Garuda - Garba Rujukan Digital

EVALUASI TINGKAT KEPUASAN PENGGUNA APLIKASI PELATIHAN DIGITAL ASURANSI MANULIFE DENGAN MENGGUNAKAN METODE EUCS DAN IPA Desak Putu Ayu Aprilia; I Komang Dharmendra; Ni Kadek Mesi Damayanti; Nyoman Ayu Nila Dewi
Jurnal Teknologi Informasi dan Komputer Vol. 10 No. 2 (2024): Jurnal Teknologi Informasi dan Komputer
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v10i2.3000

Manulife Indonesia menawarkan berbagai layanan keuangan termasuk asuransi jiwa,asuransi kecelakaan dan kesehatan, layanan investasi dan dana pensiun kepada konsumen individumaupun pelaku usaha di Indonesia. Dalam upaya untuk memenuhi kebutuhan pelatihan bagiagennya, pada tahun 2020 lalu Manulife Indonesia mengembangkan aplikasi pelatihan digital untuktenaga pemasar baik agen maupun finansial spesialis Manulife. Aplikasi MiLearn digunakan sebagaialat bantu untuk para agen dalam melayani nasabah dan dapat membantu meningkatkanketerampilan serta pengetahuan tentang asuransi dengan cara mengakses aplikasi yang dapatdilakukan dimana saja tanpa harus bertatap muka dengan trainer di ruang kelas. Tujuan daripenelitian ini adalah melakukan pengukuran tingkat kepuasan pengguna aplikasi MiLearnmenggunakan metode End User Computing Satisfaction (EUCS) dengan lima variabel yaituContent, Accuracy, Format, Ease of Use dan Timeliness. Kemudian metode IPA (ImportancePerformance Analysis) merupakan suatu teknik yang digunakan untuk mengukur tingkatkepentingan dan tingkat kinerja atribut. Pengumpulan data pada penelitian ini menggunakankuesioner yaitu google form dengan 59 responden dari agen MGM Bali yang menggunakan aplikasiMiLearn, data yang terkumpul diolah menggunakan software SPSS dan Excel. Kemudian hasilperhitungan nilai Indeks Kepuasan Pengguna (IKP) diperoleh hasil sebesar 80,41% yang berartiagen MGM Bali cukup puas dengan kinerja aplikasi MiLearn

Comparison of the DBSCAN Algorithm and Affinity Propagation on Business Incubator Tenant Customer Segmentation Agustino, Dedy Panji; Budaya, I Gede Bintang Arya; Harsemadi, I Gede; Dharmendra, I Komang; Pande, I Made Suandana Astika
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 2 (2023): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i2.1682

The increasingly complex business environment necessitates businesses to design more effective and efficient strategies for company development, including market expansion. To understand customer behaviors, customer data analysis becomes crucial. One common approach used to group customers is segmentation based on RFM analysis (Recency, Frequency, and Monetary). This study aims to compare the performance of two clustering algorithms, namely DBSCAN and Affinity Propagation (AP), in providing customer profile segment recommendations using RFM analysis. DBSCAN algorithm is employed due to its ability to identify arbitrarily shaped clusters and handle data noise. On the other hand, Affinity Propagation (AP) algorithm is chosen for its capability to discover cluster centers without requiring a pre-defined number of clusters. The transaction dataset used in this research is obtained from one of the business incubator tenants at STIKOM Bali. The dataset undergoes preprocessing steps before being segmented using both DBSCAN and AP algorithms. Performance evaluation of the algorithms is conducted using the Silhouette Scores and Davies-Bouldin Index (DBI) matrices. The research findings indicate that the AP algorithm outperforms DBSCAN in this customer segmentation case. The AP algorithm yields Silhouette Scores of 0.699 and DBI of 0.429, along with recommendations for 4 customer segments. Furthermore, further analysis is performed on the AP results using a statistical approach based on the mean values of each segment for the RFM variables. The four customer segments generated by the AP algorithm, based on the mean values of the RFM variables, can be associated with the concept of customer relationship management.

Pelatihan Canva Sebagai Media Pendukung Pembelajaran Dan Pengembangan Website Pada PKBM Widya Asrama I Komang Dharmendra; Agung Ngurah Rai Semadi, I Gusti; Agus Wirahadi Putra, I Made; Adistana Wira Saputra, Gede
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 8 : September (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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

The use of technology in education has become an urgent necessity in the digital era. PKBM Widya Asrama, a non-formal educational institution focused on educating local children, currently faces challenges in providing innovative and effective learning support media. Therefore, this community service project aims to provide training in the use of Canva as a learning support tool and to offer guidance on website development. This training is expected to assist PKBM Widya Asrama in enhancing the quality of education they provide and expanding their reach in offering educational access to the surrounding community. In addition to introducing Canva as a tool for creating engaging and creative learning materials, the training will equip the staff and teachers of PKBM Widya Asrama with skills in website development. As a result, the institution can more effectively disseminate information, manage participant data, and communicate their educational programs. Based on the evaluation conducted by the community service team, there has been a noticeable improvement in understanding how to create learning materials using Canva.

Application of Formal Concept Analysis and Clustering Algorithms to Analyze Customer Segments Budaya, I Gede Bintang Arya; Dharmendra, I Komang; Triandini, Evi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 2 (2025): April 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i2.6184

Business development cannot be separated from relationships with customers. Understanding customer characteristics is important both for maintaining sales and even for targeting new customers with appropriate strategies. The complexity of customer data makes manual analysis of the customer segments difficult, so applying machine learning to segment the customer can be the solution. This research implements K-Means and GMM algorithms for performing clustering based on the Transaction data transformed to the Recency, Frequency, and Monetary (RFM) data model, then implements Formal Concept Analysis (FCA) as an approach to analyzing the customer segment after the class labeling. Both K-Means and GMM algorithms recommended the optimal number of clusters as the customer segment is four. The FCA implementation in this study further analyzes customer segment characteristics by constructing a concept lattice that categorizes segments using combinations of High and Low values across the RFM attributes based on the median values, which are High Recency (HR), Low Recency (LR), High Frequency (HF), Low Frequency (LF), High Monetary (HM), and Low Monetary (LM). This characteristic can determine the customer category; for example, a customer that has HM and HR can be considered a loyal customer and can be the target for a specific marketing program. Overall, this study demonstrates that using the RFM data model, combined with clustering algorithms and FCA, is a potential approach for understanding MSME customer segment behavior. However, special consideration is necessary when determining the FCA concept lattice, as it forms the foundation of the core analytical insights.

Implementasi keamanan informasi file dokumen shipping menggunakan algoritma AES Shipping Dharmendra, I Komang; Januhari, Ni Nym Utami; Ramayasa, I Putu; Putra, I Made Agus Wirahadi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v7i1.1748

Opinion is an important part of decision making, so it takes the ability to get information from opinions. Sentiment Analysis is a branch of science from Text mining that can be used for opinion analysis in the form of text to classify opinions into 3 types of opinions, namely positive opinions, neutral opinions and negative opinions. Support Vector Machine (SVM) is one method that is widely applied for text mining because it is able to show good performance (Styawati and Mustofa, 2019). SVM works with a learning system that uses a hypothetical space in the form of linear functions in a high-dimensional feature space. Maximum Entropy is a probabilistic classification algorithm that belongs to the class of exponential models, which is based on the principle of Maximum Entropy. Maximum Entropy can be used to solve text classification problems such as Language detection, topic classification, and sentiment analysis. Sentiment analysis was tested using the Support Vector Machine (SVM) and Maximum Entropy methods to test the accuracy of each method in analyzing the sentiments of college alumni opinions. from the test results show Maximum Entropy has a better level of accuracy with the results of 95.45%

Implementasi keamanan informasi file dokumen shipping menggunakan algoritma AES Shipping Dharmendra, I Komang; Januhari, Ni Nym Utami; Ramayasa, I Putu; Putra, I Made Agus Wirahadi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v7i1.1748

Opinion is an important part of decision making, so it takes the ability to get information from opinions. Sentiment Analysis is a branch of science from Text mining that can be used for opinion analysis in the form of text to classify opinions into 3 types of opinions, namely positive opinions, neutral opinions and negative opinions. Support Vector Machine (SVM) is one method that is widely applied for text mining because it is able to show good performance (Styawati and Mustofa, 2019). SVM works with a learning system that uses a hypothetical space in the form of linear functions in a high-dimensional feature space. Maximum Entropy is a probabilistic classification algorithm that belongs to the class of exponential models, which is based on the principle of Maximum Entropy. Maximum Entropy can be used to solve text classification problems such as Language detection, topic classification, and sentiment analysis. Sentiment analysis was tested using the Support Vector Machine (SVM) and Maximum Entropy methods to test the accuracy of each method in analyzing the sentiments of college alumni opinions. from the test results show Maximum Entropy has a better level of accuracy with the results of 95.45%

Comparison of the DBSCAN Algorithm and Affinity Propagation on Business Incubator Tenant Customer Segmentation Agustino, Dedy Panji; Budaya, I Gede Bintang Arya; Harsemadi, I Gede; Dharmendra, I Komang; Pande, I Made Suandana Astika
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 12 No. 2 (2023): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i2.1682

The increasingly complex business environment necessitates businesses to design more effective and efficient strategies for company development, including market expansion. To understand customer behaviors, customer data analysis becomes crucial. One common approach used to group customers is segmentation based on RFM analysis (Recency, Frequency, and Monetary). This study aims to compare the performance of two clustering algorithms, namely DBSCAN and Affinity Propagation (AP), in providing customer profile segment recommendations using RFM analysis. DBSCAN algorithm is employed due to its ability to identify arbitrarily shaped clusters and handle data noise. On the other hand, Affinity Propagation (AP) algorithm is chosen for its capability to discover cluster centers without requiring a pre-defined number of clusters. The transaction dataset used in this research is obtained from one of the business incubator tenants at STIKOM Bali. The dataset undergoes preprocessing steps before being segmented using both DBSCAN and AP algorithms. Performance evaluation of the algorithms is conducted using the Silhouette Scores and Davies-Bouldin Index (DBI) matrices. The research findings indicate that the AP algorithm outperforms DBSCAN in this customer segmentation case. The AP algorithm yields Silhouette Scores of 0.699 and DBI of 0.429, along with recommendations for 4 customer segments. Furthermore, further analysis is performed on the AP results using a statistical approach based on the mean values of each segment for the RFM variables. The four customer segments generated by the AP algorithm, based on the mean values of the RFM variables, can be associated with the concept of customer relationship management.

Operational Optimization through the Development of a Digital Financial Transaction Recording Website in Village Owned Enterprise Sarwada Amerta, Taro Village: Optimalisasi Operasional melalui Pengembangan Website Pencatatan Transaksi Keuangan Digital di BUMDesa Sarwada Amerta Desa Taro Kusuma, Tubagus Mahendra; Budaya, I Gede Bintang Arya; Pande, I Made Suandana Astika; Dharmendra, I Komang
Mattawang: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2023)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.mattawang1821

In this community services activity, mentoring and implementation of a digital financial transaction recording system were conducted in village owned enterprise (VOE) Sarwada Amerta, Taro Village. The findings of this study demonstrate that the utilization of financial transaction information systems can optimize the financial operational processes of VOE. The efficiency and accuracy of financial data processing have improved, and the accessibility of financial information has become easier. However, it was found that the adaptation to the new information system still requires time for the human resources to consistently utilize the system. Strong support and commitment from relevant stakeholders, along with continuous educational efforts, are crucial factors in ensuring the successful implementation of the information system. This community services activity is expected to contribute to the economic development of the village through financial management education for VOE and by encouraging the utilization of information technology in local business financial management. Abstrak Pada kegiatan pengabdian masyarakat ini, dilakukan pendampingan dan implementasi sistem pencatatan keuangan digital di BUMDesa Sarwada Amerta, Desa Wisata Taro. Berdasarkan hasil dari kegiatan ini menunjukkan bahwa penggunaan sistem informasi pencatatan transaksi keuangan dapat mengoptimalkan proses operasional BUMDesa, khususnya dalam bidang keuangan. Efisiensi dan akurasi dalam pengolahan data keuangan meningkat, serta aksesibilitas informasi keuangan menjadi lebih mudah. Namun, ditemukan bahwa adaptasi terhadap sistem informasi yang baru masih memerlukan waktu bagi sumber daya manusia BUMDesa agar dapat menggunakan sistem dengan konsisten. Dukungan dan komitmen yang kuat dari pihak terkait, serta upaya edukasi yang berkelanjutan, menjadi faktor penting dalam memastikan keberhasilan implementasi sistem informasi ini. Kegiatan pengabdian ini diharapkan memberikan kontribusi dalam pengembangan ekonomi desa dengan edukasi manajemen keuangan BUMDesa serta mendorong pemanfaatan teknologi informasi dalam pengelolaan keuangan usaha di tingkat lokal.

Penguatan IRT Ayam Potong Melalui Peningkatan Kualitas Produk dan Pengelolaan Usaha Mahendra, Tubagus; Novia Ari Sandra; I Komang Dharmendra
Sevanam: Jurnal Pengabdian Masyarakat Vol 4 No 2 (2025): September
Publisher : Universitas Hindu Negeri I Gusti Bagus Sugriwa Denpasar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25078/sevanam.v4i2.5289

This community service program aims to empower household-scale chicken meat vendors by improving product quality and business management. The partner is a housewife who runs a small-scale chicken meat business without refrigeration tools or financial management knowledge. The methods employed were training, mentoring, and the provision of basic equipment adapted to the partner's needs. The partner was also facilitated with a bookkeeping/financial recording application using Microsoft Excel, as requested. Additionally, recommendations were given to separate personal and business expenses so that business development could be measured more accurately. The partner received guidance on how to maintain the quality of the chicken and increase product appeal to customers by processing quality products.Furthermore, supporting equipment such as a simple refrigeration unit was provided to help extend the freshness of the products. According to the partner, after using the freezer for storing the chicken, there were no more incidents of spoiled meat being sold, which previously occurred. As a result, the quality of the chicken products remained 100 percent preserved at the time of sale.

Strengthening Product Identity and Packaging Design as an Effort to Empower the Home-Based Industry Toya Kumkuman (Ukupan) Radhika Dharmendra, I Komang; I Made Agus Wirahadi Putra; Fathur Mahida Rangga; Yohanes Priyo Atmojo; Dinda Sari
Society : Jurnal Pengabdian Masyarakat Vol. 4 No. 6 (2025): November
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/bp16x625

The Toya Kumkuman (Ukupan) Radhika household industry, producing sacred water used in Balinese Hindu rituals, faces several challenges in its production and marketing. Despite positive market reception, the products were hindered by weak packaging quality, leakage due to manual sealing, and the absence of a clear brand identity. The lack of labels not only complicated consumer recognition but also prevented the inclusion of important information such as production and expiration dates, reducing competitiveness in the market. To address these issues, the community engagement team from ITB STIKOM Bali implemented a series of structured interventions. The activities included socialization with partners, mentoring on improved packaging design, the creation of product logos and labels reflecting the business philosophy, and the provision of production equipment such as a cup sealer and thermal printer. These implementations were complemented by workshops and training to ensure sustainable application. The outcomes demonstrated significant improvements: the new cup-sealed packaging reduced leakage and extended product shelf life, while the professionally designed logo and label strengthened product identity and consumer trust. Furthermore, the use of appropriate equipment enhanced efficiency in production and branding capacity. Overall, the program successfully empowered the partner by elevating product quality, improving market competitiveness, and fostering brand awareness, thereby ensuring the sustainability of Toya Kumkuman Radhika as a home-based industry. Industri rumahan Toya Kumkuman (Ukupan) Radhika yang memproduksi air suci untuk keperluan ritual umat Hindu di Bali menghadapi beberapa tantangan dalam proses produksi dan pemasaran. Meskipun mendapat sambutan positif dari masyarakat, produk ini masih terkendala oleh kualitas kemasan yang kurang baik, potensi kebocoran akibat penyegelan manual, serta ketiadaan identitas merek yang jelas. Tidak adanya label produk tidak hanya menyulitkan konsumen dalam mengenali produk, tetapi juga menghalangi pencantuman informasi penting seperti tanggal produksi dan kedaluwarsa, sehingga mengurangi daya saing di pasar. Untuk mengatasi masalah tersebut, tim pengabdian masyarakat dari ITB STIKOM Bali melaksanakan serangkaian kegiatan terstruktur. Kegiatan meliputi sosialisasi dengan mitra, pendampingan pengembangan desain kemasan, pembuatan logo dan label produk yang sesuai filosofi usaha, serta pemberian peralatan produksi seperti cup sealer dan printer thermal. Implementasi ini dilengkapi dengan pelatihan agar mitra mampu menerapkannya secara berkelanjutan. Hasil kegiatan menunjukkan adanya peningkatan signifikan: kemasan baru dengan segel cup mengurangi kebocoran dan memperpanjang daya simpan produk, sementara logo dan label profesional memperkuat identitas produk dan kepercayaan konsumen. Selain itu, penggunaan peralatan baru meningkatkan efisiensi produksi dan kapasitas branding mitra. Secara keseluruhan, program ini berhasil memberdayakan mitra dengan meningkatkan kualitas produk, memperkuat daya saing di pasar, serta membangun kesadaran merek sehingga mendukung keberlanjutan industri rumahan Toya Kumkuman Radhika

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