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Aplikasi Sistem Akuntansi Rekapitulasi Pendapatan pada Perusahaan Daerah Air Minum (PDAM) Tirtauli Pematangsiantar Tanjung, Sindi Raharjo; Suhendro, Dedi
Petik: Jurnal Pendidikan Teknologi Informasi Dan Komunikasi Vol. 6 No. 1 (2020): Volume 6 No 1 Tahun 2020
Publisher : Pendidikan Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/petik.v6i1.1144

Abstract

Abstrak — Perusahaan Daerah Air Minum (PDAM) Tirtauli Pematangsiantar digolongkan sebagai perusahaan negara yang memiliki tujuan operasional untuk memenuhi kebutuhan masyarakat. Pendapatan pada Perusahaan Daerah Air Minum (PDAM) Tirtauli terbagi menjadi dua, yaitu penerimaan air dan pendapatan non-air. Rekapitulasi pendapatan perusahaan Daerah Air Minum (PDAM) Tirtauli Pematangsaiantar masih menggunakan aplikasi Microsoft Excel di mana aplikasi masih sering kesalahan dalam rekapitulasi pendapatan. Berdasarkan hal ini, penulis merancang program aplikasi sistem akuntansi pendapatan rekapitulasi dengan menggunakan Microsoft Basic Net dan database MySQL untuk menghasilkan aplikasi lebih baik dibandingkan yang sedang berjalan. Aplikasi sistem akuntansi rekapitulasi pendapatan menggunakan Microsoft Visual Basic Net dirancang untuk menghasilkan suatu aplikasi yang lebih baik dengan menggunakan database MySQL yang didesain untuk melakukan proses manipulasi database dengan berbagai fasilitas. Tujuan penulis merancang aplikasi untuk mempermudah User dalam melakukan rekapitulasi pendapatan dengan sistem aplikasi Visual Basic Net sehingga dapat membantu atau mempermudah proses penginputan rekapitulasi pendapatan. Kata Kunci — Aplikasi, Rekapitulasi Pendapatan, Microsoft Visual Basic Net, Database MySQL. Abstract — The Tirtauli Pematangsiantar Regional Water Company (PDAM) is classified as a state-owned company that has operational objectives to meet the needs of the community. Revenues at the Tirtauli Regional Water Company (PDAM) are divided into two, namely water revenues and non-water revenues. Regional income recapitulation Tirtauli Pematangsaiantar still uses Microsoft Excel application where the application is still often an error in revenue recapitulation. Based on this, the authors designed a recapitulation income accounting system application program using Microsoft Basic Net and MySQL database to produce applications better than those running. Application of income recapitulation accounting system using Microsoft Visual Basic Net is designed to produce a better application using a MySQL database designed to perform database manipulation processes with various facilities. The purpose of the authors designed the application to facilitate the User in recapitulation of income with the Visual Basic Net application system so that it can help or simplify the process of inputing income recapitulation. Keywords — Application, Revenue Recapitulation, Microsoft Visual Basic Net, MySQL Database.
Harnessing Diversity: The Role of Inclusive HR Practices in Driving Innovation and Organizational Growth Qurniawan, Hendry; Saragihi, Ilham Syahputra; Suhendro, Dedi
INVEST : Jurnal Inovasi Bisnis dan Akuntansi Vol. 5 No. 1 (2024): INVEST : Jurnal Inovasi Bisnis dan Akuntansi
Publisher : Lembaga Riset dan Inovasi Al-Matani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/invest.v5i2.1014

Abstract

This study explores the impact of inclusive human resource practices and workforce diversity on organizational growth, with a focus on the mediating role of innovation capability. Using data from Balai Pengelola Transportasi Darat Kelas II Provinsi Sumatera Barat, the research employs a quantitative design with random sampling, resulting in 78 respondents from a population of 352. Path analysis, conducted using SmartPLS, reveals significant direct and indirect effects of inclusive human resource practices and workforce diversity on organizational growth, mediated through innovation capability. Inclusive human resource practices significantly enhance innovation capability, which in turn drives organizational growth. Similarly, workforce diversity contributes to organizational growth by improving innovation capabilities. These findings highlight the importance of fostering an inclusive and diverse work environment to promote innovation and achieve sustainable organizational success.
JARINGAN SARAF TIRUAN UNTUK MEMPREDIKSI PERMOHONAN INSTALASI LISTRIK MENGGUNAKAN ALGORITMA BACKPROPAGATION Suhendro, Dedi; Pramesti, Adinda Frizy
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4303

Abstract

PT. PLN (Persero) sebagai perusahaan BUMN di Indonesia yang bertanggung jawab menyediakan dan mengelola pasokan listrik. Perusahaan ini pun merupakan satu-satunya perusahaan milik Negara yang menyediakan jasa ketenagalistrikan, sehingga mempunyai hak eksklusif untuk menjual tenaga listrik di Indonesia. Masalah yang timbul adalah pada penyediaan perlengkapan atau alat untuk membangun saluran listrik baru,  minimnya tenaga kerja dan terbatasnya jumlah instalasi per hari. Perlu dilakukan perkiraan untuk mengetahui jumlah permohonan instalasi listrik dimasa mendatang. Data perkiraan tersebut sesuai dengan jumlah kebutuhan instalasi listrik di wilayah kerja PT. PLN (Persero) UP3 Pematang Siantar Januari s/d Agustus 2023. Algoritma yang digunakan untuk prediksi adalah jaringan syaraf tiruan backpropagation. Algoritma backpropagation ini menggunakan lima model arsitektur diantaranya 6-20-1, 6-30-1, 6-40-1, 6-50-1 dan 6-60-1. Di antara kelima model arsitektur yang digunakan, dipilih arsitektur terbaik yaitu 6-30-1 yang mempunyai akurasi 90%, MSE 0,000998854 dan tingkat error yang digunakan 0,001-0,25. Oleh karena itu, model arsitektur ini cukup efektif untuk memprediksi jumlah permohonan instalasi listrik.
PREDIKSI BEBAN TRAFO PADA PT PLN (PERSERO) UP3 SUMATERA UTARA MENGGUNAKAN ALGORITMA BACKPROPAGATION Suhendro, Dedi; Batu Bara, Dinda Rizki
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5173

Abstract

Perusahaan BUMN yang bergerak dibidang pembangkitan dan pendistribusian listrik merupapakan perusahaan PT PLN (Persero) yang berusaha memberikan pelayanan terbaik kepada semua pelanggan mengingat tingginya kebutuhan masyarakat terhadap tenaga listrik dari waktu ke waktu. Masalah yang timbul dari Jenis gangguan yang sering terjadi pada trafo diantaranya, tegangan lebih akibat petir, overload dan  beban tidak seimbang, loss contact pada terminal bushing, bushing pecah, gangguan hewan, dan gangguan tumbuhan. Setiap trafo menurut trafo daya memerlukan pemeliharaan dan perbaikan baik secara berkala maupun tiba-tiba akibat berbagai gangguan dan kerusakan, maka dilakukan pemeliharaan secara berkala, agar trafo tidak mengalami kerusakan dan gangguan saat operasi. Data pemeliharaan tersebut sesuai dengan jumlah beban trafo pada wilayah kerja PT. PLN (Persero) UP3 Pematang Siantar. Algoritma yang digunakan untuk prediksi adalah jaringan syaraf tiruan backpropagation. Algoritma backpropagation ini menggunakan lima model arsitektur diantaranya 4-10-1-1,4-15-1-1,4-20-1-1,4-75-1-1 dan 4-100-1-1. Di antara kelima model arsitektur yang digunakan, dipilih arsitektur terbaik yaitu 4-15-1-1 yang mempunyai akurasi 63.63%, Epoch sebesar 3478, MSE Pengujian 0.0039047, MSE Pelatihan 0.0009999. Oleh karena itu, model arsitektur ini cukup efektif untuk memprediksi jumlah beban trafo sesuai daya trafonya.
Implementasi Algoritma Backpropagation Untuk Prediksi Jumlah Siswa SMA Salis, Rahmi; Windarto, Agus Perdana; Suhendro, Dedi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7774

Abstract

Senior High School (SMA) is one form of formal education unit that organizes general education at the secondary education level as a continuation of Junior High School (SMP). The number of high school students in Pematangsiantar City has decreased and increased from year to year. The factors causing the decrease and increase in the number of students are economic factors, population growth rate, distance from home, age, low quality of schools, lack of teachers and teaching media. This is because the number of students is very influential in determining when additional teachers, classrooms, textbooks and teaching media are needed to support the learning process. This study aims to predict the number of high school students in Pematangsiantar City. The dataset used is a dataset of the number of high school students in Pematangsiantar City in 2019-2023 obtained from the Ministry of Education, Culture, Research and Technology (Dapodik) website https://dapo.kemdikbud.go.id/pd/2/076300. The dataset is then divided into 2 parts, namely training and testing datasets. The algorithm used in the research is the Backpropagation algorithm with 6 architectural models, namely 4-15-1, 4-25-1, 4-45-1, 4-55-1, 4-75-1, and 4-85-1. The results of this study obtained the best architectural model, namely 4-25-1 with an accuracy level of 87.5%, Epoch 65, MSE Training 0.000967055, and MSE Testing 0.001440343. Based on this best architecture model will be used to predict the number of high school students in Pematangsiantar City for 2024.
Penerapan Algoritma K-Means Dalam Mengelompokkan Rata-Rata Konsumsi Kalori Menurut Provinsi Sinaga, Juwitha Lovely Sweets; Solikhun, S; Suhendro, Dedi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.272

Abstract

Calories are a source of energy that we get from food intake that contains nutrients and as a basic human need for humans to survive. The number of people who consume excessive calories and do not pay attention to the amount of calorie intake that is consumed will result in the emergence of various diseases that are bad for health. In this case the government does not have information about the data on the average calorie consumption per province by province. The purpose of this study is to determine the highest and lowest clusters, for that the authors use Data Mining with the K-Means Algorithm to classify Average Calorie Consumption per day by province. This test is carried out using RapidMiner software. The results were obtained from the average grouping of calorie consumption grouped by two clusters: high and low clusters, high clusters of 13 provinces and low clusters of 21 provinces. Provinces that are classified as low clusters are expected to be a contribution for the Indonesian government for decision making in an effort to maintain a balanced consumption of calories per day and create a healthy lifestyle program in the future.
Implementasi Metode K-Means pada Hasil Produksi Daging Jenis Ternak Saragih, Siti Nurmila; Safii, M; Suhendro, Dedi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.288

Abstract

Meat production results should have good quantity and quality. To increase meat production, of course it is necessary to look at healthy types of livestock. Meat continues to increase in line with the increase in population, community income, education, standard of living and awareness of the nutritional value of animal production. The need for livestock meat production is one of the driving factors for the economy in Indonesia. This research can provide and input to the local government which is the leading producer of meat for the type of livestock in North Sumatra province and as a basis for making policies to increase meat production for other provinces. The method used in this research is the K-Means Algorithm. Where K-Means is one of the Algorithms in Data Mining that can be used to group data clusters. So that the data from 33 districts / cities will be divided into 2 clusters where cluster 1 is the high group, while cluster 2 is the low group. The results obtained from the study show that the results of manual calculation Algorithms and Microsoft Excel data have the same value, namely high cluster 1 and low cluster 32, and entering Microsoft Excel calculations into rapidminer has the same value as well
Penerapan Algoritma K-Means dalam Proses Clustering Penilaian Kinerja Aparatur Sipil Negera di Sekretariat DPRD Pematangsiantar Aulia, Della; Safii, M; Suhendro, Dedi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.270

Abstract

This study discusses the assessment of the performance of the ASN (State Civil Apparatus) in the Pematangsiantar DPRD Secretariat based on the quality of its work. In carrying out their performance, emoployess are still often truant and have a poor work ethic.In this case the research aims to improve employee welfare. During this time the amount of employee income is only based on the group and position they have. This study uses the K-Means method to classify or classify employee performance quality assessments based on SKP (employee work objectives) with additional income based on work quality assessment and employee behavior.After conducting this research there is a result that in carrying out the performance of employees include Quality, Quantity, Time, Cost of each task activity so as to produce a system capable of assisting the appraisal officer in evaluating the quality of employee performance using the K-Means algorithm as information to find out the employee including very good, enough, and less.
Pengelompokkan Sumber Air Minum Dari Air Sungai Menggunakan Metode K-Means Sinaga, Sabrina Biutiqwin; S, solikhun; Suhendro, Dedi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.289

Abstract

River water is one of the most frequently used water by the community and has a multipurpose function for life, one of which is a source of drinking water. However, now we know that the population of river water pollution is very high and it is used as a waste disposal site which causes a lot of river water to be polluted, it can make people susceptible to disease because they consume unhealthy river water. Judging from the data obtained by province, many use river water as a source of drinking water, for this reason the authors conducted a study that aims to classify drinking water sources from river water by province using the K-means Clustering algorithm and will test it with the Rapidminer application, so that Data from 34 provinces will be divided into 3 clusters in which cluster 1 (C1) is a high group, cluster 2 (C2) is a medium group, and cluster 3 (C3) is a low group. The results obtained from this study are C1 with a total of 2 provinces, C2 with a total of 9 provinces, C3 with a total of 23 provinces and the value of the results carried out with the Rapidminer application has the same value. With this research, it is hoped that this can provide information for the government about the data on the grouping of drinking water sources and used as a consideration for overcoming polluted rivers.
Penerapan Data Mining Algoritma C4.5 Terhadap Prediksi Faktor Menurunnya Hasil Panen Padi Siahaan, Nove Viktor Boyke; Poningsih, P; Suhendro, Dedi; Hartama, Dedy; Suhada, S
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 7, No 1 (2022): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v7i1.412

Abstract

The aim of the study was to predict the factors causing the decline in rice yields. By knowing the factors of declining rice yields, business owners can further evaluate the causes of declining rice yields and then look for solutions on how to overcome them. The method used in this study is the C4.5 Algorithm, the source of the data used is primary data obtained by direct interviews with rice mill owners and farmers in Siborna Village, Kec. Panei Kab. Simalungun Prov. North Sumatra. The variables used include (1) Pests, (2) Rice Grains, (3) Leaf Color, (4) Planting Month and (5) Planting Method. The results obtained 8 rules for the classification of factors causing the decline in rice yields with 3 increasing decision rules and 5 decreasing decision rules with an accuracy rate of 93.33%. It can be concluded that the predictor of the decline in rice yields is based on the connectedness of the Attributes of Planting Month, Pests, Rice Grains, Leaf Color and Planting Methods.