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ANALISIS DAMPAK CACHE PROGRESSIVE WEB APPS TERHADAP KONSUMSI BATERAI ANDROID Kurniawan, Wakhid; Romadloni, Nova Tri; Noor Bintang, Rauhulloh Ayatulloh Khomeini
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 2 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i2.6221

Penggunaan aplikasi web berkembang pesat, terutama di Android yang menguasai 46,18% pangsa pasar global. Pengguna menginginkan akses cepat, namun sering menghadapi koneksi lambat dan pemuatan ulang aset tanpa cache, yang dapat meningkatkan konsumsi baterai. Salah satu faktor yang diduga berpengaruh adalah penggunaan cache dalam aplikasi. Progressive Web Apps (PWA) menjadi relevan karena memanfaatkan service worker untuk menyimpan cache. PWA menawarkan keunggulan seperti akses tanpa koneksi, pemrosesan latar belakang, dan notifikasi push, memberikan pengalaman serupa aplikasi native. Penelitian ini menganalisis dampak cache PWA terhadap konsumsi baterai Android. Metode yang digunakan bersifat kuantitatif dengan eksperimen empiris. Sebanyak 33 situs PWA dipilih menggunakan Google Lighthouse. Data ukuran cache dikumpulkan, dan laporan bug dihasilkan selama 3 menit untuk mengukur konsumsi daya. Analisis dilakukan menggunakan uji Paired Sample T-Test dengan SPSS, membandingkan konsumsi baterai saat cache kosong dan terisi. Penelitian ini bertujuan memberikan wawasan mengenai pengaruh cache terhadap konsumsi daya, sehingga strategi dapat dikembangkan untuk meningkatkan efisiensi energi dan pengalaman pengguna.

A Hybrid Approach of Pearson Correlation and PCA in Feature Selection for Opinion Mining Tri Romadloni, Nova; Kurniawan, Wakhid; Ariyadi, Muhammad Yusuf; Efendi, Burhan
IJID (International Journal on Informatics for Development) 2025
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

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

This study proposes a hybrid feature selection approach that combines Pearson Correlation and Principal Component Analysis (PCA) to improve classification performance in opinion mining tasks. The rapid growth of e-commerce on social media platforms, such as TikTok, has generated a significant volume of user-generated reviews, which are valuable sources of consumer sentiment. However, the high dimensionality of textual data poses challenges in achieving accurate sentiment classification. To address this issue, the proposed method first applies Pearson Correlation to remove irrelevant features with weak correlation to sentiment labels, followed by PCA to reduce dimensionality. The dataset consists of user reviews from the TikTok Seller platform. Experiments using SVM, Naive Bayes, and Random Forest show that the hybrid approach achieves the highest accuracy of 86.2% (SVM and RF), improving over PCA-only by +0.9% and recovering 13.8% accuracy loss for Naive Bayes (from 72.0% to 83.1%). The results demonstrate that integrating correlation- and projection-based methods yields a more compact and effective feature set. This approach is especially suited for opinion mining in noisy, high-dimensional e-commerce data.

Uncovering Insights in Spotify User Reviews with Optimized Support Vector Machine (SVM) Tri Romadloni, Nova; Kurniawan, Wakhid
IJID (International Journal on Informatics for Development) Vol. 14 No. 1 (2025): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2025.4903

The rapid growth of user-generated reviews on platforms like Spotify necessitates efficient analytical techniques to extract valuable insights. This study employs a Support Vector Machine algorithm, optimized using Forward Selection, Backwards Elimination, Optimized Selection, Bagging, and AdaBoost, to effectively classify user reviews. A dataset of approximately 10,000 Spotify reviews was compiled from diverse online sources, ensuring a representative sample. The analysis reveals sentiment patterns across positive, negative, and neutral categories, with positive reviews dominates the landscape. These patterns help highlight Spotify’s strengths while identifying areas for improvement. However, the SVM algorithm faces challenges in classifying minority classes, particularly negative sentiments, due to class imbalance. To address this, advanced optimization techniques are utilized to enhance classification precision and recall. Preprocessing steps, including data cleansing, tokenization, stemming, and stopword removal, refine the dataset, while TF-IDF converts text into numerical features for effective feature selection. The results show that the Optimized Selection method achieves the highest accuracy of 84.5%, outperforming other approaches. This research contributes significantly to developing balanced sentiment analysis models. Future studies may explore deep learning techniques to further improve classification accuracy and mitigate current limitations in data representation.

A Hybrid Approach of Pearson Correlation and PCA in Feature Selection for Opinion Mining Tri Romadloni, Nova; Kurniawan, Wakhid; Ariyadi, Muhammad Yusuf; Efendi, Burhan
IJID (International Journal on Informatics for Development) Vol. 14 No. 2 (2025): IJID December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2025.5195

This study proposes a hybrid feature selection approach that combines Pearson Correlation and Principal Component Analysis (PCA) to improve classification performance in opinion mining tasks. The rapid growth of e-commerce on social media platforms, such as TikTok, has generated a significant volume of user-generated reviews, which are valuable sources of consumer sentiment. However, the high dimensionality of textual data poses challenges in achieving accurate sentiment classification. To address this issue, the proposed method first applies Pearson Correlation to remove irrelevant features with weak correlation to sentiment labels, followed by PCA to reduce dimensionality. The dataset consists of user reviews from the TikTok Seller platform. Experiments using SVM, Naive Bayes, and Random Forest show that the hybrid approach achieves the highest accuracy of 86.2% (SVM and RF), improving over PCA-only by +0.9% and recovering 13.8% accuracy loss for Naive Bayes (from 72.0% to 83.1%). The results demonstrate that integrating correlation- and projection-based methods yields a more compact and effective feature set. This approach is especially suited for opinion mining in noisy, high-dimensional e-commerce data.

SENAM HIPERTENSI UNTUK MENGURANGI RISIKO STROKE PADA KADER POSYANDU DUKUH TRENGGULI JENAWI KARANGANYAR Prasetyo, Afif Bayu Eko; Kurniawan, Wakhid; Muhammad Demas; Intan Ika Nabila; Nur Afifah; tutut
Jurnal Pengabdian Masyarakat FKIP UTP Vol 7 No 1 (2026): PROFICIO : Jurnal Abdimas FKIP UTP
Publisher : FKIP UNIVERSITAS TUNAS PEMBANGUNAN SURAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36728/jpf.v7i1.5668

Hipertensi merupakan salah satu faktor risiko utama terjadinya stroke. Kader kesehatan masyarakat, khususnya di Posyandu, memiliki peran strategis dalam pencegahan komplikasi hipertensi. Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan pengetahuan dan keterampilan kader Posyandu tentang senam hipertensi sebagai upaya pencegahan stroke di Dukuh Trengguli, Kecamatan Jenawi, Kabupaten Karanganyar. Metode yang digunakan adalah penyuluhan kesehatan, demonstrasi, dan praktik senam hipertensi. Peserta terdiri dari 25 kader Posyandu dengan kriteria berusia 25-60 tahun, aktif sebagai kader minimal 1 tahun, sehat jasmani, dan bersedia mengikuti kegiatan lengkap. Kegiatan dilakukan melalui penyuluhan kesehatan (60 menit), demonstrasi dan praktik (90 menit), serta diskusi (30 menit). Evaluasi dilakukan melalui pre-test dan post-test serta observasi kemampuan praktik senam. Hasil menunjukkan peningkatan pengetahuan peserta tentang hipertensi dari 65% menjadi 85% (peningkatan 30,7%) dan pengetahuan tentang senam hipertensi dari 45% menjadi 80% (peningkatan 77,8%). Seluruh peserta mampu melakukan gerakan senam hipertensi dengan benar setelah pelatihan, dengan tingkat keberhasilan 96% untuk gerakan pemanasan, 88% untuk gerakan inti, dan 92% untuk gerakan pendinginan. Kesimpulan adalah program senam hipertensi efektif meningkatkan pengetahuan dan keterampilan kader Posyandu dalam pencegahan komplikasi hipertensi serta dapat menjadi model untuk kegiatan pengabdian serupa. Kata Kunci: senam hipertensi; stroke; kader posyandu; pencegahan; pengabdian masyarakat

The Application of Intersection in the Set Theory for Instagram Hashtags Kurniawan, Wakhid; Ramadhan, Farha; Ardiansyah, Hafizd
IJID (International Journal on Informatics for Development) Vol. 8 No. 2 (2019): IJID December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2019.08207

Technology is developing rapidly with the advent of social media, which paper messages are substitutes for electronic messages that make someone is easier to communicate with others. Many social media exist. The famous ones are Facebook, Instagram, Twitter, and others. With so many social media emerging, every social media must have differences with other social media. Instagram has quite a lot of users, especially in student organizations on campus. The hashtags feature of Instagram makes it is easy to search what to find for people, and group them according to the hashtags used. This paper studies an implementation of intersection operators and applies the intersection operator to classification of Instagram’s hashtags.

Bit Manipulation: Conditional Statement using Bit-wise operators with C++ Nafi'ah, Rahmawati; Kurniawan, Wakhid; Setiawan, Johan; Umam, Khoirul
IJID (International Journal on Informatics for Development) Vol. 9 No. 1 (2020): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2020.09102

All of information that manipulated by a computer is represented in the form of bits, so in the programming language it is necessary to understand bitwise operations at the first. This paper aims to create a concept of making Conditional Statements with Bitwise operators in C ++. By doing so, we hope that people is easy to understand the operation behind conditional statements. A conditional operator is also known as a ternary operator. It takes three operands. A conditional operator is closely related with if else statement. The method used is a literature study studying the bit manipulation algorithm in the C ++ language. The results obtained are a function using bitwise operations in C ++ that implement conditional statements.

Integer Representation of Floating-Point Manipulation with Float Twice Kurniawan, Wakhid; Ardiansyah, Hafizd; Oktavianita, Annisa Dwi; Tahe, Mr. Fitree
IJID (International Journal on Informatics for Development) Vol. 9 No. 1 (2020): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2020.09103

In the programming world, understanding floating point is not easy, especially if there are floating point and bit-level interactions. Although there are currently many libraries to simplify the computation process, still many programmers today who do not really understand how the floating point manipulation process. Therefore, this paper aims to provide insight into how to manipulate IEEE-754 32-bit floating point with different representation of results, which are integers and code rules of float twice. The method used is a literature review, adopting a float-twice prototype using C programming. The results of this study are applications that can be used to represent integers of floating-point manipulation by adopting a float-twice prototype. Using the application programmers make it easy for programmers to determine the type of program data to be developed, especially those running on 32 bits floating point (Single Precision).

Perbandingan Genetic Algorithm dan Queue-Based Scheduling untuk Penjadwalan Kuliah Otomatis di Perguruan Tinggi Pratama, Muhammad Demas Adi; Kurniawan, Wakhid
TIN: Terapan Informatika Nusantara Vol 6 No 11 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i11.9570

Course scheduling is a fundamental activity in academic management; however, the complexity of room and teaching constraints often triggers schedule conflicts when processed conventionally. This study aims to design an automated course scheduling system at Universitas Muhammadiyah Karanganyar (UMUKA) by comparing the effectiveness of the Genetic Algorithm (GA) and Queue-Based Scheduling (QBS). The system was developed using the Laravel framework and a NoSQL Database. Comparative experiments were conducted through six dynamic scenarios (ranging from 20 to 263 courses), measured using three metrics: the final number of conflicts, fitness value, and computational time. The results indicated that QBS was absolutely superior in computational speed (maximum 4.18 seconds) but failed to produce proportional schedule quality, as the fitness value remained at 0. Conversely, GA successfully generated conflict-free schedules in medium workloads and compensated for minor conflicts in massive workloads by achieving a significant spike in fitness value (reaching 462.2). Although requiring relatively longer computational time (36.2 seconds at the highest load), this duration remains highly efficient. In conclusion, GA is recommended as the primary algorithm for course scheduling systems due to its ability to perform global optimization proportionally. The main contribution of this research is providing empirical foundations and a comparative architecture for higher education institutions in selecting the most adaptive scheduling algorithm for local room infrastructure limitations and hard-constraint complexity.

Small business in a small city: The implementation of augmented reality Ariyadi, Muhammad Yusuf; Augtiah, Imfrianti; Kurniawan, Wakhid
Sebelas Maret Business Review Vol 9, No 1 (2024): June 2024
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/smbr.v9i1.81416

SMEs (Small and Medium Enterprises) are the most are the most numerous sector in Indonesia; the MSME sector is the sector that absorbs the most workers. The MSME sector will dominate in Indonesia in 2023. The MSME sector's contribution to GDP will reach 60.5%, and total labor absorption will be 96.9% (Coordinating Ministry for the Economy, 2022). The total export contribution of MSMEs increased from 14.37% in 2020 to 15.69% at the end of 2022 (Coordinating Ministry for the Economy, 2022). Technology and digitalization have touched all elements of life. Education is one of the fundamental elements in life. This research examines the implementation of technology that can synergize aspects of education, information, and, at the same time, entertainment with augmented reality (AR) screen printing media in the alternative digital business for MSMEs as an innovative media for young people in Karanganyar Regency. This research uses a qualitative approach with a 2 stage interview method: pre-test and post-test in participant testing. The participants in this research were 51 people who were classified as producers, MSME employees, and t-shirt screen printing consumers aged 15-24 years as classified by the Central Statistics Agency (Badan Pusat Statistik-BPS). To maintain good distribution, participants in this research are expected to be representatives of all sub-districts in the Karanganyar Regency area. Implementing augmented reality (AR) technology in digital business alternatives for SMEs as innovative media for young people in Karanganyar Regency has very good prospects and potential.

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