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All Journal Semantik Jurnal Simetris Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Prosiding SNATIF Jurnal Transformatika Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) Jurnal Informatika Upgris International Journal of Artificial Intelligence Research JURNAL MEDIA INFORMATIKA BUDIDARMA Progresif: Jurnal Ilmiah Komputer Jurnal Teknologi Dan Sistem Informasi Bisnis JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Budimas : Jurnal Pengabdian Masyarakat Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Ilmiah Intech : Information Technology Journal of UMUS JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Vivabio : Jurnal Pengabdian Multidisiplin Buletin Poltanesa Abdi Masya Jurnal Pengabdian Multidisiplin Journal Of Human And Education (JAHE) Community: Jurnal Pengabdian Pada Masyarakat Journal of Computing Theories and Applications Jurnal Informatika: Jurnal Pengembangan IT LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics
Etika Kartikadarma
Universitas Dian Nuswantoro
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Pengembangan Aplikasi Pencatatan Absensi dan Kegiatan Pegawai Aru PT Jasa Raharja Jawa Tengah Marcelino Iskandar; Etika Kartikadarma; Yani Parti Astuti; Egia Rosi Subhiyakto
Poltanesa Vol 23 No 1 (2022): Juni 2022
Publisher : P2M Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (748.464 KB) | DOI: 10.51967/tanesa.v23i1.1167

Abstract

PT Jasa Raharja (Pesero) merupakan perusahaan asuransi BUMN di Indonesia yang bertugas untuk dapat memberikan layanan santunan dan perlindungan sosial bagi masyarakat khususnya untuk korban kecelakaan lalu lintas yang terjadi di Indonesia. Berdampingan dengan PT Jasa Raharja bekerja, PT ARU Raharja didirikan dengan tujuan untuk dapat membantu pekerjaan keseharian non-formal pegawai Jasa Raharja. Pegawai ARU Raharja terdiri dari satpam, sopir, dan juru layan. Pada kantor cabang PT Jasa Raharja Jawa Tengah, pegawai ARU tidak memiliki sistem pencatatan absensi dan kegiatan yang berbasiskan teknologi. Penilaian kinerja pegawai ARU masih sulit dikarenakan pencatatan masih mengandalkan pencatatan secara manual. Melalui penelitian ini dikembangkan aplikasi yang akan digunakan oleh pegawai ARU di kantor cabang PT Jasa Raharja Jawa Tengah untuk dapat melakukan pencatatan absensi dan kegiatan saat bekerja. Aplikasi akan mengimplementasikan QR Code dan GeoFencing sebagai teknik pembatasan wilayah akses aplikasi. Diajukan metode pengembangan aplikasi berupa Rapid Application Development (RAD) yang dapat membantu pengembangan aplikasi dengan perencanaan awal yang minim dan waktu pengerjaan yang singkat. Analisis dan perancangan menggunakan metode berorientasi objek dengan menggunakan diagram use case dan diagram aktivitas. Berdasarkan hasil pengujian black box didapatkan bahwa fungsionalitas aplikasi sudah sesuai. Sedangkan dari hasil pengujian white box menggunakan basis path testing sudah berjalan dengan baik dan sesuai.
Sistem Deteksi Surel SPAM Dengan DNSBL Dan Support Vector Machine Pada Penyedia Layanan Mail Marketing Fahri Firdausillah; Muhammad Hafidz; Erika Devi Udayanti; Etika Kartikadarma
Journal of Information System Research (JOSH) Vol 3 No 4 (2022): Juli 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (581.527 KB) | DOI: 10.47065/josh.v3i4.1795

Abstract

Mail marketing is an effective communication medium for users and internet providers. Many companies use email as a mean of communication with customers to ensure customers are not left behind with the latest information, and at once provide personalized offers to specific customers. However, not all emails that are sent reach mail inbox as expected. There are several factors as the cause including content that does not comply with the writing rules and tends to have SPAM signatures, invalid e-mail addresses, the sender domains are registered in the blacklist and so forth. Mail marketing service providers such as MTarget and Mailchimp must ensure that emails sent by their customers have no potential to become spam, because it can affect all of their mail marketing services will be blacklisted, thus promotional goals will not be achieved. In that case, a system is needed to check the e-mail that will be sent by the customer, to ensure that the e-mail will not detected as a spam by email service applications such as Gmail. This research produces an email validator system that can prevent sending emails that have the potential to become SPAM, so as to reduce the risk of a mail marketing service provider being blacklisted which results in delays in promotion via email and a decrease in marketing turnover. The proposed method used in this research is the Domain Name System-Based Blackhole List (DNSBL) to check the IP and the sending domain and the Support Vector Machine (SVM) to check the content of the email to be sent. The system developed has been functioning as expected and has an accuracy rate of 97.54% in detecting SPAM emails.
Analisis Sentimen Menggunakan Metode Naïve Bayes Untuk Mengetahui Respon Masyarakat Terhadap Vaksinasi Egia Rosi Subhiyakto; Yani Parti Astuti; Nathaniel Alexander; Etika Kartikadarma
Jurnal Teknik Informatika UMUS Vol 4 No 02 (2022): November
Publisher : Universitas Muhadi Setiabudi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46772/intech.v4i02.864

Abstract

Media sosial merupakan suatu media yang sulit untuk lepas dari kehidupan sehari-hari saat ini, dimana setiap orang dapat dengan bebas berekspresi dan mengeluarkan isi pikirannya secara meluas di internet, dalam menghadapi pandemi COVID-19, Vaksinasi merupakan hal yang wajib dilakukan sebagai salah satu untuk memutuskan rantai penyebaran virus COVID-19, oleh karena itu informasi yang tersebar di media sosial mengenai vaksinasi juga perlu terjaga untuk mengurangi kekhawatiran masyarakat terhadap pandemi serta menjaga kelancaran vaksinasi yang sedang berjalan. Untuk mengetahui hal tersebut, diperlukan suatu studi analisis sentimen mengenai tanggapan masyarakat mengenai “vaksinasi”, dengan penelitian yang dilakukan ini untuk mengetahui bagaimana tanggapan masyarakat terhadap vaksinasi didapatkan bahwa banyak masyarakat yang mendukung serta menerima dengan baik vaksinasi dan hanya sedikit masyarakat yang menolak vaksinasi, pengukuran confusion matrix pada hasil klasifikasi juga dilakukan dengan hasil accuracy 84%, precision 95%, recall 85%, dan specificity 80%.
Optimasi Algoritma Random Forest menggunakan Principal Component Analysis untuk Deteksi Malware Fauzi Adi Rafrastaraa; Ricardus Anggi Pramunendar; Dwi Puji Prabowo; Etika Kartikadarma; Usman Sudibyo
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 5 No 3 (2023): July 2023
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v5i3.854

Abstract

Malware is a type of software designed to harm various devices. As malware evolves and diversifies, traditional signature-based detection methods have become less effective against advanced types such as polymorphic, metamorphic, and oligomorphic malware. To address this challenge, machine learning-based malware detection has emerged as a promising solution. In this study, we evaluated the performance of several machine learning algorithms in detecting malware and applied Principal Component Analysis (PCA) to the best-performing algorithm to reduce the number of features and improve performance. Our results showed that the Random Forest algorithm outperformed Adaboost, Neural Network, Support Vector Machine, and k-Nearest Neighbor algorithms with an accuracy and recall rate of 98.3%. By applying PCA, we were able to further improve the performance of Random Forest to 98.7% for both accuracy and recall while reducing the number of features from 1084 to 32.
Metode MICE Support Vector Machine (MICE-SVM) untuk Klasifikasi Performance Mahasiswa Merdeka Belajar Kampus Merdeka Angga Apriano Hermawan; Galuh Wilujeng Saraswati; Etika Kartikadarma
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6821

Abstract

The Ministry of Education and Culture established a Merdeka Belajar Kampus Merdeka (MBKM) program with the aim of improving the competency of student graduates, both soft skills and hard skills, so that they are better prepared and relevant to the needs of the times, preparing graduates as future leaders of the nation who are superior and have personality. However, the MBKM program is not always effective in improving the quality of a student because there are still several shortcomings. It is also felt that some students have not received maximum results when participating in the MBKM program. In fact, not all programs offered by MBKM partners receive an assessment in the form of soft skills scores. The aim of this research is to classify whether the MBKM program influences the performance of MBKM program students by applying the Multivariate Imputation by Chained Equation (MICE) method to overcome missing values in the classification of MBKM student performance at the Faculty of Computer Science, Dian Nuswantoro University. The qualification of MBKM student performance is very important because we need to know whether the program is deemed effective or not to be continued in the future. In this study, researchers used a dataset originating from the MBKM report from students at the Faculty of Computer Science, Dian Nuswantoro University. Researchers obtained data by collecting data from MBKM student certificates and reporting the results. The data taken was 277 pieces for training and 69 pieces for testing. Next, the researchers used the Support Vector Machine (SVM) algorithm for the classification process. The research results show that the performance of the Support Vector Machine (SVM) algorithm model with MICE missing value handling has better accuracy results, with an accuracy value of 98.07% compared to using the Mean Imputation method, which only obtains an accuracy of 97.34%.
PENGEMBANGAN APLIKASI SISTEM INFORMASI RESIK BECIK (SIKECIK) BERBASIS WEB PADA RUMAH SAMPAH RESIK BECIK KELURAHAN KROBOKAN SEMARANG Meilani Dwi Permatasari; Dianna Yanuaresta; Rino Agung; Etika Kartikadarma; Lakui Johary; Galuh Wilujeng Saraswati; Filmada Ocky Saputra
BUDIMAS : JURNAL PENGABDIAN MASYARAKAT Vol 4, No 2 (2022): BUDIMAS : VOL. 04 NO. 02, 2022
Publisher : LPPM ITB AAS Indonesia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/budimas.v4i2.6739

Abstract

Semarang merupakan salah satu kota penghasil sampah terbesar di Indonesia. Sekitar 1.270 ton sampah per hari dan sekitar 900 ton di antaranya dikirim ke Tempat Pembuangan Akhir (TPA) setiap harinya dan hanya sebagian kecil dari sampah yang di daur ulang. Rumah Sampah Resik Becik merupakan bank sampah yang menampung sampah dari nasabah berupa kertas karton, plastik, logam, kaca, hingga cangkang telur. Rumah Sampah Resik Becik merupakan singkatan dari ’Gerakan Bersih Kreatif Bersama Ciptakan Kemakmuran’ dan rumah sampah didirikan karena jumlah sampah di kota Semarang semakin mengkhawatirkan yang setiap tahunnya mengalami peningkatan hingga 10%. Proses bisnis di rumah sampah resik becik masih dilakukan secara manual dan para pengurus masih kesulitan dalam mendata nasabah, sampah, dan saldo secara langsung. Oleh karena itu, diperlukan adanya digitalisasi manajemen sistem pada Rumah Sampah Resik Becik melalui sistem SIKECIK yang berbasis website dan mobile application.
Pengelolaan Sampah Rumah Tangga Berbasis Aplikasi Pada Seluruh Bank Sampah Di Kecamatan Semarang Barat Saputra, Filmada Ocky; Ingsih, Kusni; Kartikadarma, Etika; Isthika, Wikan; Johary, Lakui; Sakti, Maulana Bima
Jurnal Pengabdian Multidisiplin Vol. 3 No. 2 (2023): Jurnal Pengabdian Multidisiplin
Publisher : Kuras Institute & Scidac Plus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51214/japamul.v3i2.632

Abstract

Data jumlah produksi sampah rumah tangga di Kota Semarang mencapai 1.110 ton perhari. Secara keseluruhan sampah tersebut dibuang ke tempat pembuangan akhir (TPA) setiap harinya. Dinas Lingkungan Hidup (DLH) bersama dengan pemerintah Kota Semarang mencanangkan program 1.000 bank sampah terdapat dikota Semarang dengan kondisi saat ini terdapat 229 yang telah beroperasi. Harapan dengan semakin banyaknya bank sampah maka sampah yang masuk ke pembuangan sementara dan TPA dapat berkurang karena terjadi proses pilah pilih dan olah sampah sebelum dibuang pada TPA. Mitra pengusul dalam kegiatan PKM ini merupakan bank sampah di kawasan kecamatan Semarang Barat, yang memiliki 16 kelurahan dimana pada setiap kelurahan setidaknya memiliki 1 bank sampah yang aktif. Namun kondisi pada pengelolaan bank sampah pada setiap kelurahan masih berbeda, berdasarkan hasil survey tim pengusul ditemukan beberapa bank sampah yang dikelola melalui LPMK Kelurahan dan terdapat pula bank sampah yang dikelola secara individu. Hal ini menjadikan kontrol yang susah pada tingkat kecamatan untuk mengetahui pengelolaan sampah di kecamatan Semarang Barat melalui bank sampah ini. Permasalahan lain yang terjadi adalah pengelola bank sampah belum dapat menjual produk olahan sampah dengan efektif baik dari segi media penjualan dan perhitungan biaya produksi. Tim mengusulkan kegiatan PKM dengan memberikan solusi sistem pengelolaan sampah berbasis aplikasi digital dan pendampingan dalam merancang kebuatuhan biaya produksi dan sumber daya manusia. Dalam pelaksanaan tim pengusul akan mengunakan metode community based research (CBR), metode ini digunakan untuk dapat secara tepat mengatasi permasalahan riil yang terjadi dimasyarakat, sehingga tujuan yang diinginkan dapat tercapat sesuai permasalahan yang dialami masyakarat. Dalam pelaksanaan respon positif dari peserta dengan secara aktif berdiskusi, melakukan pemasangan aplikasi, pendaftaran akun, serta mencoba fitur, sehingga data timbulan sampah yang disetorkan dan diolah oleh bank sampah dapat terintegrasi se kecamatan Semarang Barat.
PENGOLAHAN LIMBAH MINYAK JELANTAH MENJADI LILIN AROMATERAPI BERNILAI JUAL DALAM GERAKAN 3R Kumoro, Imanuel Dimas Cahyo; Trisnapradika, Gustina Alfa; Rahma, Khalida Nur; Kartikadarma, Etika
Abdi Masya Vol 5 No 1
Publisher : Pusat Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52561/abdimasya.v5i1.363

Abstract

Indonesia is one of the largest waste-contributing countries in the world. This is no exception in Kelurahan Bandarharjo which has a large population so that household waste production is directly proportional to the population. The processing of household waste needs special attention, both from the household scale to the national scale. So far, household waste has only been collected at a TPS and ends up piled up in a TPA. This cannot continue because these piles of rubbish can become a source of pollution and disease for the community. Used cooking oil or jelantah is a type of waste that must be found in every household. So the service team carried out outreach activities and demonstrations on the processing used cooking oil waste or jelantah which was then processed into aromatherapy candles to turn waste into high-value selling products.. The method used in this service is in the form of socialization and demonstrations carried out in one day. As a result, the 3R (Reduce, Reuse, Recycle) movement provides an increase in public knowledge in managing the cleanliness of the earth. The team hopes that this training can also be disseminated in the surrounding district.
Enhancing Lung Cancer Classification Effectiveness Through Hyperparameter-Tuned Support Vector Machine Gomiasti, Fita Sheila; Warto, Warto; Kartikadarma, Etika; Gondohanindijo, Jutono; Setiadi, De Rosal Ignatius Moses
Journal of Computing Theories and Applications Vol. 1 No. 4 (2024): JCTA 1(4) 2024
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.10106

Abstract

This research aims to improve the effectiveness of lung cancer classification performance using Support Vector Machines (SVM) with hyperparameter tuning. Using Radial Basis Function (RBF) kernels in SVM helps deal with non-linear problems. At the same time, hyperparameter tuning is done through Random Grid Search to find the best combination of parameters. Where the best parameter settings are C = 10, Gamma = 10, Probability = True. Test results show that the tuned SVM improves accuracy, precision, specificity, and F1 score significantly. However, there was a slight decrease in recall, namely 0.02. Even though recall is one of the most important measuring tools in disease classification, especially in imbalanced datasets, specificity also plays a vital role in avoiding misidentifying negative cases. Without hyperparameter tuning, the specificity results are so poor that considering both becomes very important. Overall, the best performance obtained by the proposed method is 0.99 for accuracy, 1.00 for precision, 0.98 for recall, 0.99 for f1-score, and 1.00 for specificity. This research confirms the potential of tuned SVMs in addressing complex data classification challenges and offers important insights for medical diagnostic applications.
Exploiting Silhouette Principle Component For Dimension Reduction In Breast Ultrasound Images Classification Kartikadarma, Etika; Fanani, Ahmad Zainul; Pujiono, Pujiono; Affandy, Affandy; Wulandari, Sari Ayu
International Journal of Artificial Intelligence Research Vol 8, No 1 (2024): June 2024
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1165

Abstract

This paper proposes the use of the Dimensional Reduction method with the Silhouette Principle Component (SPC) Approach to improve the classification of breast ultrasound images. The PCA method is used to reduce the dimensions of medical images to improve classification, with MobileNet-v2 and DenseNet-121 as the optimal classification algorithm choices. The results show that the SPC method succeeded in producing efficient feature representation with data sizes that are almost the same as the original data, while PCA produces greater dimensionality reduction. The SPC model also shows the best performance in terms of accuracy and loss. This research makes a significant contribution to the development of more sophisticated and efficient medical image analysis techniques to support the diagnosis and treatment of breast cancer.
Co-Authors Aditya Wahyu Ramadhan Affandy Affandy Afida, Dita Ahmad Zainul Fanani Ajib Susanto Akbar Dwi Syahputra Alvin Jaya Hulu, Alvin Angga Apriano Hermawan Ashari Juang, Ashari Astuti, Yani Parti Azhara Devi Sandi Christy Atika Sari De Rosal Ignatius Moses Setiadi Desi Purwanti Dhani, Iqbal Dianna Yanuaresta Dico Tri Rosandi Doheir, Mohamed Dwi Puji Prabowo Egia Rosi Subhiyakto Egia Rosi Subhiyakto Egia Rosi Subhiyakto, Egia Rosi Ekaprana Wijaya Erika Devi Udayanti Erlin Dolphina Fahmi Amiq Fahri Firdausillah Farikh Al Zami Fauzi Adi Rafrastara Filmada Ocky Saputra Gomiasti, Fita Sheila Habib Mustofa Hafidhoh, Nisa'ul Hafidhoh, Nisa’ul Hafidhoh, Nisa’ul Heribertus Himawan Ifan Rizqa Ifan Rizqa Ifan Rizqa Ifan Rizqa Ifan Rizqa Ifan Rizqa Ihwati Ummi Iskandar, Marcelino Johary, Lakui Jutono Gondohanindijo, Jutono Kumoro, Imanuel Dimas Cahyo Kurniawan, Defri Kusni Ingsih L. Budi Handoko Lakui Johary Marcelino Iskandar Meilani Dwi Permatasari Muhamad Ni'am Syukri Roni Asmi Muhammad Hafidz Muljono, - Najma Fatimah, Nandhita Nathaniel Alexander Nila Tristiarini, Nila Nisa'ul Hafidhoh Nova Rijati Pujiono Pujiono Purwanto Purwanto Rahma, Khalida Nur Raihan Yusuf Ricardus Anggi Pramunendar Rino Agung Rohman, Muhammad Syaifur Safa Firdaus, Muhammad Argya Sakti, Maulana Bima Saputra, Filmada Ocky Saraswati, Galuh Wilujeng Sari Ayu Wulandari Sari Wijayanti Sari Wijayanti Sari Wijayanti Setyawati, Vilda A. V. Sudibyo, Usman Sugiyanto - Susanto, Devva Ricovani T. Sutojo Tri Listyorini Trisnapradika, Gustina Alfa Usman Sudibyo Utomo, Danang Wahyu Wardatunizza, Indah Warto - Wibowo, Alrico Rizki Widayat Yutriatmansyah, Widi Widi Widayat Yutriatmansyah Wikan Isthika, Wikan Winarsih, Nurul Anisa Sri Yani Parti Astuti Yani Parti Astuti Yunita Kemala Sari Yutriatmansyah, Widi Widayat Yutriatmansyah, Widi Widayat Zaenal Arofi, Muhammad Labib