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Sinaga, Kalvin
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Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mathematics Physics Social Sciences

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Hubungan Persepsi Pengembangan Karier Dengan Kinerja Karyawan PT. Jaya Tama Inovasi Agro Indonesia Henny Pratiwi; Sinaga, Kalvin; Riyadh, Muhammad Ilham
Jurnal Sains dan Teknologi Vol. 5 No. 1 (2023): Jurnal Sains dan Teknologi
Publisher : CV. Utility Project Solution

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

Abstract

This study aims to determine the relationship between perceptions of career development and the performance of . Jaya Tama Inovasi Agro Indonesia employees. The population of this study were employees in 3 fields, namely the education administration section, the marketing administration section and the work placement administration, totaling 55 people. The research sample uses a saturated sample system where the total population is used as a sample in the study. This study uses one scale, namely the career development perception scale. While the employee performance scale of the documentation method was taken in the HRD section of the . Jaya Tama Inovasi Agro Indonesia. On the career development perception scale consists of 4 aspects, namely responsibility, position status, authority, and compensation and employee performance scale is work quantity, work quality, work attendance and work timeliness. Data collection uses one psychological scale, namely the Career Development Perception Scale ( 40 items were declared valid with a value of r count > r table (0.3) and all items were declared reliable with a Cronbach alpha value of 0.916). The results of this study showed a correlation coefficient rxy 0.778 with p = 0.000 (p <0.01). These results indicate that the hypothesis put forward by researchers is that there is a positive relationship between perceptions of career development and the performance of . Jaya Tama Inovasi Agro Indonesia employees. The positive correlation coefficient value indicates that the direction of the relationship between the two variables is positive, meaning that the more positive the perception of career development, the better the performance of the . Jaya Tama Inovasi Agro Indonesia employees. Perceptions of career development make an effective contribution of 60.6% to the performance of . Jaya Tama Inovasi Agro Indonesia and 39.4% are influenced by other factors not examined in this study.
Edukasi Gagasab Anti Korupsi dan Kreatifitas Kerajinan Tangan Pada Siswa-Siswi MIS Terpadu Al-Ikhwan Deli Serdang Pratiwi, Henny; Sinaga, Kalvin; Sulaiman, Fahmi
Jurnal Masyarakat Indonesia (Jumas) Vol. 2 No. 01 (2023): Jumas : Jurnal Masyarakat Indonesia
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jumas.v2i01.34

Abstract

Pelaksanaan Pengabdian kepada Masyarakat ini bertujuan untuk: 1) mendeksripsikan implementasi kebijakan Pendidikan Anti Korupsi dan Kerajinan Tangan di MIS Al-Ihwan kota Medan ) mengidentifikasi faktor pendukung dan penghambatnya. Penelitian ini merupakan penelitian deskriptif dengan pendekatan kualitatif. Subyek penelitian ini adalah Kepala Sekolah, Waka Kurikulum, Waka Kesiswaan, Guru BK, Guru PPKn, dan peserta didik MIS Al-Ihwan. Pengumpulan data dilakukan dengan menggunakan metode observasi, wawancara, dan dokumentasi. Penyajian data dan penarikan kesimpulan. Uji keabsahan data menggunakan metode mengajar, dan dari sumber informasi. Hasil penelitian menunjukkan bahwa: 1) Implementasi Kebijakan Pendidikan Anti Korupsi di MIS Al-Ihwan kota Medan, (a) Kegiatan membuat kerajinan tangan dari benang menjadi gelang, kejujuran , pembiasaan-pembiasaan, (b) Nilainilai yang dikembangkan dalam pendidikan anti korupsi ditanamkan melalui perilaku peserta didik diantaranya kejujuran, kepedulian, kemandirian, kedisiplinan, tanggung jawab, kerja keras, sederhana, keberanian, dan keadilan, c) Implementasi Kebijakan Pendidikan Anti Korupsi di MIS Al-Ihwan kota Medan, dilihat dari beberapa aspek: (1) Komunikasi, dilakukan melalui sosialisasi dan pembiasaanpembiasaan, (b) sarana dan prasarana mendukung, (c) tersedia tempat melakukan penyuluhan dan dukungan dari pihak sekolah. 3) Faktor penghambat: (a) kurangnya pemahaman peserta didik terkait pendidikan anti korupsi, (b) kurangnya sarana sosialisasi tertulis, (c) buku-buku mengenai pendidikan anti korupsi masih terbatas, (d) belum ada struktur birokrasi tersendiri terkait pendidikan anti korupsi
MODEL JARINGAN SARAF TIRUAN UNTUK PREDIKSI PERMINTAAN PRODUK UMKM DI PEMATANG SIANTAR Sonang, Sahat; Sinaga, Kalvin
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1849

Abstract

This study aims to develop an Artificial Neural Network (ANN) model in predicting demand for MSME products in Pematangsiantar to optimize production and inventory management. The main problem faced by MSME actors is demand uncertainty which causes excess or shortage of stock, thus affecting business efficiency. The ANN model is applied with a guided learning approach using the backpropagation algorithm to analyze demand patterns based on historical sales data. Data were obtained from the Cooperatives and MSMEs Office of Pematangsiantar City and interviews with business actors. The research process includes data collection and pre-processing, variable selection, data sharing, model development, training, optimization, and evaluation using the Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percent Error (MAPE) metrics. The results of the study show that the ANN model with the backpropagation algorithm is able to provide accurate demand predictions, with a MAPE value below 10%, which indicates very good forecasting. The implementation of this model helps make it easier for MSMEs to make strategic decisions related to production and inventory, thereby increasing competitiveness in the market.
A Prototype of Water Turbidity Measurement With Fuzzy Method using Microcontroller Siregar, Victor Marudut Mulia; Sinaga, Kalvin; Hanafiah, M. Ali
Internet of Things and Artificial Intelligence Journal Vol. 2 No. 2 (2022): Volume 2, Issue 2, 2022 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1063.081 KB) | DOI: 10.31763/iota.v2i2.539

Abstract

Water is a source of much-needed living things such as daily needs and transportation routes, and also as a source of energy. Water is also essential as a water quality factor. Good water for treating cold-water ornamental fish with temperatures below 20o Celcius has a maximum water turbidity value of 10 NTU (Nephelometric Turbidity Unit); if the turbidity level is above 10 NTU, the water will be declared cloudy and affect fish health. The object of this research is ornamental aquarium fish with the type of goldfish. The research method used is qualitative. The research flow begins with observing the problem, then designing and simulating the Arduino Uno as a place to process the measuring data. The prototype of this tool aims to show changes in the level of turbidity of water from the value of water turbidity. This prototype uses the fuzzy method to assist the testing process. This study's results for five days showed that 1 out of 5 tests indicated that the aquarium water was cloudy, namely on the fifth day. The results of this study are expected to be implemented in a prototype for measuring water turbidity using the fuzzy method using a microcontroller. The design of this water turbidity measuring instrument is expected to estimate the turbidity of water or liquid correctly, precisely, accurately, with a small error rate, and notify warnings for replacing ornamental fish aquarium water.
A Decision Support System For Selecting The Best Practical Work Students Using MOORA Method Siregar, Victor Marudut Mulia; Hanafiah, M. Ali; Siagian, Nancy Florida; Sinaga, Kalvin; Yunus, Muhammad
Internet of Things and Artificial Intelligence Journal Vol. 2 No. 4 (2022): Vol. 2 No. 4 (2022): Volume 2 Issue 4, 2022 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (474.472 KB) | DOI: 10.31763/iota.v2i4.562

Abstract

This research aims to solve the problem of selecting the best practical work students at the Politeknik Bisnis Indonesia. The current selection of the best practical work students at PBI does not yet use a decision support system approach. This problem is solved by building a Decision Support System using Multi-Objective Optimization based on Ratio Analysis (MOORA) method. The criteria used in this DSS consist of discipline, teamwork, skills, quality of work, and attendance. As for the results of data processing from this study, the three best alternative data were obtained, namely alternative Vivi (A6) as the 1st best Practical Work Students with a score of Yi = 36.5954, Hafiz (A1) as the 2nd best Practical Work Students with a score of Yi = 34.5339, Cahaya (A3) as the 3rd best PKL student with a score of Yi = 33.4767. Through this decision support system that has been built, the selection of the best practical work students can be made quickly and effectively.
Classification of Customer Satisfaction Through Machine Learning: An Artificial Neural Network Approach Siregar, Victor Marudut Mulia; Sinaga, Kalvin; Sirait, Erwin; Manalu, Andi Setiadi; Yunus, Muhammad
Internet of Things and Artificial Intelligence Journal Vol. 3 No. 3 (2023): Vol. 3 No. 3 (2023): Volume 3 Issue 3, 2023 [August]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v3i3.643

Abstract

This study aims to classify customer satisfaction data from Café Alvina using Machine Learning, specifically by implementing the Backpropagation Artificial Neural Network. The data used in this study consists of 70 training data and 30 testing data, with the input layer of the Artificial Neural Network having 5 neurons and the output layer having 2 neurons. The tested Artificial Neural Network models include the 5-5-2 model, 5-10-8-8-2 model, 5-5-10-2 model, and 5-8-10-2 model. Among the four models used in the testing process of the Backpropagation Artificial Neural Network system using Matlab, the 5-10-8-8-2 architecture model performed the best, achieving an MSE (Mean Squared Error) of 0.000999932 during training with 2920 epochs and a testing MSE of 0.000997829. After conducting the testing, the performance of the Artificial Neural Network models was as follows: the 5-5-2 model achieved 81%, the 5-10-8-8-2 model achieved 100%, the 5-5-10-2 model achieved 98%, and the 5-8-10-2 model achieved 96%. Through the implementation of Backpropagation Artificial Neural Network, the classification of customer satisfaction can be effectively performed. The trained and tested data demonstrate that the Artificial Neural Network can accurately recognize the input data in the system.
Decision Support System for Selecting Social Assistance Recipients using The Preference Selection Index Method Parapat, Eka Pratiwi Septania; Sinaga, Kalvin; Sirait, Erwin; Manalu, Andi Setiadi
Internet of Things and Artificial Intelligence Journal Vol. 3 No. 4 (2023): Vol. 3 No. 4 (2023): Volume 3 Issue 4, 2023 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v3i4.662

Abstract

This research aims to solve the problem of selecting social assistance recipients in the Nagori Moho area, Java Marajah Bah Subdistrict, Jambi, Simalungun District; in order to obtain the right targeted recipients of social assistance, the Nagori office carries out the selection of its residents, this selection is carried out by implementing a computer-based decision support system (DSS). The decision support system uses the PSI method. The criteria used in this method consist of economic condition, income, jobs, age, and dependents of the school children. The results obtained from this research are recommendations for the population receiving aid with results consisting of rank 1 with the alternative value S_Purba with a value of 0.9286, then rank two with the alternative F_Azhar with a value of 0.7599, and rank 3 is Jumiati with a value of 0.7163. This decision support system can make it easier for the Nagori office to select residents worthy of assistance.
Co-Authors Erwin Sirait, Erwin Fahmi Sulaiman Henny Pratiwi Henny Pratiwi, Henny M. Ali Hanafiah, M. Ali Manalu, Andi Setiadi Muhammad Ilham Riyadh, Muhammad Ilham Muhammad Yunus Parapat, Eka Pratiwi Septania Siagian, Nancy Florida Siregar, Victor Marudut Mulia Sonang, Sahat