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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi CESS (Journal of Computer Engineering, System and Science) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer STATISTIKA Engagement: Jurnal Pengabdian Kepada Masyarakat
Wika Dianita Utami
Department Of Mathematic, Islamic State Of Sunan Ampel Surabaya University
Religion Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Mathematics Social Sciences

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Application Random Forest Method for Sentiment Analysis in Jamsostek Mobile Review Tasya Auliya Ulul Azmi; Luthfi Hakim; Dian Candra Rini Novitasari; Wika Dianita Utami Dianita Utami
Telematika Vol 20, No 1 (2023): Edisi Februari 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i1.8868

Abstract

Purpose: This study aims to monitor the service quality of JMO applications from time to time by classifying JMO user reviews into the class of positive, neutral, and negative sentiments.Design/methodology/approach : The method used in this study is the random forest classification method. Data processing in this study uses feature extraction, TF-IDF and labeling with the lexicon-based method.Findings/result: Based on the research results, it was found that the highest frequency of classification was the positive class with 17571 reviews compared to the neutral class with 8701 reviews and the negative class with 3876 reviews with an accuracy evaluation value of 93%, precision 88%, recall 93%, and f1-score 90%.Originality/value/state of the art:This study uses 150737 reviews that have been pre-processed using the random forest method and TF-IDF and lexicon-based feature extraction.
Implementation of Naive Bayes Classification Algorithm in Determining Appropriate Help Targets of Unlimited Houses (RTLH) in Bojonegoro District Anissa Nurul Farida Tussholikhah; Nurissaidah Ulinnuha; Wika Dianita Utami
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 2 (2023): July 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i2.46295

Abstract

Rumah merupakan salah satu kebutuhan primer bagi setiap individu, dan termasuk kedalam aset terpenting yang harus dimiliki. Kelayakan rumah yang layak huni dan tidak layak huni harus dipertimbangkan. Rumah yang tidak memenuhi kecukupan minimum dari segi ruang dan luas ruangan dianggap sebagai Rumah tidak layak huni (RTLH). Untuk mengatasi terjadinya peningkatan RTLH maka pemerintah menanggulanginya dengan memberikan bantuan kepada masyarakat yang layak menerima dengan tepat sasaran. Penelitian ini bertujuan untuk menerapkan metode Naïve Bayes dalam menentukan bantuan tepat sasaran menggunakan dua kelas penelitian, yakni layak menerima bantuan RTLH dan tidak layak menerima bantuan RTLH. Dari analisis klasifikasi menggunakan confusion matrix didapatkan hasil akurasi sebesar 63%, recall 100% dan presisi 25% untuk 400 data training dan 100 data testing dari total 500 data dengan 10 atribut pengujian.The house is one of the primary needs for every individual, and is included in the most important asset that must be owned. The livability of the livable and uninhabitable houses should be considered. A house that does not meet the minimum adequacy in terms of space and room area is considered an uninhabitable house (RTLH). To overcome the increase in RTLH, the government overcomes it by providing assistance to people who deserve to receive it on target. This study aims to apply the Naïve Bayes method in determining targeted assistance using two research classes, namely eligible to receive RTLH assistance and not eligible to receive RTLH assistance. From the classification analysis using the confusion matrix, the results obtained are 63% accuracy, 100% recall and 25% precision for 400 training data and 100 testing data from a total of 500 data with 10 test attributes.
Optimasi Golden Section pada Metode Double Exponential Smoothing untuk Meramalkan Indeks Harga Konsumen di Indonesia Zumrotul Muallifah; Wika Dianita Utami; Hani Khaulasari; M. Lail Kurniawan
Statistika Vol. 23 No. 1 (2023): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v23i1.2183

Abstract

ABSTRAK Indeks Harga Konsumen (IHK) dapat digunakan sebagai indikator ekonomi dan ukuran tingkat biaya produksi, serta berguna dalam memantau tingkat kenaikan harga dan pendapatan. Pemerintah perlu secara berkala menyesuaikan kebijakan inflasi IHK untuk menjaga stabilitas situasi ekonomi rakyat, mengingat tingkat inflasi IHK berubah setiap bulan. Penelitian ini bertujuan untuk mengoptimalkan parameter dan melakukan peramalan IHK untuk periode November 2022 hingga Oktober 2023 menggunakan metode Double Exponential Smoothing Holt dengan optimasi parameter menggunakan metode Golden Section. Hasil penelitian menunjukkan bahwa MAPE (Mean Absolute Percentage Error) sebesar 0,8140406%, dengan nilai parameter optimal sebesar 0,9957141 dan 0,0127842. Peramalan menunjukkan tingkat stabilitas yang baik dari bulan November 2022 hingga Oktober 2023. ABSTRACT The Consumer Price Index (CPI) can be used as an economic index and a measure of production costs, and it is useful for examining price increases and income levels. The government needs to periodically adjust CPI inflation policies to ensure the stability of the people's economy since the CPI inflation rate changes every month. The research aims to obtain optimized parameter results and forecasts for the CPI from November 2022 to October 2023 using the Golden Section parameter optimization in Double Exponential Smoothing Holt. The research results using the Double Exponential Smoothing Holt method and Golden Section parameter optimization show an MAPE value of 0.8140406% and parameter values of 0.9957141 and 0.0127842. The forecasted results indicate a stable trend from November 2022 to October 2023.
Pendampingan Guru Madrasah untuk Mewujudkan Kompetensi Pedagogik Guru Matematika yang Berdaya Melalui Penguasaan Soal High Order Thinking Skills (HOTS) Moh Hafiyusholeh; Ahmad Lubab; Ahmad Hanif Asyhar; Aris Fanani; Yuniar Farida; Dian C. Rini Novitasari; Nurissaidah Ulinnuha; Putroue Keumala Intan; Wika Dianita Utami; Zainullah Zuhri; Ahmad Zaenal Arifin; Dian Yuliati; Abdulloh Hamid
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol 4 No 1 (2020): May 2020
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/engagement.v4i1.97

Abstract

High Order Thinking Skills (HOTS) is the ability to connect, manipulate, and change the knowledge and experience that is owned critically and creatively in determining decisions to solve problems in new situations. To include HOTS questions in a learning process is an obstacle for Madrasah teachers, including teachers of PC. LP. Maarif NU Lamongan. This community service aimed at improving the pedagogical competence of mathematics teachers of PC. LP. Maarif NU Lamongan. Community-Based Research (CBR) was employed through workshop and training administered by the Mathematics Study Program of UIN Sunan Ampel Surabaya in designing and completing high order thinking questions followed by assistance. The results indicated that the ability of Madrasah teachers to solve HOTS questions as well as its implementation in classroom teaching and learning activities improved significantly.
Economic Empowerment of Housewives Based on OPOR (One Product in One RT) in Pojok Village of Magetan Regency, Using the Asset-Based Community-Driven Development (ABCD) Approach Yuniar Farida; Wika Dianita Utami; Aris Fanani; Latifatun Nadya Desinaini; Silvia Kartika Sari
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol 6 No 1 (2022): May 2022
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/engagement.v6i1.1161

Abstract

Nowadays, the improvement in resources, especially among women, is considered. One of the efforts to empower women in the village can be done through the assistance of Micro, Small, and Medium Enterprises (MSMEs). This research-based community service aims to assist the community, especially women (housewives) in Pojok Village of Magetan Regency, in developing home businesses. This community service is carried out by using ABCD approach, which is an approach to understanding and internalizing assets, potential, strength, and utilization independently and optimally. The results of the community service carried out by researchers have positive impact to the community and it fosters a high desire and enthusiasm to make changes for the better in the development of marketing businesses, both during the mentoring process and post-mentoring so that the economy in Pojok Village, Magetan Regency can increase
Implementation of The Extreme Gradient Boosting Algorithm with Hyperparameter Tuning in Celiac Disease Classification Roudlotul Jannah Alfirdausy; Nurissaidah Ulinnuha; Wika Dianita Utami
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 1 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i1.4031

Abstract

Celiac Disease (CeD) is an autoimmune disorder triggered by gluten consumption and involves the immune system and HLA in the intestine. The global incidence ranges from 0.5%-1%, with only 30% correctly diagnosed. Diagnosis remains challenging, requiring complex tests like blood tests, small bowel biopsy, and elimination of gluten from the diet. Therefore, a faster and more efficient alternative is needed. Extreme Gradient Boosting (XGBoost), an ensemble machine learning technique that utilizes decision trees to aid in the classification of Celiac disease, was used. The aim of this study was to classify patients into six classes, namely potential, atypical, silent, typical, latent and none disease, based on attributes such as blood test results, clinical symptoms and medical history. This research method employs 5-fold cross-validation to optimize parameters that are max depth, n estimator, gamma, and learning rate. Experiments were conducted 96 times to get the best combination of parameters. The results of this research are highlighted by an improvement of 0.45% above the accuracy value with the default XGBoost parameter of 98.19%. The best model was obtained in the trial with parameters max depth of 3, n estimator of 100, gamma of 0, and learning rate of 0.3 and 0.5 after modifying the parameters, yielding an accuracy rate of 98.64%, a sensitivity rate of 98.43%, and a specificity rate of 99.72%. This research shows that tuning the XGBoost parameters for Celiac
Co-Authors Abdulloh Hamid Ahmad Hanif Asyhar Ahmad Zaenal Arifin Anissa Nurul Farida Tussholikhah Dian C. Rini Novitasari Dian Yuliati Fadiah Irine Dwiana Fanani, Aris Farida, Yuniar Hani Khaulasari Latifatun Nadya Desinaini Lubab, Ahmad Luthfi Hakim M. Lail Kurniawan Moh. Hafiyusholeh Putroue Keumala Intan Roudlotul Jannah Alfirdausy Sari, Dian Candra Rini Novita Silvia Kartika Sari Sri Asih Tasya Auliya Ulul Azmi Zainullah Zuhri Zumrotul Muallifah