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All Journal Ulul Albab: Jurnal Studi Islam MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) OPSI SMATIKA Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Riset Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Mantik ILKOMNIKA: Journal of Computer Science and Applied Informatics Jurnal Mnemonic International Journal of Advances in Data and Information Systems Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) Jurnal Computer Science and Information Technology (CoSciTech) J-Intech (Journal of Information and Technology) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer
Ririen Kusumawati
Universitas Islam Negeri Maulana Malik Ibrahim Malang
Religion Aerospace Engineering Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Investigation Of Thresholding And Region Merging In Multiple-Choice Answer With 1.3 Mega Pixels Web Camera Ririen Kusumawati, Totok Chamidy ,
SMATIKA Vol 2, No 1 (2012)
Publisher : SMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Development in the field of image processing had been a lot of inventing new technologies. Applications have been developed are character recognition, fingerprint recognition, face recognition, industrial applications, and answer sheet processing. Answer sheet processing applications using a scanner has been widely applied. However, processing the answer sheets using scanners requires special paper. It has been developed processing the answer sheets using a CCD camera. The CCD optical sensors are categorized as the price is quite expensive compared with CMOS. This research aims to obtain the performance of thresholding and region merging in multiple-choice answer with 1.3 mega pixel web camera.The web camera utilize CMOS optical sensor. Thresholding algorithm is used to convert from black-and-white image into a binary image. Thresholding operation classifies the degree of gray value of each pixel into two classes, black and white. Region merging algorithm is a process to incorporate the region that the distance is less than the threshold. Neighboring areas with the most minimum distance are combined. This process continues until the minimum distance between the neighboring region is greater than the threshold.1.3 mega pixels web camera has a low uniformity and also suffers in low light condition.This limitation can be overcome by adding a tolerance on the thresholding process. The system uses Delphi 7programming languages on Windows XP operating system. This research shows that a web camera with alow level of uniformity and suffers in low light condition can retrieve the image data from answer-sheet formwith a precision rate of 96.96%.
MESIN PENCARI AYAT AL QURAN MENGGUNAKAN INEXACT STRING MATCHING Anwar, Agus Sofiyan; Abidin, Zainal; Kusumawati, Ririen
MATICS MATICS (Vol. 4 No. 3
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (512.752 KB) | DOI: 10.18860/mat.v0i0.1569

Abstract

Dengan adanya teknologi digital, al Quran yang dahulu berupa teks manual sekarang sudah dapat dijumpai versi digitalnya. Hal tersebut memicu pengembangan perangkat lunak yang membantu mendapatkan informasi dari teks al Quran, seperti: pencarian ayat berdasarkan kata, frase maupun tema, terjemahan al Quran, tafsir al Quran. Dalam kaitannya dengan pencarian ayat berdasarkan kata atau frase, pada umumnya perangkat lunak yang ada menggunakan teknik exact string matching, yaitu teknik pencarian ayat yang sesuai dengan kata inputan secara tepat. Teknik tersebut sangat sesuai jika pemakai perangkat lunak mengetikkan kata atau frase yang akan dicari dengan benar. Tetapi jika pemakai salah dalam mengetikkan kata inputan, perangkat lunak tidak memberikan solusi atau kemungkinan-kemungkinan dari ayat yang dimaksud. Penelitian ini memadukan teknik stemming dan teknik exact string matching. Stemming berperan sebagai preprocessing untuk exact string matching. Stemming digunakan untuk menemukan kata dasar dari kata berimbuhan dengan cara menghilangkan semua imbuhan baik yang terdiri dari prefiks, sufiks, infiks, konfiks, transfiks, maupun interfiks, namun pada penelitian ini hanya menghilangkan prefiks dan sufiks saja, sebagai contoh jika kata berimbuhan adalah يسطرون maka kata dasarnya adalah سطر. Exact string matching adalah  pencocokan string secara tepat dengan susunan karakter dalam string yang dicocokkan memiliki jumlah maupun urutan karakter yang sama, sebagai contoh kata سطر akan menunjukkan kecocokan hanya dengan kata سطر. Dalam kaitannya dengan pencarian ayat, hasil stemming akan digunakan sebagai kata kunci (keyword) pencarian pada database indeks al Quran. Perpaduan tersebut dimaksudkan untuk meningkatkan hasil pencarian ayat, dan selanjutnya dapat dikategorikan sebagai teknik inexact string matching. Hasil uji coba membuktikan bahwa teknik inexact string matching dapat diimplementasikan untuk mendukung pencarian ayat al Quran dengan nilai F-measure tertinggi pada data uji coba adalah 100 % dan nilai F-measure terendah adalah 66.66 %. Uji coba juga membuktikan bahwa teknik inexact string matching lebih banyak memberikan solusi/kemungkinan dari ayat yang dimaksud dari pada teknik exact string matching. Kata kunci: Arabic Stop Word, Arabic Stemming, Exact String Matching, Inexact Matching
PERINGKASAN TEKS OTOMATIS BERITA BERBAHASA INDONESIA MENGGUNAKAN METODE MAXIMUM MARGINAL RELEVANCE Mustaqhfiri, Muchammad; Abidin, Zainal; Kusumawati, Ririen
MATICS MATICS (Vol. 4 No. 4
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (441.932 KB) | DOI: 10.18860/mat.v0i0.1578

Abstract

Perkembangan teknologi internet berdampak bertambahnya jumlah situs berita berbahasa Indonesia dan menciptakan  ledakan informasi. Hal tersebut menuntut semua informasi bisa diakses dengan cepat dan tidak harus membutuhkan banyak waktu dalam membaca sebuah headline berita.Teknologi peringkas teks otomatis menawarkan solusi untuk membantu pencarian isi berita berupa deskripsi singkat (summary). Penelitian dia­wali dengan lima tahap text preprocessing: pemecahan kalimat,case folding, tokenizing, filtering, dan stemming. Proses selanjutnya menghitung bobot tf-idf, bobot query relevance dan bobot similarity. Ringkasan dihasilkan dari ekstraksi kalimat dengan menggunakan metode maximum marginal relevance. Metode ekstraksi maximum marginal relevance me­rupakan metode yang digunakan untuk mengurangi redudansi dalam perangkingan kali­mat pada multi dokumen. Data uji coba diambil dari surat kabar berbahasa Indonesia on-line sejumlah 30 berita. Hasil pengujian dibandingkan dengan ringkasan manual yang menghasilkan rata-rata recall  60%, precision 77%, dan f-measure 66%.  Kata kunci: peringkasan, text preprocessing, tf-idf, query relevance, similarity, maximum marginal relevance
FUZZY LOGIC METODE MAMDANI UNTUK MEMBANTU DIAGNOSA DINI AUTISM SPECTRUM DISORDER Matondang, Fithriani; Kusumawati, Ririen; Abidin, Zainal
MATICS MATICS (Vol. 4 No. 3
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (163.845 KB) | DOI: 10.18860/mat.v0i0.1571

Abstract

Autism Spectrum Disorder (autis) merupakan gangguan yang dimulai dan dialami pada masa kanak-kanak, yang membuat dirinya tidak dapat membentuk hubungan sosial atau komunikasi yang normal, akibatnya anak tersebut terisolasi dari manusia lain. Perkembangan yang terganggu terutama dalam komunikasi, interaksi sosial dan perilaku. Namun permasalahan yang muncul adalah bagaimana cara mengetahui seorang anak menderita autis atau tidak, begitu juga cara penanganannya yang optimal. Seiring dengan kemajuan teknologi saat ini, berbagai permasalahan yang ada dapat diselesaikan dengan memanfaatkan teknologi. Salah satunya dengan membangun aplikasi sistem pakar untuk mendiagnosa Autism Spectrum Disorder (ASD) dengan fuzzy logic. Input sistem adalah gejala autis, sedangkan output sistem adalah Anak Normal (bukan autis) dan Anak Autis. Proses perhitungan sistem dilakukan dengan 4 tahapan mamdani yaitu: Pembentukan himpunan fuzzy, Implikasi aturan, Komposisi aturan dan Defuzzyfikasi. Dari hasil uji coba sistem, diperoleh data error sebanyak 40 data dari 1287 data uji coba jika dibandingkan dengan hasil uji coba manual. Dari hasil perbandingan uji coba tersebut, diperoleh persentase Error sebanyak 3.11 %, Recall sebesar 69%, dan Presisi sebesar 99%. Kata Kunci : Autism Spectrum Disorder, Fuzzy Logic, Gejala Autis , Mamdani
KECERDASAN BUATAN MANUSIA (ARTIFICIAL INTELLIGENCE); TEKNOLOGI IMPIAN MASA DEPAN Kusumawati, Ririen
ULUL ALBAB Jurnal Studi Islam Vol 9, No 2 (2008): Islamic Studies
Publisher : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1711.382 KB) | DOI: 10.18860/ua.v9i2.6218

Abstract

The computer technology has incredibly increased. Computer software and hardware compete to meet the customer's needs. The research intends to spread the knowledge of information technology, specifically, on the artificial intelligence. The concept of artificial intelligence is adopting and imitating human form, character, and habit which to be implemented on the computer. Using natural approach, the research aims to investigate whether artificial intelligence (AI) will produce the duplication of God's creation. Another important reason of other reseaches on AI is to create a computer which is smart and able to understand human brain working system. Hence, AI has been designed into more practical with faster CPU, cheaper mass memory, and sophisticated software tool. The concept of integrating AI science or collaborative art among sub-fields of technology will stimulate and lead to further AI researches, and it will be an interesting topic for AI researchers for developing AI technology in the future.
Prediction of Service Level Agreement Time of Delivery of Goods and Documents at PT Pos Indonesia Using the Random Forest Method Muhammad Isa Ansori; Ririen Kusumawati; M. Amin Hariyadi
International Journal of Advances in Data and Information Systems Vol. 4 No. 1 (2023): April 2023 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1281

Abstract

This study aimed to predict the service level agreement travel time for goods and document shipments at PT Pos Indonesia (Persero) from the island of Java to the islands of Kalimantan, Sulawesi, Maluku and Papua. This is very important because of the high competition between the logistics industry which is getting faster and faster. The random forest method was chosen because this method is easy to use and flexible for various kinds of data. The prediction results with Random Forest in this study have a good level of accuracy, namely 83.86% of the average 4 trials. This shows that the Random Forest method is the right choice for managing the existing data model at PT Pos Indonesia.
K-Means Binary Search Centroid With Dynamic Cluster for Java Island Health Clustering Muhammad Andryan; Muhammad Faisal; Ririen Kusumawati
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.511

Abstract

This study is focused on determining the health status of each district/city in Java using the K-means Binary Search Centroid and Dynamic Kmeans algorithms. The research data uses data on the health profile of Java Island in 2020. Comparative algorithms were tested using the Davies Bound Index and Calinski-Harabasz Index methods on the traditional k-means algorithm and dynamic binary search centroid k-means. Based on the test, 5 clusters were found in the distribution area, including 11 regions with very high health quality cluster 1, 24 regions with high health quality, 28 regions with moderate health quality, and 28 clusters 4 with low health quality, 45 regions, and cluster 5 with deficient health quality is 11 regions, with the best validation value of DBI 1.8175 and CHI 67.7868. Overall optimization of the dynamic k-means algorithm based on binary search centroid results in a better average cluster quality and a smaller number of iterations than the traditional k-means algorithm. The test results can be used as one of the best methods in evaluating the level of health in the Java Island area and a reference for decision-making in determining policies for related agencies
Hybrid Model Transfer Learning ResNet50 and Support Vector Machine for Face Mask Detection Eko Agus Moh. Iqbal; Ririen Kusumawati; Irwan Budi Santoso
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1297

Abstract

The Covid-19 virus caused a health crisis in Indonesia. This virus is so deadly that it has caused many fatalities which have caused the whole world including the government to pay major attention to the Covid-19 pandemic. The Indonesian government has issued several policies to prevent the spread of this epidemic, one of which is wearing a mask in public places. One approach that is widely used in the field of computer vision is the Convolutional Neural Network (CNN) transfer learning. In this study, Hybrid Model Transfer Learning ResNet50 and SVM with RGB to HSV preprocessing is presented to detect masks in facial images. This model consists of three process components. The first is preprocessing RGB images to HSV, the second component is for Feature Extraction with ResNet50 and the third is mask classification on face images with Support Vector Machine (SVM). From dataset of 7328 training and testing data were carried out. The first model, without preprocessing the image data with ResNet50, produces an accuracy of 86.52%. The second model, the model with preprocessing converts image data from RGB to HSV with ResNet50 resulting in an accuracy of 99.18%. In the third model, without preprocessing with ResNet50 and SVM which has an accuracy of 90.55%. The fourth model, the model with preprocessing converts image data from RGB to HSV with ResNet50 and SVM resulting in an accuracy of 98.36%.
Prediction Model of Revenue Restaurants Business Using Random Forest Erfan Ainul Yakin; Ririen Kusumawati; Usman Pagalay
Indonesian Journal of Artificial Intelligence and Data Mining Vol 6, No 2 (2023): September 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v%vi%i.24984

Abstract

This research was conducted to predict the level of revenue from the Soto Kwali Pak Wasis restaurant business using Machine Learning. The Random Forest method was chosen because it can predict optimal and fast results with low hardware requirements. Prediction Model results using the Random Forest method resulted in an average accuracy value of 75.4% from a combination of 4 experiments. Thus, the Random Forest method is one of the flexible algorithms and is very suitable for predicting revenue in the Soto Kwali Pak Wasis restaurant business because of its good speed, high accuracy, and requires lower costs.
K-Means Binary Search Centroid with Dynamic Cluster for Java Island Health Clustering Muhammad Andryan Wahyu Saputra; Muhammad Faisal; Ririen Kusumawati
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (932.207 KB) | DOI: 10.34288/jri.v5i3.218

Abstract

This study is focused on determining the health status of each district/city in Java using the K-means Binary Search Centroid and Dynamic Kmeans algorithms. The research data uses data on the health profile of Java Island in 2020. Comparative algorithms were tested using the Davies Bound Index and Calinski-Harabasz Index methods on the traditional k-means algorithm and dynamic binary search centroid k-means. Based on the test, 5 clusters were found in the distribution area, including 11 regions with very high health quality cluster 1, 24 regions with high health quality, 28 regions with moderate health quality, and 28 clusters 4 with low health quality, 45 regions, and cluster 5 with poor health quality is 11 regions, with the best validation value of DBI 1.8175 and CHI 67.7868. Overall optimization of the dynamic k-means algorithm based on binary search centroid results in a better average cluster quality and a smaller number of iterations than the traditional k-means algorithm. The test results can be used as one of the best methods in evaluating the level of health in the Java Island area and a reference for decision-making in determining policies for related agencies.
Co-Authors A, Miftahul Hikmah Putri Samudera Agung Teguh Wibowo Almais Agus Sofiyan Anwar, Agus Sofiyan Ahmad Fahmi Karami Ainul Yaqin Anwar, Aldian Faizzul Arief, Yunifa Miftachul Cahyo Crysdian Dita Aisha Dwi Purbo Yuwono Eko Agus Moh. Iqbal Erfan Ainul Yakin Fathurrahman Fathurrahman Fithriani Matondang, Fithriani Fresy Nugroho Hidayah, Ika Arofatul Hidayah Ida Ayu Putu Sri Widnyani imamudin Imamudin, M Irwan Budi Santoso Kunaefi, Aang Kurniawati Kurniawati Lia Wahyuliningtyas MARIA BINTANG Mokhamad Amin Hariyadi Muchammad Mustaqhfiri, Muchammad Muhammad Andryan Muhammad Andryan Wahyu Saputra Muhammad Faisal Muhammad Isa Ansori Nur Fitriyah Ayu Tunjung Sari Pahlevi, Achmad Fahreza Alif Puspa Miladin Nuraida Safitri A. Basid Renisa Maulidifa Silfiyah, Chilmiatus Sri Harini Subarkah, Aan Fuad Sulika Sulika Syawab, Moh Husnus Totok Chamidy Usman Pagalay Wahyuliningtyas, Lia Wiwik Handayani Yuliawan, Audi Bayu Yunifa Miftachul Arif Yunifa Mittachul Arif Yusril Haza Mahendra Zainal Abidin Zainal Abidin Zuhri, Abdurrozaq Ashshiddiqi Zuhri, Abdurrozzaaq Ashshiddiqi