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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Perfecting a Video Game with Game Metrics Telematika IJIIS: International Journal of Informatics and Information Systems Jurnal Pengabdian Mitra Masyarakat (JPMM)
Uswatun Hasanah
Amikom University Purwokerto, Indonesia
Computer Science & IT Control & Systems Engineering Education Medicine & Pharmacology Social Sciences Other

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A scoring rubric for automatic short answer grading system Uswatun Hasanah; Adhistya Erna Permanasari; Sri Suning Kusumawardani; Feddy Setio Pribadi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.11785

Abstract

During the past decades, researches about automatic grading have become an interesting issue. These studies focuses on how to make machines are able to help human on assessing students’ learning outcomes. Automatic grading enables teachers to assess student's answers with more objective, consistent, and faster. Especially for essay model, it has two different types, i.e. long essay and short answer. Almost of the previous researches merely developed automatic essay grading (AEG) instead of automatic short answer grading (ASAG). This study aims to assess the sentence similarity of short answer to the questions and answers in Indonesian without any language semantic's tool. This research uses pre-processing steps consisting of case folding, tokenization, stemming, and stopword removal. The proposed approach is a scoring rubric obtained by measuring the similarity of sentences using the string-based similarity methods and the keyword matching process. The dataset used in this study consists of 7 questions, 34 alternative reference answers and 224 student’s answers. The experiment results show that the proposed approach is able to achieve a correlation value between 0.65419 up to 0.66383 at Pearson's correlation, with Mean Absolute Error (????????????) value about 0.94994 until 1.24295. The proposed approach also leverages the correlation value and decreases the error value in each method.
Synonym Measurement Through Semantic Similarity Using the SOC-PMI Method Uswatun Hasanah; Bambang Pilu Hartato; Mitra Yulianti; Saeful Haq Faruqi
Telematika Vol 13, No 1: Februari (2020)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v13i1.941

Abstract

Abstract: Measurement of synonyms can be an important task in measuring word similarity. This work cannot be done syntactically, but must dig deeper about its semantics. Semantic relations can be anything, such as synonyms, antonyms, hyponymy, homonymy and polysemy. This research works on finding synonym values using the Second Order Co-occurrence Pointwise Mutual Information (SOC-PMI) method. The data used are 30 questions on the TOEFL exam. Each question consists of one word as a question and four reference answers as alternative answers. The results show very low accuracy (30%) since there are only 9 out of 30 answers that actually show the synonym. In addition, the LCS method was also tested to get a character-based similarity score. LCS method is able to achieve a higher similarity score of 43.33%. Finally, the idea of hybrid method by combining character-based and semantic-based methods can be considered in longer words to produce a fairer similarity score.Abstrak: Pengukuran sinonim dapat menjadi pekerjaan yang penting dalam mengukur kemiripan kata. Pekerjaan ini tidak dapat dilakukan secara sintaksis, tetapi harus dilakukan dengan menggali lebih dalam tentang semantiknya. Hubungan semantik dapat berupa apa saja, seperti sinonim, antonim, hiponim, homonim, dan polisemi. Penelitian ini berusaha untuk menemukan nilai-nilai sinonim menggunakan metode Second Order Co-occurrence Pointwise Mutual Information (SOC-PMI). Data yang digunakan adalah 30 pertanyaan pada ujian TOEFL. Setiap pertanyaan terdiri dari satu kata sebagai pertanyaan dan empat jawaban referensi sebagai jawaban alternatif. Hasil menunjukkan nilai akurasi yang sangat rendah (30%) karena hanya ada 9 dari 30 jawaban yang benar-benar menunjukkan sinonim. Selain itu, metode LCS juga diuji untuk mendapatkan skor kemiripan berdasarkan karakternya. Metode LCS mampu mencapai skor kemiripan yang lebih tinggi yaitu 43,33%. Akhirnya, gagasan metode hybrid dengan menggabungkan metode berbasis karakter dan metode berbasis semantik semantik dapat dipertimbangkan untuk kata-kata yang lebih panjang agar menghasilkan skor kesamaan yang lebih adil.
Dataset Splitting Techniques Comparison For Face Classification on CCTV Images Ade Nurhopipah; Uswatun Hasanah
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 4 (2020): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.58092

Abstract

The performance of classification models in machine learning algorithms is influenced by many factors, one of which is dataset splitting method. To avoid overfitting, it is important to apply a suitable dataset splitting strategy. This study presents comparison of four dataset splitting techniques, namely Random Sub-sampling Validation (RSV), k-Fold Cross Validation (k-FCV), Bootstrap Validation (BV) and Moralis Lima Martin Validation (MLMV). This comparison is done in face classification on CCTV images using Convolutional Neural Network (CNN) algorithm and Support Vector Machine (SVM) algorithm. This study is also applied in two image datasets. The results of the comparison are reviewed by using model accuracy in training set, validation set and test set, also bias and variance of the model. The experiment shows that k-FCV technique has more stable performance and provide high accuracy on training set as well as good generalizations on validation set and test set. Meanwhile, data splitting using MLMV technique has lower performance than the other three techniques since it yields lower accuracy. This technique also shows higher bias and variance values and it builds overfitting models, especially when it is applied on validation set.
Analysis of Data Mining Using K-Means Clustering Algorithm for Product Grouping Mohammad imron; Uswatun Hasanah; Bahrul Humaidi
International Journal of Informatics and Information Systems Vol 3, No 1: March 2020
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v3i1.3

Abstract

Rizki Barokah Store is one of the stores that every day sell a variety of basic materials of daily necessities such as food, drinks, snacks, toiletries, and so on. However, some problems occur in the Rizki Barokah Store is often a build-up of product stocks that resulted in the product has expired. This is due to an error in making decisions on the product stock. In addition to these problems, with the amount of sales data stored on the database, the store has not done data mining and grouping to know the potential of the product. Whereas data-processing technology can already be done using data mining techniques. To overcome the period of the land, the technique used in data mining with the clustering method using the algorithm K-means. With the use of these techniques, the purpose of this research is to grouping products based on products of interest and less interest, advise on the stock of products, and know the products of interest and less demand.
Pelatihan Teknis Penggunaan Aplikasi PeduliLindungi Guna Melacak Penyebaran COVID-19 Fiby Nur Afiana; Ika Romadoni Yunita; Luzi Dwi Oktaviana; Uswatun Hasanah
Jurnal Pengabdian Mitra Masyarakat (JPMM) Vol 2, No 2: Oktober (2020)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (480.713 KB) | DOI: 10.35671/jpmm.v2i2.999

Abstract

One of the four strategies presented by the Covid-19 Task Force for the Acceleration of Handling to strengthen physical distancing policy as a basic strategy for overcoming the spread of Covid-19 is the tracing of positive cases. Tracing anyone who has contact with patients if done manually requires quite a long time and within that time the virus could have spread very quickly. The Care Concern application issued by the government through the Ministry of Communication and Information Technology (Kominfo) can do tracing quickly through the recording of GPS and Bluetooth that are active on android devices. Through this dedication, participants can understand how technology can help the spread of the covid-19 virus by using the Care Protect Application to trace contacts (tracing), see how the condition of the surrounding environmental zones so that they can take anticipatory and preventive actions. Contact tracing is very helpful in controlling the spread of Covid-19 with a number of precautions taken by the local government if anyone who has contact with a positive Covid-19 patient is known.
Co-Authors Adhistya Erna Permanasari Bahrul Humaidi Bambang Pilu Hartato Feddy Setio Pribadi Fiby Nur Afiana Ika Romadoni Yunita Luzi Dwi Oktaviana Mitra Yulianti Mohammad imron Nurhopipah, Ade Saeful Haq Faruqi Sri Suning Kusumawardani