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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Edukasi dan Penelitian Informatika (JEPIN) KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Indonesian Journal of Information System JSiI (Jurnal Sistem Informasi) Jurnal Informatika: Jurnal Pengembangan IT
Ibnu Santoso
Politeknik Statistika STIS
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education

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Transfer Learning of Pre-trained Transformers for Covid-19 Hoax Detection in Indonesian Language Lya Hulliyyatus Suadaa; Ibnu Santoso; Amanda Tabitha Bulan Panjaitan
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 15, No 3 (2021): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.66205

Abstract

Nowadays, internet has become the most popular source of news. However, the validity of the online news articles is difficult to assess, whether it is a fact or a hoax. Hoaxes related to Covid-19 brought a problematic effect to human life. An accurate hoax detection system is important to filter abundant information on the internet.  In this research, a Covid-19 hoax detection system was proposed by transfer learning of pre-trained transformer models. Fine-tuned original pre-trained BERT, multilingual pre-trained mBERT, and monolingual pre-trained IndoBERT were used to solve the classification task in the hoax detection system. Based on the experimental results, fine-tuned IndoBERT models trained on monolingual Indonesian corpus outperform fine-tuned original and multilingual BERT with uncased versions. However, the fine-tuned mBERT cased model trained on a larger corpus achieved the best performance.
PENGUKURAN TINGKAT KEMIRIPAN DOKUMEN BERBASIS CLUSTER Ibnu Santoso; Lya Hulliyyatus Suadaa
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 6, No 1 (2019)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v6i1.181

Abstract

Document similarity can be measured and used to discover other similar documents in a document collection (corpus). In a small corpus, measuring document similarity is not a problem. In a bigger corpus, comparing similarity rate between documents can be time consuming. A clustering method can be used to minimize number of document collection that has to be compared to a document to save time. This research is aimed to discover the effect of clustering technique in measuring document similarity and evaluate the performance. Corpus used was undergraduate thesis of Politeknik Statistika STIS students from year 2007-2016 as many as 2.049 documents. These documents were represented as bag of words model and clustered using k-means clustering method. Measurement of similarity used is Cosine similarity. From the simulation, clustering process for 3 clusters needs longer preparation time (17,32%) but resulting in faster query processing (77,88%) with accuracy of 0,98. Clustering process for 5 clusters needs longer preparation time (31,10%) but resulting in faster query processing (83,79%) with accuracy of 0,86. Clustering process for 7 clusters needs longer preparation time (45,10%) but resulting in faster query processing (85,30%) with accuracy of 0,98.
PEMBANGUNAN APLIKASI PENGUMPUL BERITA DARI MEDIA DARING MENGGUNAKAN WEB FRAMEWORK CODEIGNITER DAN FLASK Salim Satriajati; Ibnu Santoso
Jurnal Sistem Informasi Vol. 8 No. 2 (2021)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v8i2.3624

Abstract

Advances in information and communication technology today cause access to news to be faster. Gathering news from online media is important to support various interests. News collection also needs to be done automatically to be efficient and effective. So, in this research, a news collector application will be built to get some news from online news site. The application is built using two web frameworks, namely Codeigniter and Flask. In addition, the Python-based Scrapy package is also used as a tool for web crawling and web scraping. Black-box testing is used to evaluate system functionality. Based on the results of black-box testing, it can be concluded that all functions of the news collector application from online news site that have been created can run as expected by the researcher.
Application of Named Entity Recognition via Twitter on SpaCy in Indonesian (Case Study : Power Failure in the Special Region of Yogyakarta) Rizka Maulida Yanti; Ibnu Santoso; Lya Hulliyyatus Suadaa
Indonesian Journal of Information Systems Vol. 4 No. 1 (2021): August 2021
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i1.4677

Abstract

SpaCy is a tool that can efficiently handle Natural Language Processing (NLP) problems, one of which is Named Entity Recognition (NER). NER is used to extract and identify named entities in a text. However, so far SpaCy has not officially released the NER model pre-train for Indonesian. On the other hand, based on the 2019 PLN statistical report, the Province of D.I. Yogyakarta is a province that often experiences power failure and many complaints from the public are found on Twitter related to power failure that occur in the province. This is because there is no research on extracting information related to electrical disturbances and research on NER using SpaCy in Indonesian is still rare. So in this study, information extraction related to power failure in the Province of D.I. will be carried out. Yogyakarta via twitter using Indonesian SpaCy. This study produces good performance results with 95.52% precision calculation, 93.27% recall, and 94.38% f1-score. Then, mapping is carried out based on the location entities contained in tweets related to electrical disturbances. From this process, it was found that the highest number of locations mentioned in the tweet related to power failure came from Sleman Regency, while the lowest number came from Gunung Kidul Regency. Then, the month that experienced the most power failure was March 2020, while the month that experienced the least amount of electricity was July 2020.
Social Network Analysis untuk Identifikasi Pengguna Twitter Berpengaruh pada Topik Bencana Gempa dan Tsunami di Indonesia Ibnu Santoso; Siskarossa Ika Oktora; Siti Muchlisoh; Ernawati Pasaribu
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 1 (2023): Volume 9 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i1.62211

Abstract

Indonesia merupakan negara yang rawan terjadi bencana alam seperti gempa dan tsunami. Seiring dengan perkembangan teknologi, arus informasi mengenai kebencanaan juga mengalir di media sosial seperti Twitter. Penggunaan Twitter dalam kaitannya dengan kebencanaan telah banyak diteliti antara lain untuk penyebarluasan informasi, alat manajemen dan pengurangan resiko, pemantauan aktivitas tanggap darurat, dan lain-lain. Penelitian ini bertujuan untuk mengidentifikasi pengguna twitter berpengaruh khusus untuk topik bencana gempa dan tsunami di Indonesia dengan menggunakan Social Network Analysis (SNA) dengan dan tanpa mempertimbangkan faktor frequency dan engagement. Hasil SNA tanpa mempertimbangkan faktor frequency dan engagement menunjukkan bahwa pengguna Twitter yang dinilai paling berpengaruh pada topik bencana gempa dan tsunami adalah situs berita seperti detikcom dengan influence score sebesar 0,77. Sedangkan jika mempertimbangkan faktor frequency dan engagement menunjukkan bahwa pengguna Twitter yang dinilai paling berpengaruh pada topik bencana gempa dan tsunami adalah akun infoBMKG dengan indeks influence score sebesar 0,63. Berdasarkan hasil penelitian ini ditemukan bahwa BMKG telah berperan penting dalam pemberian informasi mengenai bencana gempa bumi dan tsunami di Indonesia dan mendapatkan kepercayaan luas dari masyarakat yang ditunjukkan dengan adanya engagement yang lebih tinggi dibandingkan akun lainnya.
Rancang Bangun Knowledge Management System Politeknik Statistika STIS Ibnu Santoso; Sanjaya Abdillah Karim
Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 2 (2019): JPIT, Mei 2019
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v4i2.1133

Abstract

STIS Polytechnic of Statistics (PS-STIS) is an institutional unit with high work complexity and density. In carrying out its personnel activities, there is no support system that can be used by employees to store and process knowledge related to their work. This may indirectly lead to ineffective and inefficient work in term of costs, time, and other resources. Job-related knowledge is stored in accordance with the decisions of each employee. When needed, knowledge acquisition becomes slow and knowledge is also prone to be scattered or even lost. In this study, we will discuss about design and development of knowledge management system within the scope of PS-STIS. The focus of this research is related to the integration of the system functions to be able to perform knowledge storage, collaboration, and retrieval. The web-based system built applies the basic principles of Knowledge Management System (KMS). it has pages and permissions in accordance with the interests and responsibilities of users. In this research, we used SDLC development method to build the system and evaluated it using blackbox testing method and Survey Usability Scale (SUS). Result of blackbox testing showed that all function performed like expected and SUS score of 74 showed that system built was acceptable to users.
Co-Authors Amanda Tabitha Bulan Panjaitan Ernawati Pasaribu Lya Hulliyyatus Suadaa Rizka Maulida Yanti Salim Satriajati Sanjaya Abdillah Karim Siskarossa Ika Oktora Siti Muchlisoh