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ZK Abdurahman Baizal
Universitas Telkom
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Question Answering Chatbot using Ontology for History of the Sumedang Larang Kingdom using Cosine Similarity as Similarity Measure Rinaldi Jasmi; Z K A Baizal; Donni Richasdy
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4530

Abstract

Information can also be a means of learning for humans. Including information about history because history can be a means of learning for the younger generation to appreciate the nation's culture and build national identity. In the past, the Sumedang Larang kingdom was one of the many kingdoms in West Java, Indonesia, that could be used as much information as a lesson. Technological developments make more and more information available for study. We need the proper means to find the information we need. This study aims to build a Question Answering (QA) system to create a means for the younger generation to be more familiar with the history of the kingdom in the past. The QA system offers an information retrieval system that is easy to access and can immediately provide the answers we need. This QA system was built using ontology as a knowledge base and cosine similarity to determine the similarity between user questions and the dataset. The QA system that has been built is tested by providing a set of questions so that the system's performance can be measured, and the results of system testing get a precision value of 70% and a recall value of 90%.
Question Answering using Ontology for Sumedang Larang History with Support Vector Machine Based on Telegram Bot Erbina Selvia Br Perangin-Angin; Z. K. A Baizal; Donni Richasdy
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4574

Abstract

Technological developments affect many aspects, one of which is historical education. History lessons can shape students' personalities and encourage an interest in historical knowledge. There are many stories from Indonesian history, one of which is the Sumedang Larang Kingdom. The Sumedang Larang Kingdom is one of the Islamic kingdoms in Pasundan. However, not many people know about this kingdom. The millennial generation is technologically advanced, so they can take advantage of technological advances to quickly introduce the history of Sumedang Larang. One of them utilizes the telegram bot using the Application Programming Interface (API), which can connect the system to the telegram platform. In addition, this technology can be used as a history learning attraction using the question answering system (QA). Our research aims to build a QA system that can introduce the history of Sumedang Larang to the millennial generation. Because this system uses ontology knowledge with concepts related to the Sumedang Larang domain, it can focus on the history of Sumedang Larang. Applying the support vector machine (SVM) algorithm to process classification text can make it easier to search for text categories. The test results show the performance of the SVM method with a test size parameter of 0.5, such as 74% and 78%. The performance test results are accuracy scores in the subject category and object classification.
Food and Beverage Recommendation in EatAja Application Using the Alternating Least Square Method Recommender System Elsa Rachel Dementieva; Z K A Baizal; Donni Richasdy
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4549

Abstract

EatAja is a startup in Indonesia that provides a mobile application-based food and beverage ordering solution for restaurants. The EatAja application uses transaction data to recommend food and beverage menus to customers. Previous studies have developed recommender systems using the Apriori and Collaborative Filtering methods. However, there are shortcomings in the recommendation system using both methods, i.e., the lack of personalization factors and low scalability. The learning method with matrix factorization can overcome the problem. In this study, we improve the food and beverage product recommender system in the EatAja application using the Alternating Least Square (ALS) matrix factorization method on Apache Spark. We will compare the results of the recommender system using the ALS method with the Collaborative Filtering method. The comparison uses the Mean Absolute Error (MAE) evaluation method. The results showed that the MAE value decreased by 0.07 with the ALS Matrix factorization method.
News Recommender System Based on User Log History Using Rapid Automatic Keyword Extraction Inggrid Resmi Benita; Z K A Baizal
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4554

Abstract

There are many ways to find information; one of them is reading online news. However, searching for news online becomes more difficult because we should visit multiple platforms to find information. Sometimes, the recommended news doesn't match the user's interests. In many prior works, news recommendations are based on trending. Thus, the recommended news may not necessarily match the user's interests. To overcome this, we built a web-based news recommender system to make it easier for users to find news. We use the Rapid Automatic Keyword Extraction (RAKE) method in the recommendation process because this method can recommend news based on user preferences by utilizing user history logs. RAKE converts the title and content of the news into vector representation using Count vectorizer and applies the Cosine Similarity function to compare similarities between news. The test results show that the average performance of our proposed system is 90.8%, this accuracy outperforms earlier systems in terms of performance by the purpose of the recommender system, i.e., diversity, novelty, and relevance.
Chatbot-Based Movie Recommender System Using POS Tagging Muhammad Alwi Nugraha; Z K A Baizal; Donni Richasdy
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.1908

Abstract

The movie recommender system is a technology designed to make it easier for users to provide recommendations quickly and among the many pieces of information. Because the number of movies is huge, it causes a person to be confused in determining the choice of the movie to watch. Many movie recommending systems have been developed, but users cannot interact intensively. Based on these problems, we developed a chatbot-based conversational recommender system, which can interact intensively with the system. The developed chatbot uses normal language handling to permit the framework to comprehend what the user enters as natural language. POS Tagging is used to find tags in the form of movie titles with patterns in the POS Tagging model. However, the algorithm of those used on POS Tagging does not pay attention to the sentence entity, so the predicted title must correspond to the provisions of POS Tagging. Multinomial Naive Bayes looks for similarities of user input to datasets on intents. The dataset with the highest probability value or almost equal to the sentence entered by the user can be used as a response to user input. The test results of the chatbot application showed that the match rate between response and user input was 89.1%. Thus, the developed chatbot can be used well to provide practical and interactive movie recommendations.
Question Answering System Using Semantic Reasoning on Ontology for The History of The Sumedang Larang Kingdom Silvia Atika Anggrayni; Z K A Baizal; Donni Richasdy
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.1910

Abstract

Studying history can train us to understand the sequence of events and increase a sense of nationalism in the younger generation. However, today's young generation views studying history as boring and unimportant. Studying history is considered boring because it has the stereotype of having to learn by reading long writings in books. Therefore, in this study, a Question Answering System (QAS) was built using an ontology to get historical information and get to know the culture. With QAS, users don't have to read long sentences and spend a lot of time searching for historical information, users can also ask questions in natural language without having to pay attention to sentence structure. The ontology was chosen to be able to build a knowledge base on the historical domain and SPARQL was used to find answers in the ontology. The construction of this system is expected not only to help introduce the history of the Sumedang Larang Kingdom but also to be able to introduce the attraction of cultural tourism in Indonesia, especially the Sumedang Larang Kingdom. The results of the evaluation with the system accuracy test showed a result of 87%.
Risk identification for early warning of bleeding among mothers during childbirth Sulastri Sulastri; Tongku Nizwan Siregar; Muhammad Adlim; Hasanuddin Hasanuddin; Gholib Gholib; Lilis Suryani
International Journal of Public Health Science (IJPHS) Vol 12, No 1: March 2023
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v12i1.22299

Abstract

The study was conducted using the observational method. It assessed blood loss using a calibrated measuring cup every 15 minutes in the first hour after delivery and every 30 minutes for the next hour. The results of the analysis showed that the modelling of early warning identification in laboring mothers is influenced by the age and weight of the mother, which is at a significance of 10%. A major warning sign is an increase in blood pressure rate in the third stage of labor which begins 15 minutes from the start of bleeding, and is categorized as dangerous when the blood volume reaches 600 mL. Therefore, every mother in labor must be monitored regularly and continuously and early warning signs must be taken into account. There is no safe time in cases of blood loss. It is very important to identify the risks in a timely manner to identify the source of bleeding so that it can be handled quickly and appropriately in order to prevent complications and maternal death due to postpartum haemorrhage (PPH). Implication, effective and optimal identification in clinical practice should be evidence-based in order to better determine whether or not intervention is needed to prevent blood loss after childbirth.
The Effectiveness of the Video Assistant Poblem Based Learning Model to Improve Mathematics Problem Solving Ability and Student Independence in MTs Al Jamiyatul Washliyah Tanjung Morawa Academic Year 2021/2022 Dwi Maya Sari; Rita Destini
International Journal of Educational Research Excellence (IJERE) Vol. 1 No. 1: First Published June 2022
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (235.816 KB) | DOI: 10.55299/ijere.v1i1.96

Abstract

This study aims to: (1) To find out the video-assisted Problem Based Learning model in improving mathematical problem solving abilities in class VII MTs students. Al-Jamiyatul Washliyah Tanjung Morawa. (2) To find out the effectiveness of the video-assisted Problem Based Learning model in increasing learning independence in class VII MTs students. Al-Jamiyatul Washliyah Tanjung Morawa. This research uses mixed methods (Mixed Methods). This research was conducted in MTs School. Al-Jamiyatul Washliyah Tanjung Morawa with 30 students. The instruments used in this research are mathematical problem solving ability tests, learning independence questionnaires and interviews. The results of this study indicate that: (1) Video-assisted Problem Based Learning model is effective in improving students' mathematical problem solving abilities. (2) Video-assisted Problem Based Learning Model is effective in increasing students' mathematical learning independence.
The Portrait of Challenges in Teaching English to Young Learners: A Case Study in an Indonesian Islamic School Canda Ayu Arum Pertiwi; Mutmainnah Mustofa; M Faruq Ubaidillah; Sugeng Hariyanto
Journal of English Language Teaching and Linguistics Journal of English Language Teaching and Linguistics, 7(3), December 2022
Publisher : Yayasan Visi Intan Permata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21462/jeltl.v7i3.892

Abstract

Teaching English to students with no prior knowledge, a different first language, and varied characters is challenging. This research is a case study design that focused on the teachers’ perceptions of teaching English to young learners situated in one of the Islamic schools in Malang, Indonesia. The participants involved were six English teachers at the chosen school. A qualitative approach was employed in this study.  Data were generated through interviews. Findings suggest that the participating teachers encountered multiple challenges in their teaching enactment, such as (1) non-English prior knowledge, (2) lack of motivation, (3) negative perceptions of the English language, (4) time constraints for studying English, (5) insufficient teaching and learning devices, (6) messy classroom conditions, and (7) speaking anxiety. With some help from others, teachers’ creativity, and some collaborations with other teachers, the teaching and learning process can run conditionally.
Collaborative Filtering with Dimension Reduction Technique and Clustering for E-Commerce Product Daffa Barin Tizard Riyadi; Z K A Baizal
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5538

Abstract

The rapid development of internet users over the last decade has led to an increase in the use of electronic commerce (e-commerce). The existence of a recommender system influences the success of e-commerce. Collaborative Filtering (CF) is one of the most frequently used recommender system methods. However, in real cases, sparsity problems generally occur. This is generally caused because only a small number of users give ratings to items. In this study, we propose the combination of clustering and dimension reduction methods on the Amazon Review Data to overcome the sparsity problem. The clustering method with K-Means is used to group users based on item preferences. Meanwhile, we used Singular Value Decomposition (SVD) for dimension reduction to improve the performance of the recommender system in sparse data. The results show that the combination of SVD and K-Means is successful in predicting ratings with an RMSE value of less than 2, significant performance increase compared to previous study. The use of SVD is proven to be able to overcome sparsity, with a decrease in RMSE of 9.372%.
Co-Authors Abdul Muqit Abdullah Helmy Ade Kosasih Ade Romadhon Ade Sukma Adisti Rastosari Aditya, Naufal Adri Nur Fajari Afriani Sandra Agung Toto Wibowo Agus Alim Abdullah Ahmad Lubis Ghozali Akbar, Yoan Amri Alam Rahmatulloh Albi Fitransyah Ali, Muhammad Haidir Allismawita Allismawita amnah amnah An Fauzia Rozani Syafei Ana Fitriana Poerana Andiety, Rich Andini, Andini Andjioe, Oscar Rynandi Angelina Sagita Sastrawan Anindya, Widya Dara Aniq A Rahmawati Aniq A. Rahmawati Anisa Herdiani Annisa Cahya Anggraeni Annisa Cahya Anggraeni Antonius Randy Arjun Ardi Ardi Ari Satrio Arie Lasaprima Arifa Nur Hasanah Aryadi Pramarta Aryanta, Rafi Rizkya Ayunda Farah Istiqamah Budiarti, L Endang Burhanuddin Bahar Cahya, Anindya Cahyani, Hilda Canda Ayu Arum Pertiwi Christhofer Laurent Juliant Cut Sri Maulina D. Novia Daffa Barin Tizard Riyadi Damayanti, Elok Dana Sulistyo Kusumo Danang Triantoro Murdiansyah Darmawan, Faiha Adzra Dede Tarwidi Dedi Romli Triputra Dendy Andra Deni Novia Dessy Abdullah Devi Pratami Dhiva Rezzy Pratama Diah Mahmuda Diah Pudi Langgeni Didik Tri Setiyoko Didit Adytia Djoko Wahyono Donni Richasdy Dreyfus, Shoshana Dwi H Widyantoro Dwi Maya Sari Dwinda Tamara Edy Tandililing Eka Ismantohadi Elly Roza Elsa Rachel Dementieva Erbina Selvia Br Perangin-Angin Erliansyah Nasution Erni Masdupi Erwin B. Setiawan Erwin Budi Setiawan Esa Alfitrassalam Evitayani Evitayani Fadillah, Ichsan Alam Fatimah Nurhayani Fatimatus Zahroh Favian Dewanta Ferawati Ferawati Fernandy Marbun Ferry Lismanto Syaiful Firmansyah Firmansyah Fitriani Mangerangi Gentra Aditya Putra Ruswanda Gesit Tabrani Ghazi Ahmad Fadhlullah Gholib Gholib Grace Yohana Grace Yohana Gusti Ayu Marheni Gustina Lubis Hafid Ahmad Adyatma Hakim, Lukman Nur Hary Yuswadi Hasanuddin Hasanuddin Hasanusi, Mohammad Helmi Arifin Hendra Naldi Humaizi, Humaizi Humaizi, Humaizi Ichwanul Muslim Karo Karo Ida Ayu Putu Sri Widnyani Igga Febrian Virgiani Ika Arum Puspita Ilham Mujaddid Al Masyriq Imam Sunarno, Imam Ina Rofi’atun Nasihati Indira Adnani Indri Juliyarsi Inggrid Resmi Benita Intan Dwi Novieta, Intan Dwi Irfan Darmawan Irhas Jaya Iryanto Iryanto Iut Tri Utami Izzatul Ummah Jaka E. Sembodo Jamhari Jamhari Jamsari Jamsari Jaya, Irhas Jayana Citra Agung Pramu Putra Joni Dwi Pribadi Kalsum Kalsum Kemas M Lhaksmana Kemas M. Lhaksmana Kemas Muslim Lhaksmana Khaidarmansyah Khairiah, Khairiah Khamim, Khamim Khasrad . Khatimah, Ummu Husnul Khoirunnisaa’ Khoirunnisaa’ Khusnul Diana Kun Mustain Kusnadi, Kusnadi Lie Othman Lilis Suryani Lisa Rahmi Litasari Widyastuti, Litasari Liviandra, Monica Loiz, Andhika Lubis, Putri Handayani Lutfi Ambarwati M. Duskri M. Naufal Mu'afa M. Qadrian M. Rayhan Hakim Mahmud Dwi Sulistiyo Mahmud Imrona Mala Nurilmala Mansyur Arif Marayasa, I Nyoman Marendra Septianta Mayasari Mayasari Mella Ismelina Farma Rahayu Miranti Andhita Scantya Mirna Fitrani Misna Ariani Mizanul Kirom Moch Arif Bijaksana Moh Naufal Mizan Saputro Moh Z Mubarok Moh. Mahsus Mudayatiningsih, Sri Muhamad Faishal Irawan Muhamad Hafidh Nofal Muhammad Adlim Muhammad Agus Muljanto Muhammad Alwi Nugraha Muhammad Attalariq Muhammad Bilal Rafif Azaki Muhammad Ilham Hafizha Muhammad Ilham Hafizha Muhammad Ridha Anshari Muhammad Zaid Dzulfikar Muhammad, Widi Sayyd Fadhil Mustakim, ' Musthafa Zaki Bahar Mustofa, Mutmainnah Nabila Wardah Zamani Najla Nur Adila Naufal Akbar Hartono Ni Nyoman Sumiasih Ni Wayan Armini Niken Titi Pratitis Ningsih Purba Ningsih, Ayu Oktavia Nirmala Ayu Aryanti Nisa, Intan Khairu Nofal, Muhamad Hafidh Nora. AN, Desri Nungki Selviandro Nur Azlina Nur Jamilah Nur Rahmawati Nur Ulfa Maulidevi Nuraini Lubis Nurfadhlina Mohd Sharef Nurjayanto, Bagus Wicaksono Nurul Ikhsan Okky Brillian Hibrianto Okky Brillian Hibrianto P, Kadek Abi Satria A V Pahrurrobi Pahrurrobi Prasetia, Reza Putra, A. D. A. Putu Harry Gunawan Qisti R Arvianti Rachmi Helfianur Radhiva Hibatullah, Muhammad Rafiuddin, Rafiuddin Rahmat Firdaus Rahmi Wati Raihani Mohamed Rais Rais Ramadhan, Sageri Fikri Ramadhani, Nur Laili Ramanti Dharayani Randika Dwi Maulana Rasyid Ranestari Sastriani Rasbawati, Rasbawati Rayhan M Auliarahman Reinaldo Kenneth Darmawan Rena Feri Wijayanti Restu Aditya Rachman Reza Rendian Septiawan Rezano, Tomi Richo Fedhia Saldhi Rika Afriani Rina Dahlyanti Rinaldi Jasmi Rinita Amelia Risa Tiuria Risfaheri - Riska Padilah Riski Hernando Rita Rismala Rizaldy Arigi Rizky Andrian Rizqi Bayu Aji Robi Amizar Roby Dwi Hartanto Rohmat Gunawan Romy Adzani Adiputra Roseno, Rizky Haffiyan Rr Amanda Pasca Rini, Rr Amanda Pasca Ruh Devita Widhiana Prabowo Rusli, Ridho Kurniawan S. Syamsurizal Sa'diatul Fuadiyah Sahlya Handayati Salam N. Aritonang Sanusi Ibrahim Sarini Vita Dewi Sedyo Mukti, Putri Ayu Sepri Reski Shaufiah . Sigit Budisantoso Silvia Atika Anggrayni Simon He Siti Rohani Sitorus, Angela Tiara Maharani Sri Andayani Sri Melia Suci Aprianti Sukanta Sumaryati Syukur Suyitman Suyitman Syaifuddin Ahrom Syaifuddin Ahrom Syamsul Hadi Tebay, Selvi Teguh Surya Apri Handoyo Theriana Ayu Waskitaning Tyas Thoriq Akhdan, Muh Titi Sumanti Tongku Nizwan Siregar Ufra Neshia Umar Ali Ahmad Urnemi - Urnemi Urnemi Utomo, Muhajir Veritia, Veritia Vici E.H.S. Susilowati Wibowo, Kurnia Drajat Winardhi, Sonny Winardhi, Sonny Wiratama, Arga Kusuma Wiwik Handayani Wizna (Wizna) Wulandari, Dinda Atikah Yani Riyani Yanuar Firdaus Yanuar Firdaus A Yanuar Firdaus A.W. Yesi Chwenta Sari Yoan Amri Akbar Yolani Utami Yudha E. Pratama Yudha Endra Pratama Yuherman Yuherman Yulia Murni Yulia Yellita Yuliant Sibaroni Yulianti Fitri Kurnia Yuliawati Yuliawati Yulisna Gita Hapsari Yundari, Yundari Yusran Khery, Yusran Yusri Dianne Jurnalis Yusza Reditya Murti Zidni Mubarok Zoni Hidayat