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Pengaruh Beban Kerja dan Stres Kerja Terhadap Kinerja Karyawan Pada PT Asian Agri Singingi Hilir Kabupaten Kuantan Singingi Yulita, Rahma; Wahab, Wirdayani; Menhard, Menhard; Irawan, Candra
Jurnal Akuntansi, Manajemen, Bisnis dan Teknologi Vol 4 No 1 (2024): Jurnal Akuntansi, Manajemen, Bisnis dan Teknologi - Edisi Februari 2024
Publisher : Sekolah Tinggi Ilmu Ekonomi Mahaputra Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56870/ambitek.v4i1.132

Abstract

The purpose of this study was to determine and analyze the effect of workload and work stress on employee performance partially and simultaneously at PT Asian Agri Singingi Hilir. The population in this study amounted to 40 people taken from production employees, while the sample in this study amounted to 40 people using the census method. The analysis in this study used multiple linear regression. Based on the results of the study where the tcount> ttable value is 2.320> 2.02619 and the significance level is 0.026 <0.05, which means that workload partially affects the performance of PT Asian Agri Singingi Hilir office staff employees. Workload with tcount> ttable or 4.225> 2.02619 with a significance level of 0.00 <0.05 which means that workload partially affects the performance of employees of the office staff of PT Asian Agri Singingi Hilir. Workload and work stress have a simultaneous influence on employee performance at PT Asian Agri Singingi Hilir with a calculated F value of 33.931> F-tab of 3.25 with sig. (0,000) < 0.05. Adjusted R Square of 0.628 or 62.8%, this means that 62.8% of the employee performance variable can be explained or influenced by workload and work stress variables. While the remaining 37.2% is influenced by other variables not examined.
Klasifikasi Citra Mengkudu Berdasarkan Perhitungan Jarak Piksel pada Algoritma K-Nearest Neighbour Irawan, Candra; Rachmawanto, Eko Hari; Atika Sari, Christy; Umah Nur, Raisul
Infotekmesin Vol 14 No 2 (2023): Infotekmesin: Juli, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i2.1827

Abstract

Noni fruit is included in exported food commodities in Indonesia. The size of noni fruit, based on human vision, generally has varied shapes with distinctive textures and various patterns, so that the process of filtering fruit based on color and shape can be done in large quantities. In this study, K-Nearest Neighbor (KNN) has been implemented as a classification algorithm because it has advantages in classifying images and is resistant to noise. Noni imagery is a personal image taken from a noni garden in the morning and undergoes a background subtraction process. The imagery quality improvement technique uses the Hue Saturation Value (HSV) color feature and the Gray Level Co-Occurrence Matrix (GLCM) characteristic feature. KNN accuracy without features is lower than using HSV and GLCM features. From the experimental results, the highest accuracy was obtained using HSV-GLCM at K is 1 and d is 1, namely 95%, while the lowest accuracy was 55% using KNN only at K is 5 and d is 8.
Pengujian Aplikasi Website Sekolah Menggunakan Selenium WebDriver Kusyadi, Irpan; Firmansyah, Aksal; Irawan, Candra; Aziz, Fuad Abdul; Sidhiq, Restu Fajar; Munawaroh, Munawaroh
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 2 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

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

Abstract

Terdapat permasalahan dalam proses garansi perangkat lunak yang terjadi ketika terjadi kesalahan pada server produksi pada saat proses verifikasi, diantaranya pembuatan data buatan, membutuhkan waktu untuk menguji fungsi masalah dan juga untuk mencari data terkait pengguna. mengambil beberapa langkah untuk meningkatkan efisiensi dan efektivitas. Model pengembangan perangkat lunak yang digunakan yaitu Extreme Programming, paradigma pemrograman yang digunakan didasarkan pada pemrograman prosedural dan mengikuti konsep imperatif. Hasil penelitian ini menunjukkan bahwa penggunaan perangkat lunak otomatisasi otentikasi dalam situs web berbasis otorisasi dapat menyederhanakan dan meningkatkan proses jaminan kualitas software, pengujian kompatibilitas, dimana menunjukkan bahwa sistem dapat berjalan atau digunakan dengan benar di beberapa browser.
Pelatihan Pembuatan Pupuk Kompos pada IKM ARG Desa Pesawahan Kabupaten Garut Suhartini, Suhartini; Irawan, Candra; Sukiman, Maman; Rosalina, Rosalina; Utami, Andita; Putri, Imalia Dwi; Septian, Wira Aditia; Azhar, Kheiza Noor Aulia; Alhafish, Muhammad Radhi; Pramudya, Muhammad Kemal Caesar Aqidah
Jurnal Pengabdian Masyarakat AKA Vol 3, No 2 (2023): Desember 2023
Publisher : Politeknik AKA Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55075/jpm-aka.v3i2.176

Abstract

Livestock waste is still a problem that demands government attention. One of the livestock wastes that cause pollution comes from the cultivation of rabbits. The variation in the number of processed rabbits causes an increase in demand for the number of rabbits, which will be proportional to the amount of waste produced, both in the form of manure and leftover feed. One of the efforts to control rabbit farm waste can be done by processing it into compost. This community service activity aims to provide skills in making compost made from manure and rabbit feed to the Pesawahan Village community, who are members of IKM ARG using Effective Microorganism 4 (EM4) and Trichoderma activators. Training activities are carried out through three stages, namely pre-implementation which includes an initial survey and situation analysis, the implementation stage which consists of outreach and composting training, and evaluation of the results of activities. The results of the training showed that the compost from the training was smoother and moister than the IKM ARG fertilizer before the training was given. Based on the results of the questionnaire, it is known that IKM ARG members are interested in applying the results of the training to produce compost.
Closing the Loop: Goal Programming-Based Optimization in a Tofu-Centered Agro-Eco-Industrial Park Putri, Ade Aisyah Arifna; Purwaningsih, Ratna; Azzahra, Faradhina; Hartini, Sri; Irawan, Candra; Oryzanti, Parwa
Spektrum Industri Vol. 23 No. 2 (2025): Spektrum Industri - October 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v23i2.396

Abstract

Developing an agro-eco-industrial park based on the tofu industry must consider the balance of each agro-industry's production capacity. This research aims to (1) develop an optimization model for material flow between industries and (2) explain the material flow and provide waste utilization recommendations for other industries to create a closed loop. The industries involved in this agro-eco-industrial park consist of the tofu industry, fertilizer producers, tempeh gembus producers, cattle farms, biodigesters, paddy farmers, soybean producers, and nata de soya producers. The model was created using a goal programming approach. Traditional tofu processing generally generates a variety of waste with high nutritional value, but it is detrimental to the environment if disposed of directly. The flow of materials among the related industries is based on the tofu industrial cluster, which consists of 30 industries in Grobogan, Central Java, Indonesia. The expected output comprises eight decision variables representing the production amount of industries. Data analysis reveals that the model outperforms the current conditions, with the waste recycling rate increasing from 14 % to 97 %. This model converts waste into valuable resources such as fertilizer and gas energy through biodigester processing and other economically viable methods.
Optimization of Heart Failure Classification on Imbalanced Data Using a Supervised Learning Approach Based on Logistic Regression, Random Forest, and K-Nearest Neighbor: Optimalisasi Klasifikasi Gagal Jantung pada Data Imbalanced Menggunakan Pendekatan Supervised Learning Berbasis Regresi Logistik, Random Forest, dan K-Nearest Neighbor agustina, feri; Irawan, Candra; Erawan, Lalang; Suprayogi; Award Widya Laksana, Deddy; Jatmoko, Cahaya; Sinaga, Daurat; Lestiawan, Heru
Jurnal Informatika Polinema Vol. 12 No. 1 (2025): Vol. 12 No. 1 (2025)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v12i1.9071

Abstract

Heart failure remains one of the leading causes of mortality worldwide, posing significant challenges for early diagnosis and patient management. One of the major obstacles in developing predictive models for heart failure is the class imbalance problem, where the number of surviving patients far exceeds those who experience death events. This imbalance often leads machine learning algorithms to bias toward the majority class, reducing sensitivity to critical minority cases. To address this issue, this study applies the Synthetic Minority Oversampling Technique (SMOTE) to balance the dataset and improve model performance. Three supervised learning algorithms, namely Logistic Regression (LR), Random Forest (RF), and K-Nearest Neighbor (KNN), were implemented and compared on the UCI Heart Failure Clinical Records dataset containing 299 patient samples with 13 clinical attributes. Experimental results show that the Random Forest model achieved the highest performance with 90% accuracy, precision, recall, and F1-score, outperforming both LR and KNN. The findings demonstrate that combining data balancing with ensemble learning effectively enhances prediction accuracy and sensitivity toward minority classes. The main contribution of this research lies in optimizing supervised models for medical data with skewed class distributions, providing a more reliable and interpretable approach for early heart failure detection. Future research may extend this work by integrating advanced ensemble or hybrid deep learning models and expanding the dataset for multi-institutional validation
Co-Authors Abu Salam Agus Winarno, Agus Agustina, Feri Akbar, Ilham Januar Al-Ghiffary, Maulana Malik Ibrahim Alfany, Fauzan Maulana Alhafish, Muhammad Radhi Ali, Rabei Raad Almidawati ALQORNI, NISA Alzami, Farrikh Angow, Delicia Award Widya Laksana, Deddy Azhar, Kheiza Noor Aulia Aziz, Fuad Abdul Azzahra, Faradhina Azzami, Salman Yuris Adila Barlah Rumhayati Basri Dahlan Bima, Aristides Bimo Seto, Kahfi Akmal Janitra Cahaya Jatmoko Cahyo, Nur Ryan Dwi Caturkusuma, Resha Meiranadi Christy Atika Sari Debi, Yoga Tegar Ardi Dedy Pratama Diana Aqmala Edi Sugiarto Eko Hari Rachmawanto Eko Susanto Eni Sumanti Nasution Enriyani, Riri Fahmi Amiq Farida Farida Fikri Budiman Firmansyah, Aksal Fitri, Rahma Hadi, Heru Pramono Hari Purnama, Hari Hasbi, Hanif Maulana Henny Pratiwi Adi Heru Lestiawan Hilmansyah Huda, Masrul Ifan Rizqa Ika Novita Dewi Inzaghi, Reza Bayu Ahmad Irpan Kusyadi Isinkaye, Folasade Olubusola Jonnedi, Jonnedi Kango, Riklan Krismawan, Andi Danang Kusumawati, Yupie Laksana, Deddy Award Widya Lalang Erawan Lili Romli, Lili Lisandi, Anisa Marendra, Fajar Mariatul Kiptiah Menhard, Menhard Monica, Lala Munawaroh Munawaroh Muslih Muslih MY. Teguh Sulistyono Nawang Retno Ningrum, Amanda Prawita Nohan, Rejendra Novi Hendriyanto, Novi Nugraha, Dida Septiya Nuraini Nuraini Nurhindarto, Aris Oryzanti, Parwa Piliang, Arfah Pramudya, Muhammad Kemal Caesar Aqidah Pratama, Reza Arista Purnomo, Hari Agus Putri, Ade Aisyah Arifna Putri, Imalia Dwi Rachmat Mudiyono, Rachmat Rahmatia, Lintannisa Rajali, Muhammad Ramadhan Rakhmat Sani Randy Pradityo Rasmon Ratna Purwaningsih Rosalina Rosalina Rosalina RR. Ella Evrita Hestiandari Saputra, Randika Septian, Wira Aditia Sidhiq, Restu Fajar Simatupang, Lisnawaty Sinaga, Bunga Riama Sinaga, Daurat Solichul Huda, Solichul Sri Hartini Sri Utami Kholilla Mora Siregar Suharnawi Suharnawi Suhartini Suhartini Sukiman, Maman Sulistiana, Oktavera Sulistiyono, MY Teguh suprayogi Supriatiningsih, Supriatiningsih Sutarni, Yayan Dwi Syukri, Muhammad Yazidus Tomy Andrianto Tumanggor, Mutawaqil Bilah Ulfa, Anis Aulia Umah Nur, Raisul Utami, Andita Wibowo, Isro' Rizky Widharto, Yusuf Widya Rahmawati WIRDAYANI WAHAB, WIRDAYANI Yudi Prana Hikmat Yulita, Rahma Zaenal Arifin Zubir, Zubir