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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Matrik JMM (Jurnal Masyarakat Mandiri) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL PENDIDIKAN TAMBUSAI Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Informatika Global JSAI (Journal Scientific and Applied Informatics) Jurnal Abdimas Mandiri Jurnal Pemerintahan dan Politik Reswara: Jurnal Pengabdian Kepada Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Insyst : Journal of Intelligent System and Computation TIERS Information Technology Journal AKM: Aksi Kepada Masyarakat Jurnal Mandiri IT Indonesian Community Journal Klik - Jurnal Ilmu Komputer Malcom: Indonesian Journal of Machine Learning and Computer Science JURNAL PENGABDIAN PENDIDIKAN MASYARAKAT (JPPM) Journal of Information Systems Management and Digital Business Glow: Jurnal Pengabdian Kepada Masyarakat
Terttiaavini, Terttiaavini
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Journal : Insyst : Journal of Intelligent System and Computation

 1 
Predictive Buyer Behavior Model as Customer Retention Optimization Strategy in E-commerce Muhammad A. A. Hakim; Terttiaavini, Terttiaavini
Intelligent System and Computation Vol 6 No 1 (2024): INSYST: Journal of Intelligent System and Computation
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52985/insyst.v6i1.379

Abstract

Lazada is one of the rapidly growing E-commerce platforms in this digital era. One of the main challenges faced by Lazada is customer retention, where customers make purchases once or a few times before switching to other platforms. Therefore, it is important to understand buyer behavior in E-commerce through customer prediction to identify factors influencing retention. This study employs the Random Forest (RF) method to analyze Lazada customer data and formulate more effective marketing strategies. The analysis is conducted by loading preprocessed datasets into the KNIME workflow and utilizing various nodes and algorithms available in KNIME to build and evaluate predictive models. The Random Forest model is trained multiple times to achieve the highest Accuracy rate, which is 72.472%, with a fairly high level of agreement and a balanced trade-off between recall and precision. Additionally, this model successfully predicts that customers purchasing electronic equipment are potentially churning at a rate of 3.85%. Subsequently, customer strategy analysis for customer retention optimization in the E-commerce industry is conducted through data visualization using Tableau. Predictive analysis of customer behavior serves as a strong foundation for formulating effective retention strategies in the E-commerce industry. With this approach, Lazada can enhance customer experience and ensure sustainability in facing the increasingly fierce competition in the digital market.
A Hybrid Approach Using K-Means Clustering and the SAW Method for Evaluating and Determining the Priority of SMEs in Palembang City Terttiaavini, Terttiaavini
Intelligent System and Computation Vol 6 No 1 (2024): INSYST: Journal of Intelligent System and Computation
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52985/insyst.v6i1.392

Abstract

The current efforts to develop Small and Medium Enterprises (SMEs) are still facing challenges in setting appropriate targets. Although the Palembang City Cooperative and SME Agency has launched various programs and initiatives to support SME development, they have not yet successfully identified the SMEs that should be given priority for development. This study aims to apply a hybrid approach that combines the K-Means Clustering method and Simple Additive Weighting (SAW) to evaluate and prioritize SME development in Palembang City. The K-Means Clustering method is used to group SMEs based on their characteristics, while SAW provides preference values ( ). The SME data was obtained from the Palembang City Cooperative and SME Agency, covering 362 SME units. The K-Means Clustering results yielded two clusters: Cluster 0 as the High Growth Cluster and Cluster 1 as the Stability and Improvement Cluster. Validation using cross-validation showed that this model achieved an accuracy of 99.72%. The SAW analysis on Cluster 0 indicated that the Kopi Kaljo SME received the highest priority with a preference value of 45.71. This study confirms that this hybrid approach is effective in grouping SMEs based on their characteristics and prioritizing them based on data-driven evaluation. The research results are expected to help the Palembang City Cooperative and SME Agency design more effective and targeted assistance programs to optimize the contribution of SMEs to local economic growth to the maximum extent.
A Cascading Evaluation of Digital Population Identity in Palembang: Insights from ILPE and IPA Fadly, Farid; Kholik, Abdul; Alie, Muhammad F.; Heryati, Agustina; Terttiaavini, Terttiaavini; Antoni, Darius
Intelligent System and Computation Vol 6 No 2 (2024): INSYST: Journal of Intelligent System and Computation
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52985/insyst.v6i2.406

Abstract

Since 2022, the Indonesian government has implemented the Digital Population Identity (IKD) application, introduced by the Palembang City Population and Civil Registration Office (Disdukcapil). However, user satisfaction with IKD remains low. This study evaluates IKD user satisfaction using a cascading method combining the Electronic Public Service Index (ILPE) and Importance Performance Analysis (IPA). The ILPE calculation yields a total score of 2.682. The Information Availability (I) dimension scores highest at 0.570, reflecting strong user satisfaction with data accuracy and relevance. In contrast, the Interaction (SI) dimension scores the lowest at 0.325, highlighting the need for better communication and interaction. The IPA analysis categorizes dimensions into quadrants: Quadrant 1 (Keep Up the Good Work) includes T1 (Password Security), T4 (Reputation Recognition), T5 (Clarity of Authentication Criteria), I1 (Data Accuracy), I2 (Timely Updates), R2 (Access Availability), and R3 (Response Speed), showing excellent performance. Quadrant 2 (Concentrate Here) includes E4 (Accuracy of Data Entry Instructions) and U3 (Intuitive Navigation), requiring significant improvement. Quadrant 3 (Low Priority) includes E1 (Intuitive Navigation), E3 (Personalized Experience), T2 (Authentication Clarity), U1 (Intuitive Interface), U2 (Instruction Clarity), SI1 (Social Interaction), and SI2 (Communication Ease), with lower improvement priorities. Quadrant 4 (Possibly Overrated) contains R1 (Form Download Speed), which may be overemphasized. These findings aim to guide policy refinement, enhance public service efficiency, and improve user satisfaction.
Co-Authors Abdul Kholik Ade Dea Doyosy Agustina Agustina Heryati Agustina Heryati Agustina Heryati Heryati Ahmad Sanmorino Ajeng Oktatriani Akbar, M Dani Alie, Muhammad F. Andiki Sianipar Annisa Kurnia Antoni, Darius Arminarahmah, Nur Asmawati Asmawati Asmawati Asmawati Astuti, Lastri Widya Cahyani, Septa Candra Setiawan Cindy Destyana Putri Darmawan Susilo Derra Legiana Chintiya Dona Marcelina Eliya Berliana Endang Sri Lestari Endang Sri Lestari Ermatita - Evi Purnamasari Fadiya Faradita Fadly, Farid Fakhry Zamzam Fauziah Afriyani Fellyanus Habaora Fidya Nur Syabitha Fitriyana, Ayu fitriyani, Ulfa Habibillah, Amri Harsi Romli Harsih Rianto Hartati, Lesi Heryati, Agustina Indah Permatasari Indah Sukmawati Inessia Inessia Isabella, Isabella Iski Zaliman Iski Zaliman Jefirstson Richset Riwukore Juniarti, Anggi Putri K.Ghazali Kardinata, Silvia Kartina, Riza Lastri Widya Astuti Lesfandra Lesfandra Lesfandra, Lesfandra Lesi Hertati Lili Syafitri, Lili M Amaruna Sahona M Ravensky Taro Danayaksa Marcelina, Dona Marnisah, Luis Martadinata, A. Taqwa Masroni Dedi Kiswanto Maya Amelia Mody Sertian Amanda Muda, Seftia Putri Muhammad A. A. Hakim Muhammad Ramadhan Mulyati Mulyati Mulyati Mulyati Mustafa Ramadhan Mustika, Suci Permata Nadila Nurhalizah Ningsih Wahyuni Oktariani, Putri Pratama, Alga Wahyu Pratiwi Putri, Indah Purnamasari, Evi Putri Tsabita Putri, Indah Pratiwi Rahayu, Adelia Refki Saputra Rendra Gustriansyah Resti Wulandari Romli, Harsi Roni Sumari Hutabarat Sabrina Salsabila Putri Sahamony, Nur Fitriyani Salbani Salbani Sanawi, Fakhri Saputra, Tedy Setiawan Saputri, Lyra Ananda Seftia Putri Muda Sella Oktania Septa Cahyani Siti Komariah Hildayanti, Siti Komariah Suntana, Muhammad Yunus Thoiyibah Islamia Tri Septa Yulandari Trisna Hardianto Yeti Friyani Yossy Andri Ani Yulius, Yosef Zaliman, Iski Zanetti Julyah Berliana Perdana