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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) BERKALA FISIKA SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Jurnal Penelitian dan Pengembangan Pendidikan YOUNGSTER PHYSICS JOURNAL Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Geoplanning : Journal of Geomatics and Planning Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Scientific Journal of Informatics Register: Jurnal Ilmiah Teknologi Sistem Informasi JOURNAL ONLINE OF PHYSICS Jurnal Penelitian Pendidikan IPA (JPPIPA) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control IRJE (Indonesian Research Journal in Education) Journal of Physics and Its Applications Jurnal Sisfokom (Sistem Informasi dan Komputer) JURNAL METEOROLOGI DAN GEOFISIKA Journal of Electronics, Electromedical Engineering, and Medical Informatics Indonesian Journal of Electrical Engineering and Computer Science Jurnal Aisyah : Jurnal Ilmu Kesehatan Journal of Social Research TAKSONOMI Jurnal Ekonomi, Teknologi dan Bisnis Journal of Emerging Science and Engineering Jurnal INFOTEL Sainteknol : Jurnal Sains dan Teknologi
Rahmat Gernowo
Department Of Physics, Faculty Of Science And Mathematics, Diponegoro University, Semarang
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Sistem Informasi Manajemen Pengumpulan dan Pengangkutan Sampah Padat dengan Efisiensi Rute Menggunakan K-Means Clustering dan Travelling Salesman Problem Munji Hanafi; Budi Warsito; Rahmat Gernowo
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 12, No 2 (2022): Volume 12 Nomor 2 Tahun 2022
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol12iss2pp106-115

Abstract

The increasing population growth and rapid urbanization have resulted in large amounts of solid municipal waste (SMW). Nowadays, the problem of waste management is a problem that is being experienced by every country in the world. As a result, implementing efficient waste management strategies is increasingly needed. The collection and transportation of solid waste is the most important thing to pay attention to in waste management efficiency to reduce the costs of collecting and transporting solid waste. The research started by collecting data and interviewing the environmental services of Semarang City about the waste transportation system in Semarang City. The results of the data and interviews will then be used as a reference for the system analysis to be made. Then proceed with designing information systems. After that, the information system was developed by applying the Traveling Salesman Problem (TSP) method using a heuristic in the form of K-means Clustering. With the help of OR-Tools, TSP completion does not require node distance, just inputting the coordinates of each node. The study closed system testing. This research proposes a new approach to solving TSP. First is the process of assembling nodes into several clusters. Then, look for the shortest route in each cluster. The research resulted in 21 routes in 16 corridors to transport waste in Semarang City, presented on a map on a web-based Information System as Decision Support System (DSS). The comparison of the methods shows that TSP is the most suitable for this case.
Sentiment Analysis Naive Bayes Method on SatuSehat Application Shahmirul Hafizullah Imanuddin; Kusworo Adi; Rahmat Gernowo
Jurnal Penelitian Pendidikan IPA Vol 9 No 7 (2023): July
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i7.4054

Abstract

The SatuSehat application is an application that provides health services to users. This application is a development of the PeduliLindungi application which is used to handle vaccination history in the new normal era. Therefore, it is important to classify user reviews into positive and negative sentiments using the Naïve Bayes method. The use of this method because it can produce a model that is quite accurate and effective. The results of data collection in this study were 25,000 of which 18,359 were negative and 6,641 were positive. The results of the Naïve Bayes accuracy test are 97% with negative sentiment results, namely precision has a value of 98%, recall has a value of 98% and f1-score has a value of 98%, while positive sentiment results, namely precision has a value of 94%, recall has a value of 94 % and f1-score has a value of 94%. This study aims to classify user reviews of the SatuSehat application into positive and negative sentiments and assess the performance of the Naïve Bayes method regarding public opinion on the use of the SatuSehat application based on reviews from the Google Playstore application.
Data Augmentation for Hoax Detection through the Method of Convolutional Neural Network in Indonesian News Atik Zilziana Muflihati Noor; Rahmat Gernowo; Oky Dwi Nurhayati
Jurnal Penelitian Pendidikan IPA Vol 9 No 7 (2023): July
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i7.4214

Abstract

The concept of hoax or fake news refers to the intentional spread of false information on social media that aims to confuse and mislead readers to achieve an economic or political agenda. In addition, the increasingly diverse and numerous actors in the field of news writing and dissemination have led to the creation of news articles that need to be recognized whether they are credible or not. Furthermore, hoax can harm the social and political aspects of Indonesian society. Central Connecticut University released a study entitled The World's Most Literate Nations in 2016, where Indonesia ranked 60th out of 61 countries, indicating that Indonesian media literacy still needs to improve in critically evaluating information and distinguishing between fake news and valid news. Based on this description, the research will create the Synonym-Based Data Augmentation for Hoax Detection using the Convolutional Neural Network (CNN ) method and Easy Data Augmentation (EDA). This research resulted in an accuracy of 8,.81, indicating that it can be stated to be accurate in detecting hoax news
Sentiment Analysis on Satusehat Application Using Support Vector Machine Method Shahmirul Hafizullah Imanuddin; Kusworo Adi; Rahmat Gernowo
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 5 No 3 (2023): July
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeemi.v5i3.304

Abstract

Sentiment analysis is important in language processing and machine learning. SVM is proven to classify positive and negative sentiments with high accuracy effectively. SatuSehat application provides users with various health services and medical information, previously known as the PeduliLindungi Application. Once, this application was used to handle vaccination history used in the new normal era. Along the way, many problems arose due to the immaturity of the application after it was launched, which resulted in many user reviews being given through the Google Play Store application. Therefore, this study aims to determine SVM's performance in classifying user reviews of the SatuSehat application into positive and negative sentiments and to show visualization to find out the most frequent words from user reviews. Based on the research results, 25,000 data were divided into 18,359 negative class data and 6,641 positive class data. At the SVM classification stage, it produces a negative sentiment of 73.4% and a positive sentiment of 26.6%. In addition, the results of the SVM accuracy test obtained a result of 91% with a positive sentiment, namely having a precision test of 92%, a recall of 71%, and an f1-score of 80%, while for negative sentiment, namely having a precision test of 90%, a recall of 98% and f1-score of 94%. The visualization results found that the topics often appearing in positive reviews are good and sometimes great. In contrast, the negative reviews are update, difficult, strange, login, and bug.
Sistem Penilaian Jawaban Singkat Otomatis pada Ujian Online Berbasis Komputer Menggunakan Algoritma Cosine Similarity Dedy Kurniadi; Rahmat Gernowo; Bayu Surarso; Adi Wibowo; Budi Warsito
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 2 (2023): Volume 9 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i2.66934

Abstract

Penggunaan teknologi di bidang pendidikan sekarang ini sedang trending ke arah penilaian secara otomatis, namun penilaian secara otomatis ini memiliki permasalahan yaitu belum bisa mengkoreksi jawaban teks singkat secara otomatis, selain itu pada saat ini juga belum tersedia platform yang bisa mengkoreksi jawaban singkat secara otomatis, penilaian jawaban teks singkat ini membutuhkan waktu koreksi yang lama dan hasil penilaian yang tidak konsisten jika koreksi dilakukan oleh manusia, pada penelitian ini diusulkan sistem yang mampu mengkoreksi ujian peserta didik pada bagian jawaban singkat secara otomatis atau disebut dengan Automated Short Answer Grading (ASAG) dengan menggunakan metode cosine similarity, tahapan yang dilakukan adalah melakukan ekstraksi pada dua variabel inputan yaitu teks pada jawaban peserta didik dan teks pada kunci jawaban yang dilakukan dengan ekstraksi teks casefolding, tokenizing, stopword removal, setelah tahapan tersebut dilakukan kemudian dihitung nilai similarity antara kunci jawaban ujian dengan jawaban peserta didik apakah jawaban peserta didik sama dengan kunci jawaban atau tidak, dengan menggunakan skor yang dinilai otomatis menggunakan sistem, dihasilkan similarity antara jawaban peserta didik dengan kunci jawaban rata-rata sebesar 85,4%, untuk menguji korelasi koreksi jawaban peserta didik dengan sistem dan koreksi yang dilakukan oleh manusia maka dilakukan uji korelasi antara hasil penilian yang dilakukan oleh sistem dengan hasil penilaian yang dilakukan oleh manusia (instruktur) dengan menggunakan kendall’s w value menghasilkan nilai w antara instruktur 1 dengan sistem sebesar 0,885 dan instruktur 2 dengan sistem sebesar 0,883 dengan nilai chi square sebesar 135,4 dan 133,8 dengan p sebesar 0,0001, hasil tersebut menunjukkan ASAG memiliki korelasi yang tinggi dan sistem ASAG ini bisa melakukan penilaian secara otomatis.
Ontology learning from object-relational mapping metadata and relational database Agus Sutejo; Rahmat Gernowo; Michael Andreas Purwoadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 2: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i2.pp1116-1125

Abstract

Ontologies play an important role in representing the semantics of data sources. Building an ontology as a representation of domain knowledge from available data sources is not a simple process, particularly when dealing with relational data, which remains prevalent in existing knowledge systems. In this study, we create an ontology from a relational database using object-relational mapping (ORM) metadata as additional rules for mapping. Our method comprises two main phases: ontology schema construction using ORM metadata and the generation of ontology instances from the relational database. During the initial phase, we analyzed the ORM metadata to map it to an resource description framework schema (RDF(S))-OWL representation of the ontology. In the subsequent phase, we applied mapping rules to convert the relational database (RDB) data into ontological instances, which are then represented as RDF triples. Using ORM metadata, we enhance the accuracy of the resulting ontology, particularly in terms of extracting concepts and hierarchical relationships. This study contributes to the field of ontology learning by showcasing a novel approach that leverages ORM metadata to create ontologies from relational databases.
Determining community happiness index with transformers and attention-based deep learning Wicaksana, Hilman Singgih; Kusumaningrum, Retno; Gernowo, Rahmat
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1753-1761

Abstract

In the current digital era, evaluating the quality of people's lives and their happiness index is closely related to their expressions and opinions on Twitter social media. Measuring population welfare goes beyond monetary aspects, focusing more on subjective well-being, and sentiment analysis helps evaluate people's perceptions of happiness aspects. Aspect-based sentiment analysis (ABSA) effectively identifies sentiments on predetermined aspects. The previous study has used Word-to-Vector (Word2Vec) and long short-term memory (LSTM) methods with or without attention mechanism (AM) to solve ABSA cases. However, the problem with the previous study is that Word2Vec has the disadvantage of being unable to handle the context of words in a sentence. Therefore, this study will address the problem with bidirectional encoder representations from transformers (BERT), which has the advantage of performing bidirectional training. Bayesian optimization as a hyperparameter tuning technique is used to find the best combination of parameters during the training process. Here we show that BERT-LSTM-AM outperforms the Word2Vec-LSTM-AM model in predicting aspect and sentiment. Furthermore, we found that BERT is the best state-of-the-art embedding technique for representing words in a sentence. Our results demonstrate how BERT as an embedding technique can significantly improve the model performance over Word2Vec.
The Potential of Virtual Reality Technology in Children's Learning Success Andryani, Ria; Gernowo, Rahmat; Negara, Edi Surya
Indonesian Research Journal in Education |IRJE| Vol. 8 No. 1 (2024): IRJE |Indonesian Research Journal in Education
Publisher : Universitas Jambi, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/irje.v8i1.36961

Abstract

Learning technology for children often does not have a positive impact on improving children's learning abilities and achievements. So that an appropriate approach is needed for the development of learning technology for children. The article examined the application and implications of the success of virtual reality-based learning for children from the perspective of human-computer interaction. This study used a literature study method from previous scientific publications regarding the potential of virtual reality technology for children's learning success. This literature review was conducted using an exploratory approach. The results of the literature study showed that various studies had been conducted in this domain, the main direction in development is the user-centered design and participatory design approach with the principles of child-computer interaction (CCI).  
An insight from homogeneity testing of long-term rainfall datasets over East Java, Indonesia Mulyanti, Heri; Istadi; Gernowo, Rahmat
Journal of Emerging Science and Engineering Vol. 2 No. 2 (2024)
Publisher : BIORE Scientia Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/jese.2024.e23

Abstract

Robust, reliable, and trustworthy ground observation datasets are the preliminary requirement for assessing the impact of climate change over regions. Principal testing to assess the quality of ground observation rely on the missing data and homogeneity result. The study used 40 years of monthly rainfall documented from different topographical features in the monsoonal region of East Java, Indonesia. The test included annual rainfall, early rainy season (October-November-December), and primary rain season (January-February-March). The homogeneity of rainfall determined by absolute technique: Pettitt’s test, the Standard Normal Homogeneity Test, the Buishand Rank Test, and the von Neumann Ratio. Among the time series, October-November-December observation results in better homogeneity. However, the rainfall datasets during primary rainy season showed the worst homogeneity. By performing annual and seasonal homogeneity test from 67 rainfall stations: 5 stations out of data length required, 5% stations ‘rejected’, 11% ‘suspect’, 11% ‘doubtful’, and 73% were ‘trusted’. Therefore, a total of 45 stations can be used as metadata for relative comparison and 7 stations can be considered to be useful for analysis despite ‘doubtful’. The remaining 10 stations need careful consideration to be used for future water management.  Change point detected particularly between the year of 1997 through 2000. Pettitt’s test has outstanding results in the case of extreme climatic anomaly, but less sensitive of continuous abrupt change. The von Neumann test could detect abnormal data, but was not suitable for datasets containing few extreme values. The insights from homogeneity testing were: a) it is important to remove any outliers in the datasets before conducting homogeneity testing, b) both parametric and nonparametric homogeneity tests should be performed, and c) comparisons should be made with surrounding rainfall stations. Comparison with trusted long-term rainfall data is valuable for stations labeled as ‘doubtful’ or ‘suspect’ to mitigate false detections in individual homogeneity tests. The identified ‘useful’ rainfall data can then serve as reference stations for relative homogeneity tests. These findings suggest that reference stations should be assessed within similar rainfall zones.  
Assessing Vulnerability of Agriculture to Drought in East Java, Indonesia: Application of GIS and AHP Mulyanti, Heri; Istadi, Istadi; Gernowo, Rahmat
Geoplanning: Journal of Geomatics and Planning Vol 10, No 1 (2023)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.10.1.55-72

Abstract

Drought known as ‘silent killer’—unpredictable slow-moving hazard which cause severe damage to people and environment. Since agriculture is the first and foremost sector affected by drought, the risk of crop failure can be minimized by reducing vulnerability. Climate patterns can be considered as systematic conditions which are capable of assigning sensitivity regions to drought. Here, the study employs Oldeman’s Agro Climatic data as physical vulnerability indicator to assess and monitor the vulnerability of agriculture system to drought in East Java. The study used long-term monthly rainfall observation data to generate climatic map accompanied with socio-economic indicators to assess vulnerability of region to drought. Spatial distribution of vulnerability was mapped using Geographic Information Systems (GIS) combined with Analytic Hierarchy Process (AHP). The results show there are five categories of vulnerability to drought: very high, high, moderate, low, and very low based on standardized index. Madura Island, particularly Bangkalan, Sampang, and Sumenep considered as most vulnerable region to drought. In addition, most regions in the north plain of East Java, including Tuban, Lamongan, and Gresik categorized as highly vulnerable to drought. Factors affecting vulnerability are mostly related to drier climate which affect acreage and availability of irrigation. The socio-economic factors likewise smallholder farmers and poverty contribute to rising vulnerability level. South part of East Java, particularly Tulungagung and Blitar Regency was least vulnerable because of appropriate climate which induced to acreage of irrigated land. The study emphasizes the utilizing of Oldeman climate pattern as primary indicator in determining vulnerable regions. Smallholder farmers and poverty causing vulnerability in agriculture emerged as priority for further study. The results can provide new insights into drought management for most vulnerable regions by considering local climatic characteristics.
Co-Authors Adi Wibowo Adiyono, Soni Agus Setyawan Agus Sutejo Agusta Praba Ristadi Pinem Ahmad Lubis Ghozali Aldi Setiawan, Aldi Andryani, Ria Annisa Luthfianti Panular Ardima, Muhammad Basyier Arfriandi, Arief Ari Bawono Putranto Aria Hendrawan, Aria Aries Dwi Indriyanti, Aries Dwi Aris Sugiharto Atik Zilziana Muflihati Noor Bayong Tjasyono H. Kasih Bayu Surarso Beta Noranita Budi Prasetiyo, Budi Budi Warsito Budi Warsito Catur Edi Widodo Cholil, Saifur Rohman Christine Dewi D Febrianty Dafiz Adi Nugroho Dedy Kurniadi Edi Surya Negara Eko Nur Hidayat Eko Sediyono F M Arif Faliha Muthmainah Fauzan Ishlakhuddin Frysca Putti Muviana Ghufron Ghufron Gumay, Naretha Kawadha Pasemah Hengki Hengki Heri Mulyanti Hidayat, Agung Rahmad I. Istadi Ikhthison Mekongga Iryanto Iryanto Ismi Dian Kusumawardhani Isnain Gunadi Istadi I’tishom Al Khoiry Khusnah, Miftakhul Koesuma, Sorja Kuresih, Kuresih Kurnia Adi Cahyanto Kusworo Adi M. Solehuddin Mahrus Ali Michael Andreas Purwoadi Moh Ali Fikri Muchammad A Rofik Mulyani, Esti Munengsih Sari Bunga Munji Hanafi Nabiel Putra Adam, Nabiel Putra Novita Mariana Nuriyana Muthia Sani Nuriyana Muthia Sani Nursamsiah Nursamsiah Oky Dwi Nurhayati Prayitno R. Rizal Isnanto Radini Sinta, Radini Ratih Rundri Utami Rosyalia, Syofi Sakhina, Friska Ayu Setiabudi, Nur Andi Shahmirul Hafizullah Imanuddin Siti Yuniar Pangestu Slamet, Vincencius Gunawan Suryono Suryono Syibli, Mohammad Tri Mulyono Triyono, Liliek Victor Gayuh Utomo Wahyu Jatmiko Wahyul Amien Syafei Wicaksana, Hilman Singgih Widagdo, Krisan Aprian Widiyatmoko, Carolus Borromeus Wulandari, Rosita Ayu Yenny Ernitawati Zaenal Arifin