Article Per Year (5 Year)
p-Index From 2021 - 2026
2.81
P-Index
This Author published in this journals
All Journal Sistemasi: Jurnal Sistem Informasi Computer Based Information System Journal Jurnal Pendidikan Ekonomi (JURKAMI) Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Building of Informatics, Technology and Science Indonesian Journal of Business Intelligence (IJUBI) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Fokus: Publikasi Ilmiah untuk Mahasiswa, Staf Pengajar dan Alumni Universitas Kapuas Sintang Kontribusi: Jurnal Penelitian dan Pengabdian Kepada Masyarakat Jurnal Pendidikan Sains dan Komputer Jurnal Puan Indonesia Jurnal Pengabdian Ibnu Sina Computer & Science Industrial Engineering Journal
Darmansah, Darmansah
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

Published : 18 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 18 Documents
Search

 1   2 
Strategi Pemasaran Produk UMKM Desa Cikakak Berbasis Teknologi Fathoni, M Yoka; Wijayanto, Sena; Fernandez, Sandhy; Aldo, Dasril; Darmansah, Darmansah
Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 6, No 1 (2023): Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstormin
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/japhb.v6i1.4520

Abstract

Pada saat ini strategi pemasaran berbasis teknologi merupakan suatu alternative pilihan masyarakat untuk berbelanja secara online. Metode yang dipakai dalam penjualan yang digunakan untuk pemasaran sebelumnya seperti melalui media whatsapp/ Instagram. Dengan adanya marketplace sebagai media penjualan mampu membuat sistem pemasaran menjadi lebih efektif, efisien dan mudah sehingga Masyarakat Desa Cikakak dapat mengenal marketplace sebagai media penjualan online.  Tujuan dari pengabdian ini merupakan untuk menambah wawasan masyarakat Desa Cikakak dari fungsi media promosi dan penjualan elektronik untuk mengetahui kendala yang dihadapi dalam memperkenalkan product UMKM ke dalam media marketplace. Jenis pengabdian masyarakat ini dilakukan dengan cara pelatihan langsung ke Desa Cikakak. Hasil pengabdian berupa pembuatan toko online di marketplace dengan menggunakan media promosi seperti Shopee, Tiktokshop dan Google My Business yang dapat membantu serta mempermudah mengurangi biaya yang dikeluarkan, dapat menyampaikan informasi secara detail dan cepat mengenai produk kepada pelanggan, sehingga produk dari UMKM desa Cikakak dapat dikenal lebih luas. Berdasarkan hasil pengabdian masyarakat ini diharapkan dapat membantu Desa Cikakak untuk mendapatkan hasil yang lebih maksimal serta dapat bersaing dengan toko offline maupun online yang sejenis.
Implementasi FP-Growth untuk Analisis Pola Pembelian Produk Elektronik pada Tokopedia Handoko, Koko; Darmansah, Darmansah; Adhiatma, Novri
Jurnal Pendidikan Sains dan Komputer Vol. 5 No. 02 (2025): Artikel Riset Oktober 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v5i02.6963

Abstract

Kemajuan teknologi informasi, e-commerce Indonesia berkembang secara pesat, dengan Tokopedia menjadi salah satu situs belanja online terbesar. Dengan menggunakan algoritma FP-Growth, penelitian ini akan menganalisis pola pembelian produk elektronik di Tokopedia. Tahapan meliputi proses preprocessing data, pembentukan itemset, dan ekstraksi aturan asosiasi berdasarkan nilai minimum support dan confidence. Data yang digunakan terdiri dari 5.000 data transaksi yang dilakukan oleh pelanggan dengan berbagai jenis elektronik, seperti smartphone, laptop, charger, powerbank, earphone, mouse, dan flashdisk. Penelitian dilakukan dengan parameter minimum support yaitu 20% dan minimum confidence 50%. Hasil penelitian ini menunjukkan beberapa aturan asosiasi yang signifikan, seperti konsumen yang membeli smartphone cenderung juga membeli earphone (support 25%, confidence 65%). Konsumen membeli Mouse dan juga membeli Laptop (support 21%, confidence 70%). Konsumen membeli Flashdisk juga terkait dengan membeli Laptop (support 20%, confidence 60%). Konsumen membeli Powerbank juga membeli Charger (support 24%, confidence 55%). Kemudian pola dengan nilai lift tertinggi adalah Smartphone dan Earphone (1,25) serta Powerbank dan Charger (1,22), yang menunjukkan bahwa kombinasi ini muncul bersama jauh lebih sering daripada jika pembelian dilakukan secara acak. Oleh karena itu, penelitian ini menemukan bahwa algoritma FP-Growth dapat dengan mudah menemukan pola pembelian produk elektronik dan dapat digunakan sebagai dasar pengambilan keputusan berbasis data dalam industri e-commerce.
Penerapan Metode VIKOR dalam SPK Penentuan Strategi Pemasaran Produk UMKM Astiti, Sarah; Samosir, Khairunnisa; Nengsih, Yeyi Gusla; Darmansah, Darmansah
Jurnal Pendidikan Sains dan Komputer Vol. 5 No. 02 (2025): Artikel Riset Oktober 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v5i02.6977

Abstract

Usaha mikro, kecil, dan menengah (UMKM) adalah salah satu sektor penting dalam pembangunan ekonomi khususnya daerah purwokerto. Namun, karena keterbatasan modal, akses terhadap teknologi digital dan persaingan yang semakin ketat, banyak UMKM menghadapi kesulitan dalam menentukan strategi pemasaran yang tepat. Seringkali, strategi pemasaran yang tidak tepat menghasilkan jangkauan pelanggan dan daya saing produk yang lebih rendah di pasar. Tujuan dari penelitian ini untuk menentukan strategi pemasaran produk UMKM di purwokerto. Dengan menggunakan analisis multi-kriteria, strategi pemasaran alternatif yang ideal dapat ditemukan. Metode yang di gunakan yaitu Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR), metode ini untuk menilai dan memilih strategi pemasaran yang paling efektif berdasarkan beberapa kriteria yang relevan. Data penelitian terdiri dari lima strategi pemasaran yang berbeda yaitu pemasaran melalui media sosial, promosi di pasar, mengikuti pameran atau acara, bekerja sama dengan influencer local dan strategi door-to-door. Setiap strategi dinilai berdasarkan lima kriteria yaitu biaya implementasi, jangkauan konsumen, efektivitas promosi, kesesuaian dengan tren digital, dan kemudahan pelaksanaan. Hasil perhitungan menunjukkan bahwa strategi pemasaran melalui media sosial menempati peringkat pertama dengan nilai Q = 0,000 karena memiliki tingkat efektivitas yang tinggi, jangkauan yang luas, dan biaya yang relatif rendah. Strategi kolaborasi dengan influencer menempati peringkat kedua dengan nilai Q = 0,115 sebagai alternatif kompromi, dan strategi pameran atau event dan door to door menempati peringkat ketiga dengan nilai Q = 0,236. Oleh karena itu, penelitian ini menemukan bahwa metode VIKOR dapat menawarkan strategi pemasaran yang lebih terukur dan objektif untuk UMKM.
SISTEM INFORMASI RIWAYAT PERJALANAN (SIRP) MASYARAKAT DIMASA PANDEMI BERBASIS WEBSITE (Studi Kasus: Kecamatan Sungai Geringging) darmansah, darmansah; Tomy Nanda Putra, Tomy; Willi Novrian, Willi Novrian
Indonesian Journal of Business Intelligence (IJUBI) Vol 4 No 2 (2021): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v4i2.1930

Abstract

The Corona virus or covid-19 began to appear in wuhan china at the end of 2019. Until now the corona virus has been a disease that has spread tremendously in countries in the world, none of which is Indonesia. To prepare accurate and reliable information in order to suppress the spread of the corona virus in Indonesia, an information system is needed. The Sungai Geringging District Government is a government in Padang Pariaman Regency which is currently collecting data on the travel history of its people during the pandemic manually or has not maximized computerization and technology. This of course makes the sub-district government in recording data, managing community data entering and leaving the government environment ineffective and inefficient. To assist the Sungai Geringging District Government in collecting data and disseminating information, it is necessary to build a website-based SIRP (Travel History Information System) information system. In designing this SIRP (Travel History Information System) the researcher used UML (Unified Modeling Language) modeling. In this study, UML was used to facilitate researchers when designing the system to be made. The method that researchers apply in this study is the prototyping method. With the construction of the Travel History Information System (SIRP) during the pandemic, it is hoped that the Sungai Geringging District Government can easily manage community data that enters and exits the government environment. In addition, the public can easily find out information on how many people are under surveillance (ODP) and people without symptoms (OTG) and other information related to the corona virus.
Perancangan Sistem Informasi Geografis Untuk Pemetaan Rumah Kos Berbasis Web Di Kota Batam mervin, les lie; Darmansah, Darmansah
Computer Based Information System Journal Vol. 13 No. 1 (2025): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v13i1.9577

Abstract

The design of this system is done to develop a web-based Geographic Information System (GIS) to help map boarding houses in Batam City. The development of this system is done using the Extreme Programming (XP) method, which emphasizes short iterations, and collaboration between developers and users. This system is designed by providing information about boarding houses. such as, boarding house location, facilities, prices, boarding house photos, boarding house types, boarding house web addresses, and their availability. The main features developed are mapping of boarding house locations with leaflet and OpenStreetMap integration, filters for searching based on price, facilities and type, and the ability for boarding house owners to add, edit, or delete boarding house data. Testing of this system is done using the black-box testing method, which shows that the entire system functions according to plan without any failures and errors. The results of the study of this system increase the ease of access to information for prospective boarding house tenants and provide a platform for boarding house owners to market their properties, as well as attract prospective boarding house tenants. The implementation system is expected to be a solution to overcome the problem of marketing boarding houses in Batam City, as well as making it easier for prospective boarding house tenants to find boarding house locations that suit their needs.
Perbandingan K-Means dan DBSCAN dalam Analisis Pola Pergerakan Kapal Menggunakan Data Automatic Identification System (AIS) Darmansah, Darmansah; Handoko, Koko; Adhiatma, Novri; Simanjuntak, Pastima
Journal of Information System Research (JOSH) Vol 7 No 3 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i3.9363

Abstract

Batam waters are one of the busiest shipping lanes in Indonesia, with high ship traffic density and complex movement patterns. This condition requires data analysis techniques that can accurately identify and adapt ship movement patterns. The purpose of this study is to study ship movement patterns using Automatic Identification System (AIS) data, and also to see how the K-Means and DBSCAN algorithms work in the data clustering process. The AIS data used includes geographic coordinates, observation time, speed, and direction of ship movement in Batam waters. This study includes the application of the K-Means and DBSCAN algorithms, feature extraction and normalization, and data pre-processing to improve data quality. Internal validation metrics used to assess cluster quality are the Silhouette Score and the Davies–Bouldin Index. The results of the study show that the DBSCAN algorithm has a better level of cluster cohesion and separation between clusters than K-Means. The K-Means algorithm produces a Silhouette Score value of 0.48 and a Davies–Bouldin Index value of 0.91, while the DBSCAN algorithm produces a Silhouette Score value of 0.62 and a Davies–Bouldin Index value of 0.67. In addition, DBSCAN can find sound data of 19.96% of the data set, which indicates abnormal ship movements or does not form a certain density pattern. The results show that the DBSCAN algorithm analyzes ship movement patterns with AIS data in the Batam waters better than K-Means. This research is expected to be the basis for the development of maritime information systems that help monitor ship traffic, make decisions about safety, and manage waters.
EKSPLORASI DATA PENJUALAN DI PT ABP UNTUK MENGUNGKAP FAKTA-FAKTA SEGMENTASI KONSUMEN PROPERTI MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING Stefanus; Darmansah, Darmansah
Computer Science and Industrial Engineering Vol 14 No 01 (2026): Comasie Vol 14 No 1
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v14i01.11099

Abstract

Housing sales data in property companies are commonly utilized only for administrative purposes, limiting their potential to generate strategic insights into consumer behavior and purchasing patterns. PT Adi Bintan Permata possesses a substantial volume of housing sales transaction data, yet this data has not been systematically analyzed to support data-driven marketing decisions. This study aims to identify consumer segmentation in the property sector at PT Adi Bintan Permata by applying the K-Means clustering algorithm. A quantitative descriptive research approach was employed using housing sales data from January 2022 to June 2025. The variables analyzed include housing selling price, housing unit type, and payment method. Data processing followed the Knowledge Discovery in Databases (KDD) framework, while the optimal number of clusters was determined using the Elbow Method and Silhouette Coefficient. The clustering process was conducted using RapidMiner and Google Colaboratory. The results reveal three distinct consumer clusters with different purchasing characteristics. These findings indicate that K-Means clustering is effective for property consumer segmentation and provides meaningful insights to support more targeted and effective marketing strategies.
EKPLORASI DATA PENJUALAN DI OTOXPERT MENGGUNAKAN ALGORITMA APRIORI Jeky, Jeky; Darmansah, Darmansah
Computer Science and Industrial Engineering Vol 14 No 01 (2026): Comasie Vol 14 No 1
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v14i01.11210

Abstract

This study aims to explore sales transaction data of spare parts at OTOXPERT Batam usingthe Apriori algorithm to identify association patterns among products. The main problemaddressed is that transaction data, although available in large quantities, has not beenoptimally utilized to uncover relationships between spare parts, so the potential use of thesepatterns to support cross-selling activities and stock management has not been fullyrealized. The data used in this study were sales transactions from January 1 to March 31,2025. The research method includes data preprocessing, transformation of transaction datainto basket form, descriptive analysis, and the application of the Apriori algorithm usingsupport, confidence, and lift parameters. The results show that the Apriori algorithm is ableto discover frequent itemsets and association rules that describe the tendency of spareparts to be purchased together. These patterns provide meaningful information aboutcustomer purchasing behavior and can be used as supporting information in decisionmaking related to sales strategies and inventory management. Therefore, this studydemonstrates that the Apriori algorithm is effective in transforming transaction data intovaluable information for business analysis at OTOXPERT Batam.
Co-Authors Alvendo Wahyu Aranski Amrizal Amrizal Amrizal Arnomo , Sasa Ani Cenderato Cenderato Dasril Aldo Elisa, Erlin Gusla Nengsih, Yeyi Handoko, Koko Harman, Rika Irene Svinarky Iswandi Iswandi Jeky, Jeky M Yoka Fathoni mervin, les lie Novri Adhiatma Novri Adhiatma, Novri Putra, Riko Andrian Samosir, Khairunnisa Sandhy Fernandez Saragih, Saut Pintubipar Sarah Astiti S.Kom., M.MT Simanjuntak, Pastima Stefanus Tomy Nanda Putra Willi Novrian, Willi Novrian