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All Journal FIKRAH Abdimas Pedagogi: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Pilar Nusa Mandiri Jurnal Teknik Informatika STMIK Antar Bangsa Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Manajemen Informatika Wahana Sekolah Dasar JSAI (Journal Scientific and Applied Informatics) INTERACTION: Jurnal Pendidikan Bahasa INTI Nusa Mandiri Jurnal Ide Bahasa STUDI PELAKSANAAN SELFMEDICATION PADA PENDERITA DIARE BERDASARKAN TINGKAT PENGETAHUAN MASYARAKAT PESISIR KECAMATAN SOROPIA KABUPATEN KONAWE Best : Journal of Applied Electrical, Science and Technology Abditeknika - Jurnal Pengabdian Kepada Masyarakat Sosietas: Jurnal Pendidikan Sosiologi Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) JDEP (Jurnal Dinamika Ekonomi Pembangunan) Jurnal Pengabdian Masyarakat dan Penelitian Thawalib Jurnal Teknologi Jurnal Ilmiah Fakultas Sains dan Teknik Universitas Nusa Cendana Abdi Teknoyasa Jurnal Lektur Keagamaan Easta Journal of Innovative Community Services Aqwal: Journal of Quran and Hadies Studies Jurnal Pengabdian West Science Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) ABDI MASYARAKAT INTERACTION: Jurnal Pendidikan Bahasa
Imam Nawawi, Imam
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Jamu as a Healthy Solution for Travelers: The Initiative of DPD Aspetri East Java at the Health Post in Purabaya Terminal Larasaty, Hartaty; Nawawi, Imam; Wibowo, Teguh Setiawan
Jurnal Pengabdian West Science Vol 4 No 04 (2025): Jurnal Pengabdian West Science
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/jpws.v4i04.2138

Abstract

Long journeys often cause fatigue and a decrease in immune function, especially for public transportation users. Jamu, as a heritage of herbal medicine from the Indonesian archipelago, holds great potential in maintaining health and enhancing stamina during travel. This community service activity aims to introduce and distribute jamu as a healthy solution for travelers through the initiative of DPD Aspetri Jawa Timur at the Health Post in Purabaya Terminal. The activity includes education on the benefits of jamu, free distribution of jamu, and herbal-based health consultations for passengers and terminal visitors. The results of the activity show that the majority of beneficiaries responded positively to the program, with an increased understanding of the benefits of jamu in maintaining health during travel. This activity is expected to serve as a model for promoting herbal-based health in other public facilities.
Komparasi Algoritma Logistic Regression dan Random Forest pada Prediksi Cacat Software Prasetyo, Rizal; Nawawi, Imam; Fauzi, Ahmad; Ginabila
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v6i2.1522

Abstract

Testing becomes the standard in producing quality software, testing can be assessed through certain measures and methods, one of the benchmarks for software quality is ISO, which was made by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) , In the prediction of software defects software defect prediction error is a very bad thing, the prediction results can have an effect on the software itself. This study compares the results of the Logistic Regression Algorithm and Random Forest before and after the resampling method is applied, the test results show that Random Forest with resampling produces a higher level of accuracy. From the test results above, it can be concluded that the Random Forest with resampling method is more effective in predicting software defects
Klasifikasi Human Stress Menggunakan Adagrad Optimization untuk Arsitektur Deep Neural Network Azis, Mochammad Abdul; Fauzi, Ahmad; Ginabila; Nawawi, Imam
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v7i1.1916

Abstract

According to the World Health Organization, stress is a type of mental illness that affects human health and there is no one in this world who does not suffer from stress or depression. Stress is a term that is often used synonymously with negative life experiences or life events. . Analysis of data that has an unbalanced class results in inaccuracies in predicting human stress. This study shows that using the Deep Neural Network (DNN) Architecture model by optimizing several parameters, namely the optimizer, Learning rate and epoch. The best DNN Architect results are obtained with 4 Hidden Layers, Adagard Optimization, Learning rate 0.01 and the number of epochs 100. Accuracy, precision, recall and f-measure scores get 98.25%, 83.00%, 98.25%, 91.00%, respectively.
Komparasi Algoritma Logistic Regression dan Random Forest pada Prediksi Cacat Software Prasetyo, Rizal; Nawawi, Imam; Fauzi, Ahmad; Ginabila
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (665.169 KB) | DOI: 10.54367/jtiust.v6i2.1522

Abstract

Testing becomes the standard in producing quality software, testing can be assessed through certain measures and methods, one of the benchmarks for software quality is ISO, which was made by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) , In the prediction of software defects software defect prediction error is a very bad thing, the prediction results can have an effect on the software itself. This study compares the results of the Logistic Regression Algorithm and Random Forest before and after the resampling method is applied, the test results show that Random Forest with resampling produces a higher level of accuracy. From the test results above, it can be concluded that the Random Forest with resampling method is more effective in predicting software defects
Klasifikasi Human Stress Menggunakan Adagrad Optimization untuk Arsitektur Deep Neural Network Azis, Mochammad Abdul; Fauzi, Ahmad; Ginabila; Nawawi, Imam
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v7i1.1916

Abstract

According to the World Health Organization, stress is a type of mental illness that affects human health and there is no one in this world who does not suffer from stress or depression. Stress is a term that is often used synonymously with negative life experiences or life events. . Analysis of data that has an unbalanced class results in inaccuracies in predicting human stress. This study shows that using the Deep Neural Network (DNN) Architecture model by optimizing several parameters, namely the optimizer, Learning rate and epoch. The best DNN Architect results are obtained with 4 Hidden Layers, Adagard Optimization, Learning rate 0.01 and the number of epochs 100. Accuracy, precision, recall and f-measure scores get 98.25%, 83.00%, 98.25%, 91.00%, respectively.
Optimasi Kernel SVM dengan PSO untuk Gagal Jantung Nurdin, Hafis; Sugiarto, Hari; Yuliandari, Dewi; Wuryanto, Anus; Nawawi, Imam
Jurnal Manajemen Informatika JAMIKA Vol 15 No 2 (2025): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v15i2.14409

Abstract

Accurate early detection is important to improve the quality of life of patients and reduce mortality and a major burden on the public health system caused by heart failure. This study aims to improve the accuracy of heart failure prediction using Support Vector Machine (SVM). SVM is used as a strong classifier for high-dimensional data, then optimizes its kernel using Particle Swarm Optimization (PSO), which has not been widely applied in similar studies. The method used includes computational experiments with a quantitative approach based on heart failure datasets from the UCI Repository which are analyzed using SVM with three types of kernels: Dot, Radial, and Polynomial. PSO is used to optimize the selection of kernel parameters in SVM to improve classification accuracy. The results show that SVM + PSO kernel Dot gives the best performance, with an AUC of 0.865 and an accuracy of 83.97%, and this difference is confirmed significant through a paired t-test (p <0.05) compared to SVM without optimization. PSO optimization consistently improves precision and recall in the tested kernels, indicating stability and effectiveness in classification. The impact of the research is to make a significant contribution to early detection efforts for heart failure which can lead to faster treatment and improved quality of life for patients, but also adds clinical value for medical practitioners seeking efficient and accurate classification methods.
Aplikasi Sistem Informasi Layanan Dan Managemen Data Customer Pada Laundry Mandala Nawawi, Imam; Hatmoko, Bondan Dwi; Ismailah, Ismailah
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 5, No 1 (2021): SEMNAS RISTEK 2021
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v5i1.4895

Abstract

Dirancangnya suatu aplikasi layanan dan managemen data pelanggan dengan tujuan untuk memproses pengolahan data pelanggan dan proses pembayaran yang ada saat ini. Perangkat aplikasi yang telah dibuat dengan bahasa pemrograman Java NetBeans 8.0.2 dan penyimpanan data pada database MySQL dapat memberikan kelancaran dalam menginput dan penyimpanan data-data serta laporan-laporan yang diberikan kepada Pimpinan perusahaan. Dengan menggunakan metode pengembangan sistem yaitu Waterfall dalampenelitian ini adalah dengan tahapan-tahapan seperti rekayasa sistem, analisis, desain, coding, testing, dan maintenance. Hasil dari penelitian yang dilakukan di Laundry Mandala terkait sistem informasi layanan dan managemen data pelanggan ini dapat menciptakan aplikasi untuk pendataan data pelanggan dan data pembayaran dapat tersampaikan dengan baik di pelaporannya sehingga aplikasi ini dapat bermanfaat.
Problematika Transaksi Jual Beli Jambu Air (Studi Kasus di Desa Dharma Camplong) Khorofi, Moh; Nawawi, Imam; Hoiruddin
ABDI MASYARAKAT Vol 1 No 2 (2025): PENGUATAN PENDIDIKAN DAN KEWIRAUSAHAAN
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) STAI Nahdlatul Ulama (STAINU) Malang

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

Abstract

Penelitian ini mengkaji praktik jual beli jambu air di Desa Dharma, Camplong, Sampang, yang masih menghadapi berbagai kendala. Melalui metode kualitatif berupa observasi, wawancara, dan dokumentasi, ditemukan bahwa petani berada pada posisi tawar yang lemah karena harga sepenuhnya ditentukan tengkulak, akses pasar terbatas, serta belum adanya sistem pemasaran mandiri. Kondisi ini membuat keuntungan tidak terdistribusi secara adil, di mana petani hanya menerima sebagian kecil dari nilai jual sebenarnya di pasar. Dalam perspektif Islam, situasi ini menyentuh aspek keadilan dan kerelaan dalam transaksi. Sebagai solusi praktis, penelitian ini merekomendasikan pembentukan koperasi tani untuk memperkuat posisi petani, penerapan akad jual beli yang lebih transparan, serta pemanfaatan media sosial untuk memperluas akses pemasaran dan meningkatkan kesejahteraan petani.
OPTIMISASI PEMILIHAN FITUR UNTUK PREDIKSI GAGAL JANTUNG: FUSION RANDOM FOREST DAN PARTICLE SWARM OPTIMIZATION Nawawi, Imam
INTI Nusa Mandiri Vol. 18 No. 2 (2024): INTI Periode Februari 2024
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v18i2.5031

Abstract

Heart failure is a serious, life-threatening cardiovascular disease that increases with age and unhealthy lifestyles. Early prediction is essential to provide timely treatment and reduce mortality. The use of machine learning techniques, especially the Random forest (RF) method, for predicting heart failure has been previously researched, so the problem that occurs is that the RF method does not have maximum results because of irrelevant features. Selection of relevant features is a key step in building an accurate prediction model. Particle Swarm Optimization (PSO) is used to improve feature selection by searching for optimal combinations. The aim of the research is to reduce the mortality rate by improving the RF method with relevant features so as to increase the accuracy of predictions with Fusion RF and PSO. The results show an increase in accuracy of 02.78% to 87.33% with PSO, although the AUC decreased by 0.031%. The advantage of PSO is a significant increase in accuracy, but the disadvantage is a slight decrease in AUC. Future developments could explore how to address AUC degradation without compromising accuracy and transmitting additional relevant features.
The Analysis of Character Identity in “The Woman in The Window” Novel by A. J. Finn Nawawi, Imam; Satria, Robby
INTERACTION: Jurnal Pendidikan Bahasa Vol. 11 No. 1 (2024): INTERACTION: Jurnal Pendidikan Bahasa
Publisher : Program Studi Pendidikan Bahasa Inggris, Universitas Pendidikan Muhammadiyah Sorong

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

Abstract

This study delves into the exploration of character identity within A.J. Finn's psychological thriller "The Woman in the Window," focusing particularly on the protagonist, Dr. Anna Fox. Employing a comprehensive research methodology, including textual analysis, character profiling, literary examination, comparative analysis, psychological insights, reader response, and an interdisciplinary approach, the study unveils the intricate and multi-dimensional nature of the novel's characters. The findings contribute to a deeper understanding of character identity in the psychological thriller genre. The analysis reveals key themes such as unreliable narration, trauma's profound influence, external impacts on character development, the theme of the fragmented self, and deliberate narrative ambiguity. These elements, exemplified through Dr. Anna Fox's character, showcase the complexities inherent in character identity. Furthermore, the study extends its scope to a comparative analysis of psychological thriller novels, reader response studies, comparative character studies across genres, and an analysis of the author's intent. This multi-faceted approach enriches our understanding of character identity within psychological thrillers and underscores the enduring significance of the genre in contemporary literature. In conclusion, this research emphasizes the complex interplay of narrative techniques in shaping character identity, particularly exemplified through Dr. Anna Fox, and highlights the enduring relevance of psychological suspense literature in contemporary contexts.
Co-Authors A.A. Ketut Agung Cahyawan W ACHMAD RIFAI Akhmad Jayadi Anus Wuryanto Aris Risdiana, Aris Azis, Mochammad Abdul Bastari, Winarno Fadjar Cahyaningsih, Annisa Dewi Yuliandari Djoko Dwi Kusmayanto, Djoko Dwi Eka Intan Kumala Putri Faisal Rahutomo Fauzi Ahmad Muda Ginabila Hafis Nurdin Hani, Siti Hari Sugiarto - UBSI Hatmoko, Bondan Dwi Hilda Rachmi Hoiruddin Ismailah, Ismailah Khorofi, Moh Larasaty, Hartaty Luthfi Maulana, Luthfi Mahmudah Mahmudah Makbul Muksar Maruloh, Maruloh Muhammad Darussalam, Muhammad Nurlaela, Siti Hani Parama Diptya Widayaka Prasetyo, Rizal Priyanti, Widi Intan Putra Prima Arhandi, Putra Prima Putri Mahanani, Putri Ramadhan, Reza Bakhtiar Riadi, Ahsan Risa Wati - AMIK BSI Tasikmalaya Risa Wati - AMIK BSI Tasikmalaya Rohmah, Diah Aulia Azizatur Sabiq, Mohammad Satria, ROBBY Siti Komariah Solichin Solichin Sudrajad, Ahmad Wahyu Sukmawati Anggraeni Putri, Sukmawati Anggraeni Wasil, Mohammad Wibowo, Teguh Setiawan Yadi Ruyadi