Garuda - Garba Rujukan Digital

Analisis Pengaruh Iklim Kerja dan Pemberian Insentif Terhadap Kepuasan Kerja Karyawan di Perguruan Tinggi XXX Yuwono, Sapto; Lisdiana, Lisdiana; Ahsan, Moh
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13480

Persoalan karyawan di organisasi suatu Perusahaan menjadi perhatian dari suatu organisasi tersebut untuk tetap eksis. Karyawan memiliki peran utama dan pokok dalam aktivitas organisasi. Meskipun banyak factor yang lainnya, tanpa dukungan karyawan, kegiatan organisasi tidak dapat berjalan baik. Sumber daya manusia di Perguruan Tinggi XXX adalah harta yang memiliki nilai tinggi dan penting dalam konteksnya sehingga sangat diperlukan perhatian yang serius dan berkelanjutan agar pencapaian hasil kerja secara maksimal dapat terwujud. Dukungan Pimpinan yang terlibat dalam pengelolaan sumber daya manusia sangat penting. Adanya perubahan lingkungan organisasi atau berubahnya iklim kerja yang begitu cepat menjadikan karyawan tidak dapat mengikuti irama pekerjaan. Karyawan menganggap perubahan iklim kerja memasung kreatifitas dan kebiasaan yang telah tertanam bertahun-tahun dan menganggap manajemen baru tidak lebih baik dari manajemen sebelumnya. Penelitian “Analisa Dampak Iklim Kerja dan Pemberian Insentif Pada Kepuasan Kerja menggunakan Motivasi sebagai dimensi antara di Perguruan Tinggi XXX.

Implementasi Metode Single Moving Average dan Double Moving Average untuk Memprediksi Populasi Sapi Potong di Jawa Timur Syarif Hidayat, Yusron; Aziz, Abdul; Ahsan, Moh
RAINSTEK: Jurnal Terapan Sains dan Teknologi Vol. 5 No. 3 (2023): September
Publisher : Fakultas Sains dan Teknologi Universitas Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/jtst.v5i3.9120

Berdasarkan data Dinas Peternakan yang terpublis di Badan Pusat Statistik Jawa Timur ( BPS ) menunjukkan jumlah populasi Sapi Potong di Kota / Kabupaten di Jawa Timur mengalami peningkatan dan penurunan dari tahun ke tahun. Tujuan dari penelitian ini adalah mengetahui tingkat akurasi populasi sapi potong menggunakan metode Single Moving Average (SMA) dan Double Moving Average (DMA) karena dari jurnal yang telah diperoleh peneliti menunjukkan bahwa metode Single Moving Average dan Double Moving Average memiliki nilai akurasi MAPE dibawah 10%. Metode untuk mengetahui tingkat akurasi dalam penelitian ini diuji akurasi error menggunakan Mean Absolut Deviation (MAD) dan Mean Absolut Percentage Error (MAPE). Metode Single Moving Average dan Double Moving Average dalam penelitian ini juga diimplementasikan untuk memprediksi populasi sapi potong menggunakan Python dengan hasil yang sama dengan perhitungan manual. Kualitas prediksi yang dihasilkan dalam pengujian oleh peneliti dengan data aktual pada tahun 2022 menggunakan metode SMA (Single Moving Average) dan DMA (Double Moving Average) dengan periode 3 tahun atau interval 3 berjumlah 5.018.296,00, MAD 1.876,22, dan MAPE 4,99% untuk periode 4 tahun atau interval 4 berjumlah 5.036.615,04, MAD 1.728,85, MAPE 5,97%. Berdasarkan hasil yang diperoleh dapat disimpulkan bahwa metode Single Moving Average dan Double Moving Average interval 4 atau periode 4 tahun bisa dikategorikan prediksi sangat baik dikarenakan jumlah prediksi mendekati data aktual dan nilai MAPE kurang dari 10%.

Deteksi Leukemia Limfoblastik Akut menggunakan Convolutional Neural Network Akbar, Mutaqin; Prasetyaningrum, Putri Taqwa; Setyaningsih, Putry Wahyu; Ahsan, Moh; Budianto, Alexius Endy
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 1 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i1.34168

Acute lymphoblastic leukemia is the most important type of childhood leukemia, and accounts for 25% of childhood cancers. Accurately differentiating normal cell precursors from cancer cells is key to the diagnosis of acute lymphoblastic leukemia (ALL). However, under a microscope, cancer cells are so similar to normal cells that it is difficult to classify them. This article presents a detection of acute lymphoblastic leukemia using Convolutional Neural Network (CNN). The dataset which is obtained from ALL_IDB is 582 color image data which is divided into 482 training image data and 100 testing image data. The image data will be resized to 128x128x3 before being input to the CNN model. The CNN model used in this study is a multi-scale CNN which consists of 3 convolution layers (filter size of 3x3, number of filters for each convolution layer is 32, 64, and 128 respectively, and ReLU activation function), 3 subsampling layers using maxpool with filter size of 2x2 , 1 concatenate layer is used to combine the output of each subsampling layer, 1 fully-connected layer with a softmax activation function and a cross-entropy error function, and finally an output layer with 2 classes, namely normal cells and cancer cells. The CNN model will be trained using the Adam optimizer training algorithm with a training rate of 0.0002 and iterated 20 times. Based on the training results after iterating 20 times, the smallest error value was obtained, namely 0.0001 and the largest accuracy value, namely 100% in the 20th epoch. The CNN model was then tested with 100 testing image data and obtained an accuracy rate of 98% and an error value of 0.0482.

PERANCANGAN METODE HUMAN CENTERED DESIGN USER INTERFACE DAN USER EXPERIENCE PADA SISTEM HARGA KEBUTUHAN POKOK KABUPATEN MALANG Eka Wahyudi, Desantara; Budianto, Alexius Endy; Ahsan, Moh
Jurnal Fakultas Teknologi Informasi Vol 8 No 1 (2025): BIMASAKTI
Publisher : Prodi Teknik Informatika, Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v8i1.12516

The Ministry of Communication and Information with all its diverse society requires overlapping in terms of equalizing services, especially in terms of data information. The problem is caused by inaccurate data information so that the asset data used as the basis of the data affects the data information received which does not match the field conditions. The running of data processing so far is still based on technicalities that tend to be conventional so that a capable system is needed to accommodate the problem. By using a mixed method, this study uses Human Centered Design as the basis for designing an application design called SIHARKEPO (Basic Needs Price Information System). This study will later focus on two main problems, namely the SIHARKEPO user interface design process and the analysis of users of the Basic Needs Price Information System (SIHARKEPO) in providing data information to users. The results of this study are concrete applications that can be applied to the process of providing basic needs price information data services and make it easier for the public to obtain them.

IMPLEMENTASI MEDIA ONLINE (WEBSITE) SEBAGAI PUBLIKASI POTENSI DESA SIDODADI MELALUI PEMBERDAYAAN KARANG TARUNA Ahsan, Moh; Aziz, Abdul
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 1, No 2 (2018): MARTABE : JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v1i2.36-41

Sidodadi Village is one of the villages located in southern Malang area located in Gedangan sub-district. The village is one of the villages that has the most extraordinary natural potentials such as Ungapan Beach, Bajulmati Beach, Parangdowo Beach, Jolangkung Beach, Bengkung Beach, Ngudel Beach, and Ngantep Beach, which is a beach located in the southern cross of Malang Regency. Rows of mountains are sturdy and beautiful to make the tourists interested to travel there.Sidodadi village area bounded with Sumbermanjing wetan district in the east, village elephant rejo in the west. On the other hand, not only the potential of nature is extraordinary, but the results of the abundant earth. Rice, corn, coconut, banana, rice, cassava, mangosteen, durian, and palm are natural products that can be processed there. The potential possessed and remarkable until now has not been published or promoted through websites and social media, to hog the visitors who more aplagi most visitors see the first reference before coming directly.The abundant natural resources with the stammered human resources of technology will make the potential of nature unknown to the wider community. Coral cadets and devices in the village of Sidodadi maximal educated High School (SMA) and only two people who can take the bench lecture. This is where the turmoil experienced by villagers Sidodadi where they can not publish the area. Only limited to the beaches that have been published, but for other natural potentials can not be published because of lack of knowledge about the use of the internet (Online Media).Â Keywords:Sidodadi, Karangtaruna, Publikasi, Online.

Pemanfaatan Techno-Pest Control Berbasis IoT Untuk Membasmi Hama Padi di Area Persawahan Pondok Condongcatur Ratnawati, Dianna; Setuju; Zamroni; Purnomo, Sigit; Ahsan, Moh
Jurnal Pemberdayaan Masyarakat Vol 5 No 2 (2020): November
Publisher : Direktorat Penelitian dan Pengabdian kepada Masyarakat (DPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/jpm.v5i2.4699

Planthopper and grasshopper pests that attack rice plants in the Padukuhan Pondok rice fields, Condongcatur have an impact on decreasing productivity of rice farmers. The objectives of this community service are: (1) to produce an IoT-based techno-pest control device by utilizing solar cells as power supply; (2) increasing the skills of farmers in using efficient technology that is economical, modern and environmentally friendly. The methods used include experimentation, socialization and training. This community service activity is the manufacture of IoT-based techno-pest control tools and tool dissemination. The dissemination activity was successfully held and attended by 50 participants from the farmer's group of culinary sources, the participants actively asked questions and were enthusiastic in practicing the operation of the tools. 85% of participants can operate the equipment in groups. Techno-pest control tools can eradicate planthoppers and grasshoppers at a radius of 6m within 4 hours via 40kHz ultrasonic waves. This tool is integrated on the internet to monitor the situation of rice fields by accessing the website http://pkm.ptm.ustjogja.ac.id.

PENERAPAN METODE NAÏVE BAYES DAN SUPPORT VECTOR MACHINE PADA ANALISIS SENTIMEN NETIZEN DI TWITTER VOLLEY BALL INDONESIA Ginanjar, Wismo; Budianto, Alexius Endy; Ahsan, Moh
Jurnal Fakultas Teknologi Informasi Vol 8 No 2 (2026): BIMASAKTI
Publisher : Prodi Teknik Informatika, Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v8i2.12376

Social media has become an integral part of modern society, offering a platform for public opinion expression. In Indonesia, volleyball is a very popular sport, and Volley Ball Indonesia is the main topic of discussion on social media, especially Twitter. This study aims to analyze the sentiment of netizen comments on the official Twitter account of Volley Ball Indonesia (@volleyball.indonesia) using the Naive Bayes method and Support Vector Machine (SVM). The data used amounted to 2,920 comments from 50 posts in the period of September 28, 2023 - May 10, 2024, focused on the U-23 and Senior Men's National Team matches. Naïve Bayes and SVM were chosen because both are effective methods in sentiment classification. Naïve Bayes uses a probabilistic approach, while SVM looks for the best hyperplane to separate data classes. The results of the study show that both methods can be used to analyze sentiment with a good level of accuracy. The test results on each training data and testing data with different presentations will provide different accuracy results. The test results of the Naive Bayes method obtained the highest accuracy value of 71% with a ratio of 70:30 and the Support Vector Machine obtained the highest accuracy value of 76% with a ratio of 80:20. So it can be concluded that the Support Vector Machine method gets a higher accuracy value than the Naive Bayes method.

OPTIMALISASI ANALISIS SENTIMEN FILM PADA YOUTUBE DENGAN ALGORITMA CHI-SQUARE PADA NAÏVE BAYES DAN SUPPORT VECTOR MACHINE Wardana, Oky Kurnia; Budianto, Alexius Endy; Ahsan, Moh
Jurnal Fakultas Teknologi Informasi Vol 8 No 1 (2025): BIMASAKTI
Publisher : Prodi Teknik Informatika, Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v8i2.12377

The management of correspondence and monthly reports in educational administration environments still faces efficiency issues due to workflows that do not align with user needs and insufficient attention to usability aspects. These conditions result in suboptimal performance and low effectiveness in the use of digital systems. This study aims to analyze the usability of the web-based SIRATU application using the User-Centered Design (UCD) approach in accordance with the ISO 9241-210 standard. The research method includes analysis of the context of use, user identification, interface design, and usability evaluation using the System Usability Scale (SUS). The study is limited to the primary users of the SIRATU application, namely administrative staff, school operators, and the head of the district education office, with a focus solely on usability aspects. The evaluation results show an increase in the average SUS score from 60.6 to 87.4, which falls into the excellent category. The contribution of this study lies in the application of a UCD methodological framework that has proven effective in improving the usability of the SIRATU application.

ANALISIS PERANCANGAN UI/UX PADA SISTEM TERINTEGRASI DATA PENDUDUK KABUPATEN MALANG (SI-CANTIK) MENGGUNAKAN METODE HUMAN CENTERED DESIGN Presetia, Ahmad Yudha; Budianto, Alexius Endy; Ahsan, Moh
Jurnal Fakultas Teknologi Informasi Vol 8 No 1 (2025): BIMASAKTI
Publisher : Prodi Teknik Informatika, Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v8i2.12517

The management of correspondence and monthly reports in educational administration environments still faces efficiency issues due to workflows that do not align with user needs and insufficient attention to usability aspects. These conditions result in suboptimal performance and low effectiveness in the use of digital systems. This study aims to analyze the usability of the web-based SIRATU application using the User-Centered Design (UCD) approach in accordance with the ISO 9241-210 standard. The research method includes analysis of the context of use, user identification, interface design, and usability evaluation using the System Usability Scale (SUS). The study is limited to the primary users of the SIRATU application, namely administrative staff, school operators, and the head of the district education office, with a focus solely on usability aspects. The evaluation results show an increase in the average SUS score from 60.6 to 87.4, which falls into the excellent category. The contribution of this study lies in the application of a UCD methodological framework that has proven effective in improving the usability of the SIRATU application.

PENERAPAN ALGORITMA LOGISTIC REGRESSION UNTUK KLASIFIKASI PENYAKIT STROKE Amelia, Rachel Trivica; Nugraha, Danang Aditya; Ahsan, Moh
Jurnal Fakultas Teknologi Informasi Vol 8 No 2 (2026): BIMASAKTI
Publisher : Prodi Teknik Informatika, Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v8i2.13201

Stroke is one of the leading causes of death worldwide, ranking after heart disease and cancer. Early detection of stroke risk is essential to enable faster and more accurate treatment. The purpose of this study is to apply the Logistic Regression algorithm to classify stroke cases based on several risk factors, including gender, age, hypertension, heart disease, marital status, occupation, residence type, average glucose level, body mass index (BMI), smoking status, and stroke status. The dataset used in this research was obtained from Kaggle and consists of 5,110 patient records. The research process involves several stages, including data cleaning, data transformation, and normalization using the Min-Max Scaler method, followed by splitting the data into training and testing sets with various proportions (90%-10%, 85%-15%, 80%-20%, 70%-30%, and 65%-35%). The evaluation was conducted using a Confusion Matrix with performance metrics such as accuracy, precision, recall, and F1-score. The analysis results show that the 90%-10% data split achieved the highest accuracy of 76.17%, with precision and recall values indicating that the model performs well in identifying non-stroke cases. However, performance on the minority class (stroke) remains relatively low, suggesting the need for improvement through data imbalance handling. Overall, the application of the Logistic Regression algorithm proved to be effective for initial stroke classification, although accuracy can still be improved through resampling techniques or advanced model optimization.

Title

Found 10 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 10 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 10 Documents
Search