Article Per Year (5 Year)
p-Index From 2021 - 2026
1.701
P-Index
This Author published in this journals
All Journal Jurnal Pengabdian Pada Masyarakat METHABDI Majalah Ilmiah METHODA TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Indra M. Sarkis S.
Universitas Methodist Indonesia
Religion Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Immunology & microbiology Languange, Linguistic, Communication & Media Medicine & Pharmacology Physics Public Health

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 13 Documents
Search

 1   2 
PENGENALAN INTERNET SEHAT PADA SMAN I TIGAPANAH, KABUPATEN KARO, SUMATERA UTARA Fati Gratianus Nafiri Larosa; Humuntal Rumapea; Indra M. Sarkis S.; Yolanda Yulianti Pratiwi Rumapea; Edward Rajagukguk; Darwis Robinson Manalu; Doli Hasibuan; Jhoni Maslan; Surianto Sitepu; Arina Prima Silalahi; Posma Lumbanraja; Nettina Samosir; Gresa Simarmata; Putra Palipi
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 1 No 1 (2021): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (561.92 KB) | DOI: 10.46880/methabdi.Vol1No1.pp41-44

Abstract

A healthy Internet is one of the basic needs of the use of digital technology in various fields, especially in the world of education. Since SMAN I is one of the service partners and is also very close to the center of agriculture and tourism, Community is carried out by the Information System Study Program, Universitas Methodist Indonesia as a form of implementing the Tri Dharma of Higher Education. Its purpose and benefits are to share and contribute ideas and transfer knowledge and technology. This service activity was carried out for a day, with the material including explanations about Internet Sehat (Healthy Internet) and Internet Cakap. This topic is very much needed in the education community to be able to use the internet intelligently, creatively, and productively.
SISTEM INFORMASI TRANSPORTASI AIR BERBASIS CUSTOMER RELATIONSHIP MANAGEMENT (CRM) Cinta Sinaga; Indra M. Sarkis S.; Samuel Van Basten Manurung
Majalah Ilmiah METHODA Vol. 8 No. 1 (2018): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol8No1.pp27-35

Abstract

Dinas Perhubungan Kabupaten Samosir merupakan pendorong utama terwujudnya pembangunan juga kebutuhan sarana, prasarana dan fasilitas. Saat ini proses pengolahan data transportasi air masih dilakukan secara manual. Tidak hanya di proses pengujian saja, proses pengolahan data masih meliputi komponen lainnya seperti pembayaran pajak masih dilakukan secara manual seperti halnya dengan proses pengujian standarisasi dan masa berlaku kapal tersebut. Untuk menangani masalah-masalah tersebut dimanfaatkanlah sistem informasi dengan membuat sebuah sistem yang mencakup proses pengolahan data pengujian transportasi air dan pembayaran pajak transportasi air tersebut yang dimana akan dikombinasikan dengan konsep atau pemodelan Customer Relationship Management yang dimana sistem ini akan memberitahukan notifikasi pemberitahuan masa berlaku transportasi air seperti kapal kepada pemiliki trasnportasi air tersebut untuk melakukan uji kembali di Dinas Perhubungan Kabupaten Samosir lewat SMS agar dapat terhindar dari kecelakaan. Selain notifikasi masa uji berlaku kapal, terdapat juga notifikasi untuk pemberitahuan kepada pemilik kapal untuk membayar pajak tepat waktu agar pendapatan dari pajak untuk dinas perhubungan tidak tersendat dan membantu pemilik kapal untuk membayar pajak tepat pada waktunya. Jadi dengan adanya Customer Relationship Management ini maka Dinas Perhubungan Kabupaten Samosir akan lebih mudah untuk menangani pendataan transportasi air dan mengingatkan masa berlaku kapal dan pembayaran pajak sebelum tanggal berakhir.
Prediksi Harga Cabe Rawit di Wilayah Provinsi Sumatera Utara dengan Metode Simple Exponential Smoothing Naomi Gracetira; Vony Melinda Simamora; Nokia Margareta; Josua Pedro Anata P.; Joy Syahputra Lingga; Kevin Ginsigel Ginting; Indra M. Sarkis S.
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp73-77

Abstract

This study aims to predict the price of cayenne pepper in North Sumatra Province using the Simple Exponential Smoothing (SES) method with α = 0.2. The data used includes the price trend of cayenne pepper from January to July 2024, taken from Databoks and supported by BAPANAS (Badan Pangan Nasional). The analysis results show that the SES method can capture the upward trend in the price of cayenne pepper with a relatively high level of accuracy, indicated by the MAPE (Mean Absolute Percentage Error) value of 7.34%. The predicted average price of cayenne pepper on July 15, 2024 is estimated to reach Rp. 47,555.34. These findings suggest that the SES method is reliable for planning and decision-making regarding the price of cayenne pepper, although it is more sensitive to recent data. This research makes an important contribution to the government, farmers, and traders in dealing with fluctuations in agricultural commodity prices.
Prediksi Konsumsi Rokok di Indonesia dengan Single Exponential Smooting Dina Sonia Lumbantoruan; Maria Oktaviani Gultom; Egita Fanie Lumbantoruan; Diana Muthiah Sigalingging; Ella Angelica; Theresia Jesika Simbolon; Indra M. Sarkis S.
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp122-128

Abstract

This study predicts cigarette consumption per capita in Medan City using the Single Exponential Smoothing (SES) model. The problem faced is the fluctuation and increasing trend of cigarette consumption which requires accurate prediction. The SES model was chosen due to its ability to capture historical data and produce accurate forecasts. To test the accuracy of the model, three prediction error indicators were used, namely Mean Squared Error (MSE), Mean Absolute Deviation (MAD), and Mean Absolute Percentage Error (MAPE). The results of the analysis show that the SES model has low MSE, MAD, and MAPE values, which indicates a high level of accuracy. For the type of filter clove cigarettes, the MAPE value is 9.43%, for clove cigarettes without filter, the MAPE value is 27.77%, white cigarettes MAPE value is 27.73%, tobacco MAPE value is 38.13% and for other types of cigarettes and tobacco 33.20% where the accuracy results are good. The predictions generated by this model show an increasing trend of consumption in Medan City. These predictions provide important insights for policymakers in designing cigarette consumption control. This study thus confirms the effectiveness of the SES model in predicting per capita cigarette consumption in Indonesia. It makes a significant contribution to the literature on tobacco product consumption prediction.
Analisis Sentimen Game Mobile Legends Berdasarkan Review Pengguna di Playstore Menggunakan Algoritma Naive Bayes Amron Rido Sitorus; Wawan John Putra Ziraluho; Indra M. Sarkis S.
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp108-113

Abstract

Sentiment analysis of Mobile Legends user reviews on the Google Play Store was conducted using the Naive Bayes algorithm, with the aim of identifying user perceptions and providing recommendations for developers to improve the quality of the game. The methods used include data collection, text processing, and vectorization using TF-IDF. The data was divided into training and testing subsets to build and evaluate the model. Results showed an accuracy of 74%, with precision 1.00 and recall 0.00 for positive sentiment, and precision 0.74 and recall 1.00 for negative sentiment. Although the model effectively detects negative sentiment, optimization is needed to improve the detection of positive sentiment. The findings provide valuable insights for developers in understanding user opinions and improving game quality.
Analisis Perkiraan Jumlah Pegawai Negeri Sipil di Kota Medan Menggunakan Metode Single Exponential Smoothing Riska Maria Br. Purba; Desriana Aritonang; Grace Theodora Valentina Purba; Kevin Yohanes Hutauruk; Stevanus Hendy Sitanggang; Indra M. Sarkis S.
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp149-154

Abstract

The number of civil servants is a crucial factor in determining budget allocation, human resource planning and the provision of public services. In Medan City, the number of civil servants has decreased from year to year based on data from the North Sumatra Province Central Statistics Agency. The uncertainty of the number of civil servants from year to year makes forecasting the number of civil servants a challenging task and requires appropriate analytical methods. Therefore, an analysis of the estimated number of civil servants is needed to determine the right policy. One method that can be used is Single Exponential Smoothing (SES). Based on the results of testing predictions for the number of civil servants in the city of Medan for the 2023 period using alpha SES of α0.1, α0.3, α0.5, α0.7 and α0.9, it was found that using alpha 0.7 gave prediction results with a Mean Square Error value the smallest is 26515890 and the predicted number of civil servants is 11867 people in 2023. The prediction results can be used by local governments to plan human resource needs, including recruitment, training or development of civil servants according to future needs.
Penerapan Data Mining Menggunakan Algoritma C4. 5 Untuk Memprediksi Persediaan Stok Beras Smansal Hartawan Totonafo Gulo; Olva Andrian Naibaho; Dewi Sartika Br. Rajagukguk; Gracetia Sari Madu Sihite; Indra M. Sarkis S.
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp114-121

Abstract

Penelitian ini bertujuan untuk menerapkan data mining dengan menggunakan algoritma C4.5 dalam memprediksi persediaan stok beras di Grosir Media Jaya yang terletak di Kota Medan. Data diperoleh melalui wawancara langsung dengan pemilik grosir dan catatan transaksi selama empat minggu, yang kemudian diolah menggunakan Microsoft Office Excel. Data yang digunakan meliputi atribut Jenis Beras, Jumlah Terbeli Per Minggu, Jumlah Tersisa Per Minggu, Kategori, dan Keteranan Stok. Setelah preprocessing data, algoritma C4.5 diterapkan untuk membangun model pohon keputusan. Hasil analisis menunjukkan bahwa variabel "Jumlah Tersisa Per Minggu" merupakan faktor utama dalam memprediksi ketersediaan stok. Akurasi dari model yang dihasilkan adalah 96.88%, mengindikasikan efektivitas algoritma C4.5 dalam memprediksi persediaan stok beras secara akurat. Penelitian ini memberikan kontribusi signifikan terhadap pengelolaan stok di grosir dengan mengoptimalkan sistem prediksi untuk menghindari kekurangan atau kelebihan stok.
Analisis Pola Pembelian Konsumen pada Swalayan Surya Menggunakan Algoritma Apriori Juli Yanti Br. Situmorang; Leoni Sancai; Kristina Surbakti; Yenni Tasya E. Simanungkalit; Poltak Breziz Manalu; Indra M. Sarkis S.
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp160-167

Abstract

Data mining is a technique for extracting new information from data sets. Information is considered very important and valuable as it can help achieve desired goals. Therefore, not only individuals compete for information, but also trading businesses such as Swalayan Surya. This supermarket is strategically located in a residential area, which of course affects the level of sales there. With sales transaction activities every day, transaction data continues to grow and cause data accumulation. Unfortunately, Swalayan Surya has never analyzed the sales patterns made to consumers, even though this analysis can provide very important strategic information. This information can be used to increase profits and optimize product control in the decision-making process. Sales pattern analysis can help in various aspects, such as ensuring the availability of products that are always on the shelves, identifying products that are closely related to other products, and placing these products strategically to make it easier for consumers to find and buy the products they need. Thus, Swalayan Surya can provide a better shopping experience to consumers while improving operational efficiency and store profits. However, until now, this transaction data has only been used as an archive and has not been properly utilized, even though the dataset contains very useful information. The association method using the Apriori Algorithm is one of the data mining techniques that is useful for finding association patterns based on consumer shopping patterns so that it can be seen what product items are commonly purchased together by consumers. The results of this study show that the combination of Aqua and ABC Milk Coffee products has the highest support value of 50% and a confidence value of 60%, with a lift ratio value of 2.50 which shows a positive (strong) correlation.
Pendekatan Regresi Linear Berganda untuk Estimasi Pengeluaran per Kapita di Desa dan Kota untuk Wilayah Sumatera Utara Agnes Tri Abiya Perangin-angin; Elsa Adella Siburian; Geri Juna Putra Orando Purba; Jeffry Delay Silaban; Raisa Delvina Pakpahan; Theodora Risma Naftali; Indra M. Sarkis S.
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp260-267

Abstract

The level of community welfare can be seen from economic factors. To find out the economic welfare of the community requires the calculation of per capita expenditure. Identifying per capita expenditure estimates can be a reference for the government and a company to find out the economic dynamics of the community. The expenditure data is per capita expenditure in villages and cities for the North Sumatra region, this data is taken from the BPS website. In estimating using the Multiple Linear Regression method and to analyze its accuracy using MAPE analysis. The results of estimation with multiple linear regression on per capita expenditure in villages and cities in North Sumatra for 2024 are 11,182, and the value obtained from the calculation with MAPE is 0.933% which means the accuracy level is 99.067%.
Perbandingan K-Means dengan Hierarchical Clustering Untuk Pengelompokkan Tingkat Pengangguran di Sumatera Utara Enzelina Feronika Situmorang; Yunita Angelina Sihombing; Eva Lina Damayanti Samosir; Indra M. Sarkis S.
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp155-159

Abstract

Unemployment is a crucial issue faced by many countries, including Indonesia. This study compares two data clustering methods, K-Means and Hierarchical Clustering, to group districts/cities in North Sumatra based on the Open Unemployment Rate (OUR). The K-Means method is known for its speed and simplicity in partitioning data into clusters by determining centroids as the central points, while Hierarchical Clustering organizes data into a more complex hierarchy without requiring a predefined number of clusters. The OUR dataset used in this study was obtained from various districts/cities in North Sumatra and processed using statistical software to apply both methods. The results indicate that the K-Means method provides superior clustering quality with a Silhouette Score of 56.50%, compared to Hierarchical Clustering, which obtained a score of 43.69%. These findings suggest that the K-Means method is more effective in identifying unemployment patterns in the region. This insight can serve as a reference for policymakers in formulating more targeted strategies to address unemployment in North Sumatera.
Co-Authors Agnes Tri Abiya Perangin-angin Amron Rido Sitorus Astri Agnes Panjaitan Cinta Sinaga Crisvan Simamora Darwis Robinson Manalu Desriana Aritonang Dewi Sartika Br. Rajagukguk Diana Muthiah Sigalingging Dina Sonia Lumbantoruan Doli Hasibuan Edward Rajagukguk Egita Fanie Lumbantoruan Ella Angelica Elsa Adella Siburian Enzelina Feronika Situmorang Eva Lina Damayanti Samosir Fati Gratianus Nafiri Larosa Fransisco Julius Marpaung Geri Juna Putra Orando Purba Gilbert Surbakti Grace Theodora Valentina Purba Gracetia Sari Madu Sihite Gresa Simarmata Humuntal Rumapea Jeffry Delay Silaban Jhoni Maslan Johan Siregar John Franz E.D.L. Sitorus Josua Pedro Anata P. Joy Syahputra Lingga Juli Yanti Br. Situmorang Kevin Ginsigel Ginting Kevin Yohanes Hutauruk Kristina Surbakti Labora Triasi Butar-Butar Leoni Sancai Maria Oktaviani Gultom Naomi Gracetira Nettina Samosir Nokia Margareta Olva Andrian Naibaho Poltak Breziz Manalu Posma Lumbanraja Putra Palipi Raisa Delvina Br. Pakpahan Raisa Delvina Pakpahan Reimer Fernando Purba Riska Maria Br. Purba Rosanti Rumapea Samuel Van Basten Halomoan Manurung Silalahi, Arina Prima Smansal Hartawan Totonafo Gulo Stevanus Hendy Sitanggang Surianto Sitepu Theodora Risma Naftali Theresia Jesika Simbolon Valdiona Ginting Vony Melinda Simamora Wawan John Putra Ziraluho Yenni Tasya E. Simanungkalit yolanda yulianti pratiwi rumapea Yunita Angelina Sihombing