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Penerapan Metode Monte Carlo pada Simulasi Antrian Poliklinik RSUD DR. RM. Djoelham Desty Dwi Putri; Akim M.H. Pardede; Anton Sihombing
Saturnus : Jurnal Teknologi dan Sistem Informasi Vol. 2 No. 4 (2024): Oktober : Saturnus : Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v2i4.368

Abstract

Long queues at the polyclinic of RSUD RM DR Djoelham Binjai often cause inconvenience to patients and reduce service efficiency. This study aims to analyze the queuing system at the hospital's polyclinic using the Monte Carlo method, which is able to model uncertainty in patient arrivals and service times. With this method, it is expected that a more accurate picture of patient waiting time and queue performance can be obtained so that improvement measures can be identified. The data used in this simulation includes the number of patients who come and the service time in the polyclinic. Monte Carlo simulations are carried out to predict various queuing scenarios based on variations that occur in patient arrivals and service duration. The simulation results provide information related to the estimated average waiting time of patients, and the level of queue density. This study shows that the application of the Monte Carlo method is effective in providing a more measurable solution to minimize waiting time and improve service quality at the polyclinic of RM DR Djoelham Binjai Hospital. These results are expected to be a reference for hospital management in making strategic decisions related to the optimization of health services. With the average waiting time for patients in the queue is 10.59 minutes while the average patient time is 25.34 minutes.
A Decision Support System To Determine The Location Of A New Sales Branch At Star East Shop With The Smart Method Nawawi, Ahmad; Ramadhani, Suci; Sihombing, Anton
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 2 No. 2 (2023): February 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v2i2.156

Abstract

In a business world that is always dynamic and full of competition, business people must always think of ways to continue to survive and if possible develop their business scale in order to meet these business needs, there are many ways that can be taken, one of which is by conducting data analysis. . Bintang Timur shop is one of the businesses in the field of iron and building material shops in the city of stabat. Bintang Timur shop was founded in 2013 which continues to grow at this time. Equipped with the desire to meet the needs of users in the field of iron and building, Bintang Timur store continues to grow by adding various products. The profits obtained in this shop are also used to develop the business, one of which is the addition of goods sold. Based on the analysis that has been done, there are several obstacles faced by this eastern star shop. One of them is the process of finding a new sales branch location at the Bintang Timur store. In this study, a Decision Support System (DSS) will be built using the Simple Multiple Attribute Rating Technique (SMART) method which is a multi-criteria decision making technique based on each alternative consisting of of a number of criteria that have a value and each criterion. Based on the calculation results of the SMART method above, Tebasan (A1) is a new branch location at the Bintang Timur Store in Stabat City which is feasible with a value of 0.763.
Klasifikasi Tingkat Minat Belanja Online Melalui Media Sosial pada Masyarakat di Kota Binjai Meggunakan Algoritma K-Means Dhea Agustina Akmal; Relita Buaton; Anton Sihombing
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 3 (2024): Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i3.169

Abstract

The advancement of information technology and globalization has transformed shopping behaviors, with social media becoming the primary platform for online shopping. This study aims to analyze the online shopping preferences of residents in Binjai City through social media using clustering methods, specifically the K-Means algorithm. Data were collected via a questionnaire targeting 523 respondents in Binjai City, focusing on variables such as gender, age, and the social media platforms used. Clustering methods are employed to group online shopping data into representative clusters, helping identify community preferences for specific social media platforms for shopping. Matlab is used to process the data and generate relevant insights into online shopping patterns, facilitating decision-making regarding the selection of the most suitable social media platform for transactions.The findings of this study are expected to provide valuable insights for both sellers and buyers in determining the most effective social media platforms for online shopping. Additionally, the results will be useful for residents of Binjai City to understand and choose the social media platforms that best meet their online shopping needs.
Penerapan Metode Waspas dalam Pengambilan Keputusan Rekrutmen Anggota KPPS Pemilu Agung Aulia Tama; Marto Sihombing; Anton Sihombing
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 4 (2024): Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i4.223

Abstract

Members of the KPPS (Voting Organizing Group) are responsible for organizing voting in a polling station (TPS) during general elections in Indonesia. They are the spearhead in carrying out the democratization process by supervising and ensuring the continuity of elections honestly, fairly, and transparently. The duties of KPPS members include preparing TPS before voting begins, receiving and examining voters, supervising the election process to ensure compliance with applicable regulations, counting votes after voting is complete, reporting election results, and maintaining security and order around TPS. Decision support system is a Decision support system or Decision Support System (DSS) is an interactive system that supports decisions in the decision-making process through alternatives obtained from data processing results. The purpose of this study is to facilitate the recruitment of members of the Voting Organizing Group (KPPS). The research method is Weighted Aggregated Sum Product Assessment (WASPAS). WASPAS is to find the most appropriate priority location choices using weighting. The results of this study are that the development of this support system can help the KPU in selecting or selecting KPPS members and this decision support system as a tool in developing KPPS members by viewing or using criteria according to the criteria needed using the WASPAS method.
Penerapan Metode Clustering Untuk Mengetahui Kepatuhan Wajib Pajak Bumi Dan Bangunan Pada Desa Perkebunan Tanjung Keliling Ratna Cantika; Achmad Fauzi; Anton Sihombing
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 4 (2024): Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i4.242

Abstract

Land and Building Tax (PBB) is a type of area regulated by the government in determining the amount of tax for implementation and development as well as increasing the prosperity and well-being of the people. Based on taxpayer compliance data in Tanjung Keliling Plantation, the results of tests carried out using the Clustering algorithm can determine the variables of ownership area, hamlet name and payment level. Clusters 1,2,3 of 600 PBB taxpayer data, namely where cluster 1 has 166 data, can be grouped based on the Ownership Area of "500,001-600,000m2" with the Hamlet Name "Ujung Bangun" and the Payment Level "Quite Good". Cluster 2 consists of 196 data, which can be grouped based on ownership area "200,001-300,000m2" with the hamlet name "Karang Jati" and payment level "fairly good". And Cluster 3 with a total of 238 data, can be grouped based on the Ownership Area "400,001-500,000m2" with the Hamlet Name "Mojosari" and the Payment Level "Quite Good".
Application of the K-Means Method for Clustering Land and Building Tax Payments Based on Tax Types (Case Study: BPKPAD Binjai City) Riski Ramadhansyah; Akim Manaor Hara Pardede; Anton Sihombing
International Journal of Health Engineering and Technology Vol. 1 No. 3 (2022): IJHET-SEPTEMBER 2022
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (596.035 KB) | DOI: 10.55227/ijhet.v1i3.56

Abstract

Land and Building Tax or abbreviated as PBB is a fee that must be paid for the existence of land and buildings owned by the community or residents. The determination of PBB in Binjai City is based on the application of the Land Value Zone (ZNT) which is close to the market price, which will be able to create equitable development throughout Binjai City. BPKPAD (Regional Revenue and Assets Financial Management Agency) Binjai City is a government agency that receives PBB payments from the community. Data - data on PBB payments for the people of Binjai City have been stored in an existing system and every year it will continue to increase so that it will cause data accumulation in the land and building tax archives. A data processing system is needed to manage these data, one of which can be done with data mining which can process piles of data into useful information and can be utilized by grouping PBB data based on criteria. Clustering is a method in data mining that can be used to automatically detect clusters of adjacent records that have a certain definition in all variables. K-Means algorithm is a simple algorithm to classify or group a large number of objects with certain attributes into groups (clusters). So that this system can be used as input for the Binjai City BPKPAD in finding solutions to increase regional income from PBB payments.
Clustering of Customer Complaints from PDAM Kota Binjai Using the K-Means Method Lailatul Magfiroh; Hermansyah Sembiring; Anton Sihombing
International Journal of Health Engineering and Technology Vol. 1 No. 3 (2022): IJHET-SEPTEMBER 2022
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2176.556 KB) | DOI: 10.55227/ijhet.v1i3.65

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PDAM Tirtasari Binjai City is a public service institution that has a monopoly on water supply in Binjai City. The predicate as a metropolitan city, illustrates that Binjai City is a city with dense industry and trade. In this study, discusses how to handle customer complaints of PDAM Binjai City to provide satisfaction to customers. The research method used in this study is K-Means which aims to describe the quality of service for handling customer complaints at PDAM Kota Binjai in increasing customer satisfaction. The informant determination technique carried out by the researcher is using the Clustering K-Means method.
Optimization Of Learning Scheduling Using Linear Regression Naufal Falaah Nduru; Akim M.H Pardede; Anton Sihombing
International Journal of Health Engineering and Technology Vol. 1 No. 3 (2022): IJHET-SEPTEMBER 2022
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (627.354 KB) | DOI: 10.55227/ijhet.v1i3.66

Abstract

Scheduling is a process, method, manufacture, or schedule to be included in the schedule (KBBI). Scheduling that is needed in general and that occurs at one point of education in making study schedules requires various supporting factors from the division of teacher tasks. Based on this, efforts to facilitate learning schedules are made to optimize an activity so as to increase productivity and effectiveness.To carry out learning activities that are carried out conventionally and for a long time, teachers who have teaching schedules in two or more different classrooms at the same time must be revised by changing their respective schedules or reducing the hours that occur as guided by the teacher. At SD S Muhammadiyah Sambirejo, which is a school located in Sambirejo Village, Binjai District, Langkat Regency, and has several educators and educational staff at this school, I focus on the case study of learning scheduling, so that teaching and learning activities in a school must pay attention to the learning schedule and avoid clashes. This makes it easier to prepare a study schedule. The method used is linear regression as an optimization of learning scheduling. The results of testing the linear regression method in optimizing learning scheduling using linear regression with a total of 10 forecasting data as analysis and determining the forecasting result value of 2.0063334474495 obtained data results with the number of conflicting hours.
Sistem Pendukung Keputusan untuk Penilaian Kinerja Karyawan Biller di Kantor ULP Kuala Menggunakan Metode TOPSIS Sri Defriani Br Sembiring; Suci Ramadani; Anton Sihombing
Saturnus : Jurnal Teknologi dan Sistem Informasi Vol. 3 No. 4 (2025): Oktober : Saturnus : Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v3i4.1088

Abstract

Employee performance appraisal is a crucial aspect of human resource management and development, as the evaluation results serve as the basis for managerial decision-making, including promotions, incentives, and career development. However, unstructured assessment sistems often hinder the objectivity, transparency, and accuracy of performance evaluations. This study aims to design and develop a web-based Decision Support Sistem (DSS) to assess the performance of Biller employees at the ULP PLN Kuala office by applying the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. TOPSIS was selected because it effectively addresses multi-criteria decision-making problems by comparing each alternative to both positive and negative ideal solutions. The evaluation criteria include invoice achievement, account return balance, and PAL balance. The sistem was developed using PHP as the programming language and MySQL as the database, ensuring integration and accessibility. The test results indicate that the sistem is capable of providing employee rankings in an objective and measurable manner. Based on the calculation, Tri Widodo achieved the highest score (0.8027), demonstrating the best performance among the evaluated employees. The implementation of this TOPSIS-based DSS makes the performance appraisal process more sistematic, efficient, transparent, and accurate, thereby contributing to the improvement of human resource management quality within the organization.  
Pelatihan Pembuatan Eco Enzym bagi Mahasiswa Baru STMIK Kaputama TA. 2024-2025 Sebagai Bentuk Kepedulian Kampus pada Pelestarian Lingkungan Arliana, Lina; Maulita, Yani; Fauzi, Ahmad; Novriyenni, Novriyenni; Sihombing, Anton; Ambarita, Indah; Simanjuntak, Magdalena; Syahputra, Siswan; Khair, Husnul; Pramana, I Gusti; Annatasia, Kristina; Puspadini, Ratih; Selfira, Selfira; Sitompul, Melda Pita Uli; Khadafi, Muammar
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 5 No 1 (2025): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

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

Abstract

The growing volume of household organic waste poses a serious challenge to environmental sustainability. Through this community service program, STMIK Kaputama offers an educational and practical solution by involving first-year students in Eco Enzyme production training. Eco Enzyme, a fermented product derived from organic kitchen waste, has been proven to provide various benefits such as an eco-friendly cleaner, liquid fertilizer, and natural deodorizer, serving as an effective alternative to harmful chemical-based products. During the student orientation program (PKKMB), 300 students participated in a series of activities, including environmental education, fermentation practice, and harvesting of Eco Enzyme. The results demonstrated improvements in students’ knowledge and skills, with the expectation of long-term behavioral changes in managing waste at its source. The program successfully produced more than 300 liters of Eco Enzyme and significantly reduced organic waste disposal to landfills. More importantly, it cultivated environmentally conscious student leaders. Engaging first-year students in this real-world initiative serves as a strategic effort to instill sustainability values and foster a culture of environmental responsibility both within the campus and the broader community.
Co-Authors ., Novriyenni Achmad Fauzi ACHMAD FAUZI Adelia Ramadani Agung Aulia Tama Ahmad Fauzi Ahmad Nawawi Ambarita, Indah Andriansyah, M Juli Angel, Kiki Annatasia, Kristina Arliana, Lina Astari, Rizki Yulidha Astrika, Rahayu Buaton, Relita Budi Serasi Ginting Budi Serasi Ginting Clara Rosa Wijaya Desty Dwi Putri Dewi, Sintia Dhea Agustina Akmal Dhea Alfiya Ningsih Dini Syahfitri Fauzi Ahmad Muda Fauzi, Achmad Fitri Handayani Fuji Dodo Aritonang Ginting, Budi Serasi Hana Niska Tafonao Hermansyah Sembiring Hotler Manurung husnul khair husnul khair husnul khair Ihsan Wibowo Zakti Indah Malasari Julia Br Sembiring Kadim, Lina Arliana Nur Khair, Husnul Kiki Angel Kiki Angel Lailatul Magfiroh M Agung Hidayat Magdalena Simanjuntak Marto Sihombing Marto Sihombing Melda Pita Uli Sitompul Mhd Ferdiansyah Putra Muammar Khadafi Natalia Sianturi, Ruth Naufal Falaah Nduru Novriyenni Novriyenni Novriyenni, Novriyenni Novriyenni, Novriyenni Pardede, Akim Manaor Hara Pramana, I Gusti Rahmat Ramadhan Ramadani, Suci Ratih Puspadini Ratna Cantika Riski Ramadhansyah Risna Serviya risna serviya risna serviya risna serviya Rizki Yulidha Astari Rusmin Saragih, Rusmin Selfira, Selfira Serasi Ginting, Budi Serviya, Risna Shelly Maulia Sihombing, Marto Simanjuntak, Magdalena Sirait, Suprianto Sri Defriani Br Sembiring Suci Rahmadani suci ramadani Suci Ramadhani, Suci Supri Anto Sirait Suprianto Sirait Syahputra, Siswan Syahputri, Heni Tasya Maysarah Br. Sembiring Tasya Maysarah Sembiring Triono, Arif Yani Maulita