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All Journal Jurnal Sains dan Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnas Nasional Teknologi dan Sistem Informasi ANDHARUPA Jurnal Informatika Jurnal Pilar Nusa Mandiri Indonesian Journal of Artificial Intelligence and Data Mining JTAM (Jurnal Teori dan Aplikasi Matematika) JURTEKSI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Indonesian Journal of Data and Science Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) Journal of Technology and Informatics (JoTI) DECODE: Jurnal Pendidikan Teknologi Informasi Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi JOMPA ABDI: Jurnal Pengabdian Masyarakat Digital Transformation Technology (Digitech) ABDINE Jurnal Pengabdian Masyarakat Bulletin of Social Informatics Theory and Application Jurnal Pengabdian Kepada Masyarakat Ceria Jurnal Medika: Medika Jurnal Pengabdian Kepada Masyarakat Bersinergi Inovatif TECHNOVATE
Subarkah, Pungkas
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Design and Build Chatbot Application for Tourism Object Information in Bengkulu City Rohman, M. Abdul; Subarkah, Pungkas
TECHNOVATE: Journal of Information Technology and Strategic Innovation Management Vol. 1 No. 1 (2024): January 2024
Publisher : PT.KARYA GEMAH RIPAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52432/technovate.1.1.2024.28-34

Abstract

As technology develops and the number of new arrivals to the city of Bengkulu increases, the need for information regarding information related to tourism in Bengkulu is also increasing. The growth of Bengkulu tourism increases very rapidly every year as many local and foreign tourists visit the city of Bengkulu. Therefore, the author intends to build a chatbot that functions as a Virtual Assistant for Bengkulu tourists and those outside the city of Bengkulu. This chatbot is able to provide information to tourists through data stored in the system. The implementation and design of this software produces a chatbot that is built using the Extreme Programming (XP) method. Chatbots are also able to answer questions according to the abilities embedded in them. The application of chatbots provides fast information in a relatively short time to obtain information because the questions asked can be answered directly.
Pendampingan Teknologi Informasi E- Smart Care sebagai Upaya Pencegahan Stunting secara Dini pada Remaja melalui Sekolah Siaga Kependukan (SSK) Subarkah, Pungkas; Hermanto, Nandang; Sari, Rida Purnama; Kholifah Dwi Prasetyo Kartika, Nur; Nasar Ghanim, Nadif; Arsi, Primandani
ABDINE: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2024): ABDINE : Jurnal Pengabdian Masyarakat
Publisher : Sekolah Tinggi Teknologi Dumai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52072/abdine.v4i2.984

Abstract

Sekolah Siaga Kependudukan (SSK) di SMA Negeri 1 Wangon, merupakan SSK rintisan sekolah yang mengintegrasikan pndidikan kependudukan dan keluarga berencana, ke dalam beberapa mata pelajaran sebagai pengayaan materi pembelajaran, dimana di dalamnya terdapat pojok kependudukan sebagai salah satu sumber belajar peserta didik. Permasalahan yang dihadapi oleh mitra yaitu belum adanya teknologi informasi yang menunjang untuk pencegahan stunting secara dini di SSK. Metode pelaksanaan pengabdian masyarakat ini dilakukan dengan tahapan pra-pelaksanaan, tahap pelaksanaan dan tahap evaluasi. Dari hasil pelaksanaan kegiatan yang sudah dilakukan maka didapatkan  para peserta kegiatan mengikuti pelatihan dengan baik,  dengan menguasai materi selama pelatihan berlanggsung dan peningkatan kemampuan peserta dalam menggunakan teknologi infomasi E-Smart Care berbasis android dan website. Dengan terlaksana program pendampingan ini dari Tim Program Kemitraan Masyarakat (PKM) 2024, bahwa mitra mendapatkan peningkatan pengetahuan yaitu penggunaan aplikasi E-smart Care berbasis android serta para peserta mendapatkan peningkatan keterampilan cara mengoperasikan aplikasi secara benar. Hasil respon terhadap pelatihan ini yaitu rata-rata memberikan predikat “Sangat Baik”.
Improving K-Means Clustering Accuracy for Academic Success Investigation With Extreme Gradient Boosting Algorithm Darmayanti, Irma; Adhimah, Laily Farkhah; Sadewo, Rizki; Hidayati, Nurul; Subarkah, Pungkas
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.26657

Abstract

Human Resources (HR) has a very important role in the development of the nation, so to improve the quality of human resources, education is needed. Education has a role in developing science, disseminating, socializing, and applying it. So that education is one of the important factors in advancing a nation. However, there are still many challenges in achieving quality education, especially in developing countries such as Indonesia, such as parental education level, socioeconomic status, and environmental conditions can also affect the quality of education and students' opportunities for academic success. The research methods used in this research are problem identification, data collection, data analysis, and evaluation. The results in this study are an increase in accuracy of 38.55% from the difference in the K-Means accuracy value of 14% resulting from the David Bounded Index and the use of the extreme gradient adaboost algorithm.
Early Prediction of Stroke Disease Diagnosis Patients Using Data Mining Algorithm Comparison Subarkah, Pungkas; Damayanti, Wenti Risma; Sabaniyah, Arbangi Puput
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.25955

Abstract

Stroke constitutes a medical emergency of paramount significance, characterized by a notably elevated mortality rate, and stands as the foremost cause of mortality within hospital settings. The dataset employed for this analysis is sourced from Kaggle, denoted as the Brain Stroke Dataset, encompassing a total of 4981 records. This research aims to carry out early prediction of stroke sufferers using several algorithms including the ANN algorithm, CART, KNN, and the NBC algorithm. The results obtained in the ANN algorithm obtained an accuracy of 93.53%, in the CART algorithm of 95.02%, in the KNN algorithm of 91.09% and in the NBC algorithm of 88.44%. With the outcomes of this research, the use of the cart set of rules may be used for early evaluation of stroke sufferers because it has a good degree of accuracy and is listed inside the excellent type kind
IMPROVEMENT OF NAIVE BAYES ALGORITHM IN SENTIMENT ANALYSIS OF SHOPEE APPLICATION REVIEWS ON GOOGLE PLAY STORE Elistiana, Khoerotul Melina; Bagus Adhi Kusuma; Subarkah, Pungkas; Awal Rozaq, Hasri Akbar
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 6 (2023): JUTIF Volume 4, Number 6, Desember 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.6.1486

Abstract

Reviews of the shopee application on the google play store are included in useful information if processed properly. Old or new users can analyze app reviews to get information that can be used to evaluate services. The activity of analyzing application reviews is not enough just to see the number of stars, it is necessary to see the entire contents of the review comments to be able to know the intent of the review. A sentiment analysis system is a system used to automatically analyze a review to obtain information including sentiment information that is part of an online review. The data is classified using Naive Bayes. A total of 1,000 shopee app user reviews were collected to form the sample dataset. The purpose of this study is to determine the sentiment analysis of shopee application reviews in the Google Play Store using the Naive Bayes algorithm. The stages of this research include, data collection, labeling, pre-processing, sentiment classification, and evaluation. In the pre-processing stage there are 6 stages, namely Cleaning, Case folding, Word Normalizer, Tokenizing, Stopword Removal and Stemming. TF-IDF (Term Frequency - Inverse Document Frequency) method is used for word weighting. The data will be grouped into two categories, namely negative and positive. The data will then be evaluated using accuracy parameter testing. The test results show an accuracy value of 81%, this result shows that shopee application reviews tend to be negative.
Sentiment Analysis of Twitter Cases of Riots at Kanjuruhan Stadium Using the Naive Bayes Method Katiandhago, Bryan Jerremia; Mustolih, Akhmad; Susanto, Wachyu Dwi; Subarkah, Pungkas; Satrio Nugroho, Chendri Irawan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.2196

Abstract

Sentiment analysis is a process carried out to analyze opinions, sentiments, judgments, and emotions from the riot case at the kanjuruhan stadium. The purpose of this research is to find out public opinion about the tragedy that is currently happening at the Kanjuruhan Stadium. the data was obtained from social media Twitter using the Twitter API, then after that, an analysis was carried out. data from the results of the analysis will be classified using the Naive Bayes method. The classification process is divided into 7 (seven) stages, namely Crawling, Cleansing, pre-processing, labeling, classification, data training, and data testing. In the labeling process, data is classified into 2 (two) classes, namely the positive class and the negative class. The data obtained before the preprocessing process was 1963 tweets, after the preprocessing the data obtained was 1001 tweets. The data will be trained and tested using the naive Bayes classification method. classification results obtained precision values of 82% for negative data and 65% for positive data, recall values obtained 74% for negative data and 75% for positive data, F1-score values obtained 78% for negative data and 70% for positive data, while accuracy value obtained 74%.
DESIGNING UI/UX OF DOCTOR'S CONSULTATION APPLICATION USING DESIGN THINKING METHOD Damayanti, Wenti Risma; Kuncoro, Adam Prayogo; Subarkah, Pungkas; Saputro, Rujianto Eko
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 2 (2024): Maret 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i2.3053

Abstract

Abstract: For all people in the world, the application of information and communication technology has become something that is used in everyday life. All information can be accessed easily using current developments in various technologies. The process of searching for various information on the internet has become a habit of today's society. One of the information that people often seek is about health. Several available online health consultation service applications provide considerable benefits for all users. One method used for the UI and UX design process is design thinking. The average user of the application is 18-35 years old. The user interface provided in this application is not yet user friendly, especially for the elderly. User interface (UI) and user experience (UX) are important so that users feel comfortable when using an application.            Keywords: information technology; consulting application; UI/UX; design thinking  Abstract: Bagi seluruh masyarakat di dunia, penerapan teknologi informasi dan komunikasi menjadi hal yang sudah digunakan dalam kehidupan sehari-hari. Seluruh informasi dapat diakses dengan mudah menggunakan perkembangan berbagai macam teknologi saat ini. Proses mencari berbagai informasi di internet sudah menjadi kebiasaan masyarakat saat ini. Salah satu informasi yang sering dicari oleh masyarakat yaitu tentang kesehatan. Beberapa aplikasi layanan konsultasi kesehatan online yang tersedia memberikan manfaat yang cukup besar bagi seluruh pengguna. Salah satu metode yang digunakan untuk proses desain UI dan UX adalah design thinking. Pengguna aplikasi tersebut rata-rata berusia 18-35 tahun. Tampilan user interface yang disediakan pada aplikasi tersebut belum bersifat user friendly, terutama bagi kalanagn lansia. User interface (UI) dan user experience (UX) menjadi hal penting supaya pengguna merasakan kenyamanan pada saat menggunakan sebuah aplikasi.            Keywords: teknologi informasi; aplikasi konsultasi; UI/UX; design thinking
DESIGNING UI/UX FOR ELEMENTARY SCHOOL E-LEARNING USING DESIGN THINKING METHOD Anshari, Muhammad Rifqi; Kuncoro, Adam Prayogo; Subarkah, Pungkas
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 3 (2024): Juni 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i3.3177

Abstract

Abstract: Advances in technology and the internet have an impact on various daily activities, including the teaching and learning process. E-learning facilitates flexible learning without being constrained by space and time constraints. With e-learning, subject matter can be delivered consistently and more standardly than conventional learning which depends on the conditions of the teacher or instructor. One school in Banjarnegara Regency faced problems with students who had difficulty in learning, especially English. The learning media owned is limited to package books only. Therefore, schools need to have media that can support the learning process to be more optimal. This study aims to design and test UI/UX e-learning designs that suit the needs of the school using the design thinking method. This UI/UX design is expected to be an effective solution to overcome the limitations of learning media and improve the quality of student learning. Before the UI/UX design is implemented into the system, this study also conducts testing of the UI/UX design to assess its feasibility. Testing using the SUS (System Usability Scale) method resulted in a value of 82 with grade B, so it can be concluded that the design developed in this study is feasible to be deployed into the system and further developed.             Keywords: E-learning; design thinking; system usability scale; UI/UX Abstrak: Kemajuan teknologi dan internet berdampak pada berbagai aktivitas sehari-hari, termasuk proses belajar-mengajar. E-learning memfasilitasi pembelajaran yang fleksibel tanpa terkendala oleh batasan ruang dan waktu. Dengan e-learning, materi pelajaran dapat disampaikan secara konsisten dan lebih standar dibandingkan pembelajaran konvensional yang bergantung pada kondisi guru atau instruktur. Salah satu sekolah di Kabupaten Banjarnegara menghadapi permasalahan dengan peserta didik yang kesulitan dalam pembelajaran, khususnya bahasa Inggris. Media pembelajaran yang dimiliki terbatas hanya pada buku paket saja. Oleh karena itu, sekolah perlu memiliki media yang dapat menunjang proses pembelajaran agar lebih optimal. Penelitian ini bertujuan untuk merancang dan menguji desain UI/UX e-learning yang sesuai dengan kebutuhan sekolah tersebut menggunakan metode design thinking. Desain UI/UX ini diharapkan dapat menjadi solusi efektif untuk mengatasi keterbatasan media pembelajaran dan meningkatkan kualitas belajar siswa. Sebelum desain UI/UX diterapkan ke dalam sistem, penelitian ini juga melakukan pengujian terhadap desain UI/UX untuk menilai kelayakannya. Pengujian menggunakan metode SUS (System Usability Scale) menghasilkan nilai 82 dengan grade B, sehingga dapat disimpulkan bahwa desain yang dikembangkan dalam penelitian ini layak untuk dideploy ke dalam sistem dan dikembangkan lebih lanjut. Kata kunci: E-learning; design thinking; system usability scale; UI/UX 
OPTIMIZATION OF CART ALGORITHM BASED ON ANT BE COLONY FEATURE SELECTION FOR STUNTING DIAGNOSIS Subarkah, Pungkas; Ikhsan, Ali Nur; Wahyudi, Rizki; Rofiqoh, Dayana
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 2 (2025): Maret 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3579

Abstract

Abstract: One of the main health problems in children is stunting which is one of the concerns in the Sustainable Development Goals (SDGs). Specifically in Indonesia, the prevalence of stunting in 2024 is 21.6%. This figure is still relatively high, because the target prevalence of stunting is 14%. This study aims to implement machine learning knowledge through the Classification And Regression Trees (CART) algorithm based on Ant Be Colony (ABC) feature selection which aims to determine the increase in accuracy in analyzing stunting datasets. The data used comes from Kaggle which consists of 16500 datasets. The dataset consists of gender, age, birth length, birth weight, body length, body weight, breastfeeding and stunting status. The research methods used are data collection, data preprocessing, classification, and evaluation using K-fold cross validation. The results obtained in this research are the implementation of the CART algorithm obtained a value of 89.86% and the results of CART with Ant Be Colony (ABC) feature selection, which obtained an accuracy value of 93.65%. This shows that there is an increase in the accuracy value in the use of CART algorithm optimization and Ant Be Colony (ABC) feature selection by 3.76%. With the research results that have been obtained, it can be categorized as excellent accuracy value excellent. It is hoped that further research can be carried out by adding other classification algorithms or adding feature selection.            Keywords: classification; feature selection; optimazation; stunting Abstrak: Salah satu masalah kesehatan utama pada anak adalah stunting yang menjadi salah satu perhatian dalam Sustainable Development Goals (SDGs). Khusus di Indonesia angka Pravelensi stunting pada tahun 2024 di angka 21.6%. Angka ini masih tergolong tinggi, karena target angka pravelensi stunting ialah 14%. Penelitian ini bertujuan untuk mengimplementasikan pengetahuan machine learning melalui algoritma Classification And Regression Trees (CART) berbasis seleksi fitur Ant Be Colony (ABC) yang bertujuan untuk mengetahui peningkatan akurasi dalam menganalisis dataset stunting. Data yang digunakan bersumber dari Kaggle yang terdiri dari 16500 dataset. Dataset terdiri dari jenis kelamin, usia, panjang lahir, berat lahir, panjangg badan, berat badan, menyusui dan status stunting.  Metode penelitian yang digunakan adalah pengumpulan data, preprocessing data, klasifikasi, dan evaluasi menggunakan K-fold cross validation. Hasil yang diperoleh pada penelitian ini adalah Implementasi algoritma CART memperoleh nilai sebesar 89,86% dan hasil seleksi fitur CART dengan Ant Be Colony (ABC) memperoleh nilai akurasi sebesar 93,65%. Hal ini menunjukkan adanya peningkatan nilai akurasi pada penggunaan optimasi algoritma CART dan pemilihan fitur Ant Be Colony (ABC) sebesar 3,76%. Dengan hasil penelitian yang telah diperoleh dapat dikategorikan nilai akurasi yang diperoleh sangat baik. Diharapkan dapat dilakukan penelitian selanjutnya dengan menambahkan algoritma klasifikasi lain atau menambahkan seleksi fitur. Kata kunci: klasifikasi; optimalisasi; seleksi fitur; stunting
Sentiment Perspective of Government's Free Nutritious Meal Policy on Social Media X using Indo-BERT and Bi-LTSM Subarkah, Pungkas; Ikhsan, Ali Nur; Anggraeni, Epri; Sabaniyah, Arbangi Puput
Journal of Technology and Informatics (JoTI) Vol. 7 No. 2 (2025): Vol. 7 N. 2 (2025)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v7i2.1065

Abstract

This research has the potential to make an important contribution to the development of computationally-based sentiment analysis, especially in the context of government policies regarding the Free Meal Program that will be implemented throughout Indonesia. This research was conducted using Indo-BERT and Bi-LSTM algorithms. These approaches were used to categorize emotions into three groups: neutral, negative, and positive. Data is obtained from posts on social media X, then after processing the data, it will be applied to both algorithms, namely Indo-BERT and Bi-LSTM. The research findings show that the model's performance in determining the public sentiment of government policies. Validation and valuation were conducted using the f1 score, recall, and precision metrics. The evaluation findings show that the Indo-BERT algorithm is better than the Bi-LSTM algorithm with an accuracy value of 80% for Indo-BERT and 78% for the accuracy value of the Bi-LSTM algorithm, and the Indo-BERT accuracy value is included in the good classification accuracy value. The sentiment analysis results are also represented by word clouds for each positive, negative and neutral class, providing an intuitive picture of the words frequently used in public discourse on free nutritious meals.
Co-Authors Adam Prayogo Kuncoro Adhimah, Laily Farkhah Aditya Permana, Reza Afifah, Erika Luthfi Alifian , Raditya Sani Amin, M. Syaiful Anggraeni, Epri Anggraini, Nova Anshari, Muhammad Rifqi Anunggilarso, Luky Rafi Arief Rachman Hakim Arsi, Primandani Astrida, Deuis Nur Aunillah, Puteri Johar Awal Rozaq, Hasri Akbar Awali, Uston Azhar Andika Putra Azzahra, Delia Oktaviana Bagus Adhi Kusuma Baihaqi, Wiga Maulana Busyro, Muhammad Damayanti, Wenti Risma Darmo, Cahyo Pambudi Dermawan, Riky Dimas Dhanar Intan Surya Saputra Dias Ayu Budi Utami, Dias Ayu Budi Dwi Krisbiantoro, Dwi Elistiana, Khoerotul Melina Fadilah, Alif Nur Fandy Setyo Utomo Firmanda, Reza Arief Hellik Hermawan Hendra Marcos Hendra Marcos, Hendra hidayatulloh, hanif Ikhsan, Ali Nur Ilham, Fatah Irma Damayanti Irma Darmayanti Katiandhago, Bryan Jerremia Khoerida, Nur Isnaeni Khofiyah, Salma Ngarifatul Kholifah Dwi Prasetyo Kartika, Nur Kisma, Atmaja Jalu Narendra Kusuma, Bagus Adhi Kusuma, Velizha Sandy Lestari, Vika Febri Marlita, Reva Merliani, Nanda Nurisya Mohammad Imron Muflikhatun, Siti Mustolih, Akhmad Nandang Hermanto Nasar Ghanim, Nadif Nuraini , Rema Sekar Nurul Hidayati Pramudya, Reyvaldo Shiva Prasetya, Eko Budi Prasetyo Kartika, Nur Kholifah Dwi Prastyadi Wibawa Rahayu Prayoga, Iphang Primandani Arsi Purba, Mariana Ramadani, Nevita Cahaya Riandini, Dini Riyanto Riyanto Rizki Wahyudi Rofiqoh, Dayana Rohman, M. Abdul Romadoni, Nova Salma Rujianto Eko Saputro Sabaniyah, Arbangi Puput Sadewo, Rizki Salsabiela, Ayuni Saputra, Dhanar Sari, Rida Purnama Sarmini Sarmini Satrio Nugroho, Chendri Irawan Septiana Putri, Refida Sugiarti Sugiarti Suhaman, Jali Susanto, Wachyu Dwi Syabani, Amin Syamsiar, Syamsiar Tarwoto, Tarwoto Tri Astuti Triana, Latifah Adi Umma, Rofiqul Utami, Melida Ratna Utomo, Anwar Tri V, Jay Wahyu, Herta Tri WIDI LESTARI, TRI ENDAH Widiawati, Neta Tri Yunita, Ika Romadhoni