RECOMMENDATION SYSTEM BASED ON COSINE SIMILARITY AND SUPERVISED GENRE CLASSIFICATION Jamie Mayliana Alyza; Fandy Setyo Utomo; Yuli Purwati; Bagus Adhi Kusuma; Mohd Sanusi Azmi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 9 No. 1 (2023): JITK Issue August 2023
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v9i1.4324

Abstract

Categorizing musical styles can be useful in solving various practical problems, such as establishing musical relationships between songs, similar songs, and finding communities that share an interest in a particular genre. Our goal in this research is to determine the most effective machine learning technique to accurately predict song genres using the K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) algorithms. In addition, this article offers a contrastive examination of the K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) when dimensioning is considered and without using Principal Component Analysis (PCA) for dimension reduction. MFCC is used to collect data from datasets. In addition, each track uses the MFCC feature. The results reveal that the K-Nearest Neighbors and Support Vector Machine offer more precise results without reducing dimensions than PCA results. The accuracy of using the PCA method is 58% and has the potential to decrease. In this music genre classification, K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) are proven to be more efficient classifiers. K-Nearest Neighbors accuracy is 64,9%, and Support Vector Machine (SVM) accuracy is 77%. Not only that, but we also created a recommender system using cosine similarity to provide recommendations for songs that have relatively the same genre. From one sample of the songs tested, five songs were obtained that had the same genre with an average accuracy of 80%.
Rectified Linear Units and Adaptive Moment Estimation Optimizer on ANN with Saved Model Prediction to Improve The Stock Price Prediction Framework Performance Sekhudin Sekhudin; Yuli Purwati; Fandy Setyo Utomo; Mohd Sanusi Azmi; Pungkas Subarkah
ILKOM Jurnal Ilmiah Vol 15, No 2 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i2.1586.271-282

Abstract

A stock is a high-risk, high-return investment product. Prediction is one way to minimize risk by estimating future prices based on past data. There are limitations to solving the stock prediction problem from previous research: limited stock data, practical aspects of application, and less than optimal stock price prediction results. The main objective of this study is to improve the prediction performance by formulating and developing the stock price prediction framework. Furthermore, the research provides a stock price prediction framework that can produce better prediction results than the previous study with fast computation time. The proposed framework deals with data generation, pre-processing and model prediction. In further, the proposed framework includes two prediction methods for predicting stock closing prices: stored model prediction and current model prediction. This study uses an artificial neural network with Rectified Linear Units as an activation function and Adam Optimizer to predict stock prices. The model we have built for each forecasting method shows a better MAPE value than the model in previous studies. Previous research showed that the lowest MAPE was 1.38% for TLKM shares and 0.81% for BBRI. Our proposed framework based on the stored model prediction method shows a MAPE value of 0.67% for TLKM shares and 0.42% for BBRI. While the current model prediction method shows a MAPE value of 0.69% for TLKM shares and 0.89% for BBRI. Furthermore, the stored model prediction method takes 1.0 seconds to process a single prediction request, while the current model prediction takes 220 seconds.
AN INNOVATIVE LEARNING ENVIRONMENT: G-MOOC 4D TO ENHANCE VISUAL IMPAIRMENTS LEARNING MOTIVATION Rujianto Eko Saputro; Berlilana Berlilana; Wiga Maulana Baihaqi; Sarmini Sarmini; Yuli Purwati; Fandy Setyo Utomo
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 9 No. 2 (2024): JITK Issue February 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v9i2.5037

Abstract

The proliferation of visual impairment among school-age children in Indonesia has prompted the need for specialized online learning solutions. The G-MOOC 4D platform, a novel Learning Management System (LMS), is designed to address this need by leveraging gamification and artificial intelligence to enhance accessibility for visually impaired users. This study reports on the development and testing of two AI models within the G-MOOC 4D framework: a facial recognition model for secure user authentication and a voice command model for interactive learning. User Acceptance Testing (UAT), conducted with expert users, namely teachers at a special needs school, showed high approval rates for the platform's features. The results show that all metrics, accuracy, precision, and recall reach their optimal values at a distance of 40 cm for face detection. The respective metric scores at that distance, precision: 100%, accuracy: 98%, and recall: 97%. Additionally, the voice command functionality tested achieved a 100% recognition rate, reflecting the platform’s potential to significantly ease the learning process for visually impaired students. The findings underscore the importance of integrating assistive technologies into educational platforms to ensure all students have equal access to learning opportunities.
COMPARATIVE ANALYSIS OF EXPONENTIAL SMOOTHING MODELS FOR SALES PREDICTION AND SUPPLY MANAGEMENT IN E-COMMERCE Aji Saeful; Fandy Setyo Utomo; Yuli Purwati; Mohd Sanusi Azmi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 1 (2024): JITK Issue August 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i1.5035

Abstract

In the growing era of e-commerce, stock management is crucial. Problems arise in forecasting sales in order to achieve effective stock management. This research uses the time series analysis method by focusing on comparing the accuracy of three forecasting methods: Single Exponential Smoothing (SES), Double Exponential Smoothing (DES), and Triple Exponential Smoothing (TES/Holt-Winter). This research provides a solution by comparing the performance of the three methods based on the Mean Absolute Error (MAE) results and prediction graphs. The goal is to determine the most accurate forecasting method using the time series analysis method with several stages, namely data preprocessing, train/test split, modeling, and performance metrics measurement. based on the test results show MAE SES 1077, DES 96, and TES (Holt-Winter) 101. Although DES has a lower MAE, TES (Holt-Winter) provides better accuracy, especially through prediction graph analysis. Holt-Winter is recognized as the most effective method in forecasting future sales, reliable for proper stock management in the dynamic e-commerce industry. This approach is expected to improve efficiency and accuracy in enterprise stock management, support the growth of online businesses, and contribute to the literature and practice of stock management. The use of time series analysis methods, especially Holt-Winter, is considered an important strategic step to optimize sales prediction, positively impact stock management, and create a competitive advantage in a growing market
PELATIHAN APLIKASI PEMANTAUAN STATUS GIZI BALITA BERBASIS MOBILE BAGI KADER POSYANDU PERUMAHAN PURI KENCANA SUMBANG Purwati, Yuli
Jurnal Pengabdian Kepada Masyarakat (MEDITEG) Vol. 7 No. 1 (2022): Jurnal Pengabdian Kepada Masyarakat (MEDITEG)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat (P3M) Politeknik Negeri Tanah Laut (Politala)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/mediteg.v7i1.99

Abstract

The Posyandu housing Puri Kencana Sumbang has now formed a cadre to carry out monitoring activities for under-five nutrition by weighing. However, due to the Covid-19 pandemic, this activity has not been carried out routinely. The purpose of this community service is to provide solutions to these problems by conducting training on the implementation of the application for monitoring the nutritional status of children and toddlers using mobile applications and website applications. This activity is in the form of providing information on the standards and indicators used in monitoring the nutritional status of toddlers as well as the use of applications used for the process of recording data on the nutritional status of children and toddlers which can be accessed online to Posyandu cadres and residents of Puri Kencana Sumbang housing. The achievements of this community service activity are that 12 participants consisting of representatives of cadres and residents of housing can understand the standards and indicators used in monitoring the nutritional status of toddlers and increase their ability to use the application for monitoring the nutritional status of toddlers, this is indicated participants became aware of the standards for measuring nutritional status and were able to name the measurement indicators. All participants also agreed that the features in the application were easy to use and very useful for monitoring the nutritional status of toddlers.
Pelatihan Desain Konten Instagram untuk Penguatan Branding SD Qaryah Thayyibah Purwokerto Purwati, Yuli; Al Fauzan, Lukman; Limaz Morallez, Airlangga
Jurnal Pengabdian Kepada Masyarakat (MEDITEG) Vol. 9 No. 1 (2024): Jurnal Pengabdian Kepada Masyarakat (MEDITEG)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat (P3M) Politeknik Negeri Tanah Laut (Politala)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/mediteg.v9i1.200

Abstract

As an educational institution, schools must have strong branding so that parents will see the reputation and value of the school. Currently, SD Qita has several social media, usually used to provide various information related to the school, such as vision and mission, student activities, events and school registration information. The analysis results show that the current Instagram feed display and content design still do not show the branding of SD Qita, so visitors cannot immediately understand the school's image if they only glance at the feed display and Instagram content design. The achievement of this service activity is that the teachers gain knowledge related to creating Instagram content design, creating video reels and knowledge related to Instagram SEO further to strengthen the branding and value of SD Qita.
Analisis dan Perancangan Antarmuka Aplikasi Wisata Menggunakan Metode User Centered Design (UCD) Purbo, Yevi Septiray; Utomo, Fandy Setyo; Purwati, Yuli
Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i2.977

Abstract

Lampung has many tourist attractions and natural areas that attract the attention of tourists, both domestic and foreign. However, there are still challenges in optimizing Lampung's tourism potential. One of the challenges is limited access to information regarding tourist destinations, accommodation and available activities. Apart from that, coordination between tourists and related parties such as destination managers and tourism services also need to be improved. To overcome this problem, a prototype of the VACALAM (Vacation Lampung) application was designed using Figma with the User-Centered Design (UCD) method. This research aims to increase user comfort and satisfaction in using the Vacalam application and encourage tourists to visit Lampung. In this application there are several features including ticket booking features, tour lists, trending tours, and a list of events in Lampung. The results of this research are user interface designs that follow good design principles, including simplicity, consistency, and readability. The use of colors, typography, and icons are also considered to improve the clarity and visual appearance of the application. The good user interface design and user experience have been tested using the System Usability Scale (SUS), with a final score of 71.75. These results provide guidance for other application developers in designing engaging and responsive user interfaces and user experiences using Figma.
Co-Authors Adam Prayogo Kuncoro Aji Saeful Al Fauzan, Lukman Alfazri, Rifa Azmi, Mohd Sanusi Bafaqih, Mohamad Aqil Bagus Adhi Kusuma Baihaqi, Wiga Maulana Berlilana Berlilana Casro Casro Dwi Krisbiantoro Ely Purnawati, Ely Esa Damayanti Fandy Setyo Utomo Gustin Setyaningsih Hanif Hidayatulloh Imung Dwi Upaya Jamie Mayliana Alyza Khoirun Nisa Limaz Morallez, Airlangga Linda Perdanawanti Mohd Sanusi Azmi Najmuddin, Faris Labib Nandang Hermanto Nikmah Trinarsih Nurfaizah Pambudi, Aldi Setia Prasetya, Dhika Adi Prasetya Pungkas Subarkah Purbo, Yevi Septiray Putranto, Banu Dwi Ria Indriyani Rizqi Aulia Widianto Rujianto Eko Saputro Sagita, Selvi Sarmini - Sarmini Sekhudin Sekhudin Shafira, Lulu Suliswaningsih Suliswaningsih, Suliswaningsih Tandi Kukuh Jati Laksono Trinarsih, Nikmah Utomo, Dadang Wahyu Wibowo, Nurma Budi Santoso Wiga Maulana Baihaqi