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Analisis cost volume profit pada Hasanudin Orchids Nursery & Laboratory Mustika Charismawati; Ary Bakhtiar; Istis Baroh

Publisher : Fakultas Pertanian Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/agx.v14i1.3158

????????????????????????????????????????????????: ???????????????? ???????????????????????? ???????????????????????? ???????????????????????????????? ???????? ???????????? ???????? ???????????? ???????????????????? ???????????????? ???????????? ???????? ???????????????? ???????? ???????????????????????? ????????????????????????????????, ????????????????????????????????????????????, ???????????? ???????????????????????? ???????????????????????????????????? ???????????????????? ???????????????????????????? ???????????????????????????????????????? ???????? ???????????????????????????????????? ???????????? ???????????????????????????? ???????????????????????? ???????????? ???????????????????????????? ???????????????? ???????????????????????????? ???????????????? ???????????? ???????????????????? ???????? ???????????????????? ???????????????????????? ???????????? ???????????????????? ????????????????????????????????. ???????????? ???????????????????????????????????????? ???????? ???????????????? ???????????????????????????????? ???????????? ???????? ???????????????? ???????????? ???????????????? ???????? ???????????????????????????????????? ???????? ???????????????? ???????? ???????????????????????????? ???????????? ???????????????????????????????????????????? ???????? ???????????????? ???????????????????????? ???????????????????????? ???????????????????????????????? ???????? ???????????????????????????????????? ???????????????????????????? ???????????????????????????? & ????????????????????????????????????????. ????????????????????????????: ???????????????? ???????????????????????????????? ???????? ???????????????????????????????????????????? ???????????????????????????????? ???????????????????? ???? ???????????????????????????????????????????????? ???????????????????????????????? ???????????? ???????????????? ???????????????? ???????? ???????????????? ???????????????????? ???????????????????? ???????????????????????????? ???????????????? ???????????????????????????????? ???????????????????????????? ???????????????????????? ???????????????????????????????????????????? ???????????? ????????????????????????????????????????. ???????????????? ???????????????????????????????????? ???????????????? ???????????????????????????????? ???????????????????? ???????????? ???????????????????????????? ???????????????????? ???????????????? (???????? = ???????? + ????????) ???????????????? ???????????????????????? ???????????????????????? ???????????????????????????????? ???????????????? ???????????????????????????????????????????? ???????????????????????????????????????????????? ????????????????????????, ???????????????????? ???????????????? ???????????????????? (????????????), ???????????? ???????????????????????? ???????? ???????????????????????? (????????????). ????????????????????????????: ???????????????????????????????? ???????????????? ???????????????????????????? ???????????????????????? ???????????????????? ???????? ???????????????????????????? ???????????????????????????????????? ???????????????????????????? ???????????????????????????? & ???????????????????????????????????????? ???????? 2019 ???????????????? 48,000 ???????????????????? ???????? ???????????????????????? ???????????????????? ???????? ????????1.920.000.000 ???????????????? ???? ???????????????????????? ???????? ????????928.430.869, ???????????? ???????????? ???????????????????? ???????????? ????????61.300.000, ???????????????????? ???????????? ???????????? ???????????????????????????????? ???????????? 1.534 ???????????????????????????? ???????? ???????????????????????? ???????????????????? ???????????? ???????????? ???????????????????? ???????? 96.80% ???????? ???????????????????? ???????? 46.466 ???????????????????????????? ???????? ???????????????????????? ????????????????????. ????????????????????????????????????????: ???????????????????? ???????? ???????????????????????????????????? ???????????????????????????? ???????????????????????????? & ???????????????????????????????????????? ???????????????? ???????????????????????????????? ???????????? ???????????? ???????????????????? ???????????? ???????????????? ???????? ???????????????????? ???????????????????? ???????????????????? ???????????????????? ???????????????????? ???????????????????? ???????????? ???????????????????????????????? ????????????????????????????. ???????????????????? ???????????????????????????? ???????????? ???????? ???????????????? ???????? ???? ???????????????????????????????? ???????????????????????????????????? ???????????? ???????????? ???????????????? ????????????????.

The role of agricultural extension workers in digital transformation at the Agricultural Extension Center in Lowokwaru Malang Salsabella, Irene Hanies; Bakhtiar, Ary; Ibrahim, Jabal Tarik

Publisher : Fakultas Pertanian Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/agx.v15i2.4098

Introduction: The pivotal role of the agricultural sector in Indonesia's economic advancement stems from the employment of a significant portion of the Indonesian populace. Central to this sector are agricultural extension workers tasked with fostering motivational shifts, altering operational methodologies, and instilling adaptive practices congruent with technological advancements. This research endeavors to scrutinize the modus operandi of agricultural extension workers amidst the digital metamorphosis era within the Agricultural Extension Center situated in Lowokwaru, Malang, Indonesia. Methods: Employing a Mixed methods approach, this study draws upon primary and secondary data sources. Thirty samples, affiliated with the Farmers Group at the Agricultural Extension Center in Lowokwaru Malang, constitute the study cohort, selected through purposive sampling techniques. Data accrual involves questionnaire administration, employing the Likert scale as the measurement metric. Statistical analysis entails multiple linear regression, facilitated through SPSS 22 software. Results: Simultaneously, variables embodying extension workers' roles as facilitators, innovators, motivators, dynamists, and educators collectively impact the income of registered farmers at the Agricultural Extension Center in Lowokwaru, Malang. Conclusion: This study reveals that the roles of extension workers as facilitators, innovators, and educators significantly enhance farmers' capacity to integrate digital technology into their agricultural practices. Nevertheless, the absence of direct statistical significance in some roles suggests the interplay of other critical factors, such as farmers' readiness to adopt technology and external support mechanisms. These findings highlight the need for targeted interventions to bolster extension workers' capabilities and farmer engagement with digital innovations.

Agroindustrial productivity through copra processing partnership mechanisms in Bulukumba, South Sulawesi, Indonesia Firdausi, Ananda Nuril; Bakhtiar, Ary; Agustina, Yohana; Akbar, Adjar Yusriandi

Publisher : Fakultas Pertanian Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/agx.v16i1.4013

Introduction: the expanding demand for copra (the dried flesh of a coconut), the desiccated kernel of the coconut fruit, underscores its promising potential for agroindustrial development. Effective partnership formations emerge as pivotal drivers in this context. This study aims to ascertain the most productive partnership patterns within five distinct mechanisms operating in Bulukumba, South Sulawesi, Indonesia. Methods: the research site was determined using a purposive method, selecting five sub-districts prominent for coconut production, and employing the snowball sampling technique for data collection. Productivity analysis was conducted utilizing efficiency criteria and profit ratios across various partnership patterns. Results: efficiency and profit ratios were calculated for each mechanism as follows: 1) middlemen involvement yielded an efficiency of 107% and a profit ratio of 0.94; 2) engagement with local traders resulted in 77% efficiency and a profit ratio of 1.29; 3) participation in farmers' associations exhibited 36% efficiency and a profit ratio of 2.76; 4) group mechanisms demonstrated 86% efficiency and a profit ratio of 1.17; while 5) subcontract mechanisms displayed 31% efficiency and a profit ratio of 3.24. Conclusion: among the investigated mechanisms, the subcontract mechanisms emerged as the most productive partnership model, while the middlemen mechanism, non-partnership, exhibited the lowest productivity.

Analisis cost volume profit pada Hasanudin Orchids Nursery & Laboratory: Analysis of cost volume profit in Hasanudin Orchids Nursery & Laboratory Mustika Charismawati; Bakhtiar, Ary; Baroh, Istis
AGROMIX Vol 14 No 1 (2023)
Publisher : Fakultas Pertanian Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/agx.v14i1.3158

ð˜ð˜¯ð˜µð˜³ð˜°ð˜¥ð˜¶ð˜¤ð˜µð˜ªð˜°ð˜¯: ð˜Šð˜°ð˜´ð˜µ ð˜·ð˜°ð˜ð˜¶ð˜®ð˜¦ ð˜±ð˜³ð˜°ð˜§ð˜ªð˜µ ð˜¢ð˜¯ð˜¢ð˜ð˜ºð˜´ð˜ªð˜´ ð˜ªð˜´ ð˜°ð˜¯ð˜¦ ð˜°ð˜§ ð˜µð˜©ð˜¦ ð˜µð˜°ð˜°ð˜ð˜´ ð˜µð˜©ð˜¢ð˜µ ð˜¤ð˜¢ð˜¯ ð˜£ð˜¦ ð˜¶ð˜´ð˜¦ð˜¥ ð˜¢ð˜´ ð˜±ð˜³ð˜°ð˜§ð˜ªð˜µ ð˜±ð˜ð˜¢ð˜¯ð˜¯ð˜ªð˜¯ð˜¨, ð˜¤ð˜°ð˜¯ð˜µð˜³ð˜°ð˜ð˜ð˜ªð˜¯ð˜¨, ð˜¢ð˜¯ð˜¥ ð˜®ð˜¢ð˜¬ð˜ªð˜¯ð˜¨ ð˜¥ð˜¦ð˜¤ð˜ªð˜´ð˜ªð˜°ð˜¯ð˜´ ð˜¢ð˜£ð˜°ð˜¶ð˜µ ð˜¤ð˜°ð˜®ð˜±ð˜¢ð˜¯ð˜º ð˜¢ð˜¤ð˜µð˜ªð˜·ð˜ªð˜µð˜ªð˜¦ð˜´ ð˜ªð˜¯ ð˜¢ð˜¤ð˜©ð˜ªð˜¦ð˜·ð˜ªð˜¯ð˜¨ ð˜µð˜©ð˜¦ ð˜¥ð˜¦ð˜´ð˜ªð˜³ð˜¦ð˜¥ ð˜±ð˜³ð˜°ð˜§ð˜ªð˜µ ð˜¢ð˜¯ð˜¥ ð˜¥ð˜¦ð˜¢ð˜ð˜ªð˜¯ð˜¨ ð˜¸ð˜ªð˜µð˜© ð˜¤ð˜©ð˜¢ð˜¯ð˜¨ð˜¦ð˜´ ð˜µð˜©ð˜¢ð˜µ ð˜®ð˜¢ð˜º ð˜°ð˜¤ð˜¤ð˜¶ð˜³ ð˜ªð˜¯ ð˜´ð˜¢ð˜ð˜¦ð˜´ ð˜·ð˜°ð˜ð˜¶ð˜®ð˜¦ ð˜¢ð˜¯ð˜¥ ð˜¤ð˜°ð˜´ð˜µð˜´ ð˜ªð˜¯ð˜¤ð˜¶ð˜³ð˜³ð˜¦ð˜¥. ð˜›ð˜©ð˜¦ ð˜°ð˜£ð˜«ð˜¦ð˜¤ð˜µð˜ªð˜·ð˜¦ð˜´ ð˜°ð˜§ ð˜µð˜©ð˜ªð˜´ ð˜³ð˜¦ð˜´ð˜¦ð˜¢ð˜³ð˜¤ð˜© ð˜¢ð˜³ð˜¦ ð˜µð˜° ð˜¬ð˜¯ð˜°ð˜¸ ð˜µð˜©ð˜¦ ð˜¤ð˜°ð˜´ð˜µ ð˜°ð˜¯ ð˜´ð˜µð˜³ð˜¶ð˜¤ð˜µð˜¶ð˜³ð˜¦ ð˜¢ð˜´ ð˜¸ð˜¦ð˜ð˜ ð˜¢ð˜´ ð˜¬ð˜¯ð˜°ð˜¸ð˜ªð˜¯ð˜¨ ð˜µð˜©ð˜¦ ð˜¢ð˜±ð˜±ð˜ð˜ªð˜¤ð˜¢ð˜µð˜ªð˜°ð˜¯ ð˜°ð˜§ ð˜¤ð˜°ð˜´ð˜µ ð˜·ð˜°ð˜ð˜¶ð˜®ð˜¦ ð˜±ð˜³ð˜°ð˜§ð˜ªð˜µ ð˜¢ð˜¯ð˜¢ð˜ð˜ºð˜´ð˜ªð˜´ ð˜ªð˜¯ ð˜ð˜¢ð˜´ð˜¢ð˜¯ð˜¶ð˜¥ð˜ªð˜¯ ð˜–ð˜³ð˜¤ð˜©ð˜ªð˜¥ð˜´ ð˜•ð˜¶ð˜³ð˜´ð˜¦ð˜³ð˜º & ð˜“ð˜¢ð˜£ð˜°ð˜³ð˜¢ð˜µð˜°ð˜³ð˜º. ð˜”ð˜¦ð˜µð˜©ð˜°ð˜¥ð˜´: ð˜›ð˜©ð˜ªð˜´ ð˜³ð˜¦ð˜´ð˜¦ð˜¢ð˜³ð˜¤ð˜© ð˜ªð˜´ ð˜¥ð˜¦ð˜´ð˜¤ð˜³ð˜ªð˜±ð˜µð˜ªð˜·ð˜¦ ð˜³ð˜¦ð˜´ð˜¦ð˜¢ð˜³ð˜¤ð˜© ð˜¶ð˜´ð˜ªð˜¯ð˜¨ ð˜¢ ð˜²ð˜¶ð˜¢ð˜¯ð˜µð˜ªð˜µð˜¢ð˜µð˜ªð˜·ð˜¦ ð˜¢ð˜±ð˜±ð˜³ð˜°ð˜¢ð˜¤ð˜© ð˜›ð˜©ð˜¦ ð˜¥ð˜¢ð˜µð˜¢ ð˜¶ð˜´ð˜¦ð˜¥ ð˜ªð˜¯ ð˜µð˜©ð˜ªð˜´ ð˜´ð˜µð˜¶ð˜¥ð˜º ð˜¶ð˜´ð˜ªð˜¯ð˜¨ ð˜±ð˜³ð˜ªð˜®ð˜¢ð˜³ð˜º ð˜¥ð˜¢ð˜µð˜¢ ð˜°ð˜£ð˜µð˜¢ð˜ªð˜¯ð˜¦ð˜¥ ð˜µð˜©ð˜³ð˜°ð˜¶ð˜¨ð˜© ð˜¥ð˜ªð˜³ð˜¦ð˜¤ð˜µ ð˜°ð˜£ð˜´ð˜¦ð˜³ð˜·ð˜¢ð˜µð˜ªð˜°ð˜¯ ð˜¢ð˜¯ð˜¥ ð˜ªð˜¯ð˜µð˜¦ð˜³ð˜·ð˜ªð˜¦ð˜¸ð˜´. ð˜Šð˜°ð˜´ð˜µ ð˜´ð˜µð˜³ð˜¶ð˜¤ð˜µð˜¶ð˜³ð˜¦ ð˜¥ð˜¢ð˜µð˜¢ ð˜¢ð˜¯ð˜¢ð˜ð˜ºð˜´ð˜ªð˜´ ð˜¶ð˜´ð˜ªð˜¯ð˜¨ ð˜µð˜©ð˜¦ ð˜§ð˜°ð˜³ð˜®ð˜¶ð˜ð˜¢ ð˜›ð˜°ð˜µð˜¢ð˜ ð˜Šð˜°ð˜´ð˜µ (ð˜›ð˜Š = ð˜ð˜Š + ð˜ð˜Š) ð˜¤ð˜°ð˜´ð˜µ ð˜·ð˜°ð˜ð˜¶ð˜®ð˜¦ ð˜±ð˜³ð˜°ð˜§ð˜ªð˜µ ð˜¢ð˜¯ð˜¢ð˜ð˜ºð˜´ð˜ªð˜´ ð˜¶ð˜´ð˜¦ð˜¥ ð˜¤ð˜¢ð˜ð˜¤ð˜¶ð˜ð˜¢ð˜µð˜ªð˜°ð˜¯ ð˜¤ð˜°ð˜¯ð˜µð˜³ð˜ªð˜£ð˜¶ð˜µð˜ªð˜°ð˜¯ ð˜®ð˜¢ð˜³ð˜¨ð˜ªð˜¯, ð˜£ð˜³ð˜¦ð˜¢ð˜¬ ð˜¦ð˜·ð˜¦ð˜¯ ð˜±ð˜°ð˜ªð˜¯ð˜µ (ð˜‰ð˜Œð˜—), ð˜¢ð˜¯ð˜¥ ð˜®ð˜¢ð˜³ð˜¨ð˜ªð˜¯ ð˜°ð˜§ ð˜´ð˜¢ð˜§ð˜¦ð˜µð˜º (ð˜”ð˜–ð˜š). ð˜™ð˜¦ð˜´ð˜¶ð˜ð˜µð˜´: ð˜—ð˜³ð˜°ð˜¤ð˜¦ð˜¦ð˜¥ð˜´ ð˜§ð˜³ð˜°ð˜® ð˜´ð˜¦ð˜ð˜ð˜ªð˜¯ð˜¨ ð˜°ð˜³ð˜¤ð˜©ð˜ªð˜¥ ð˜´ð˜¦ð˜¦ð˜¥ð˜´ ð˜ªð˜¯ ð˜£ð˜°ð˜µð˜µð˜ð˜¦ð˜´ ð˜ð˜¢ð˜´ð˜¢ð˜¯ð˜¶ð˜¥ð˜ªð˜¯ ð˜–ð˜³ð˜¤ð˜©ð˜ªð˜¥ð˜´ ð˜•ð˜¶ð˜³ð˜´ð˜¦ð˜³ð˜º & ð˜“ð˜¢ð˜£ð˜°ð˜³ð˜¢ð˜µð˜°ð˜³ð˜º ð˜ªð˜¯ 2019 ð˜¸ð˜¦ð˜³ð˜¦ 48,000 ð˜¶ð˜¯ð˜ªð˜µð˜´ ð˜°ð˜§ ð˜£ð˜°ð˜µð˜µð˜ð˜¦ ð˜´ð˜¦ð˜¦ð˜¥ð˜´ ð˜°ð˜³ ð˜™ð˜±1.920.000.000 ð˜¸ð˜ªð˜µð˜© ð˜¢ ð˜±ð˜³ð˜°ð˜§ð˜ªð˜µ ð˜°ð˜§ ð˜™ð˜±928.430.869, ð˜›ð˜©ð˜¦ ð˜‰ð˜Œð˜— ð˜±ð˜³ð˜ªð˜¤ð˜¦ ð˜¸ð˜¢ð˜´ ð˜™ð˜±61.300.000, ð˜¸ð˜©ð˜ªð˜ð˜¦ ð˜µð˜©ð˜¦ ð˜‰ð˜Œð˜— ð˜²ð˜¶ð˜¢ð˜¯ð˜µð˜ªð˜µð˜º ð˜¸ð˜¢ð˜´ 1.534 ð˜£ð˜°ð˜µð˜µð˜ð˜¦ð˜´ ð˜°ð˜§ ð˜°ð˜³ð˜¤ð˜©ð˜ªð˜¥ ð˜´ð˜¦ð˜¦ð˜¥ð˜´ ð˜¢ð˜¯ð˜¥ ð˜”ð˜–ð˜š ð˜ð˜¦ð˜·ð˜¦ð˜ ð˜°ð˜§ 96.80% ð˜°ð˜³ ð˜´ð˜¢ð˜ð˜¦ð˜´ ð˜°ð˜§ 46.466 ð˜£ð˜°ð˜µð˜µð˜ð˜¦ð˜´ ð˜°ð˜§ ð˜°ð˜³ð˜¤ð˜©ð˜ªð˜¥ ð˜´ð˜¦ð˜¦ð˜¥ð˜´. ð˜Šð˜°ð˜¯ð˜¤ð˜ð˜¶ð˜´ð˜ªð˜°ð˜¯: ð˜šð˜¢ð˜ð˜¦ð˜´ ð˜¢ð˜µ ð˜ð˜¢ð˜´ð˜¢ð˜¯ð˜¶ð˜¥ð˜ªð˜¯ ð˜–ð˜³ð˜¤ð˜©ð˜ªð˜¥ð˜´ ð˜•ð˜¶ð˜³ð˜´ð˜¦ð˜³ð˜º & ð˜“ð˜¢ð˜£ð˜°ð˜³ð˜¢ð˜µð˜°ð˜³ð˜º ð˜©ð˜¢ð˜·ð˜¦ ð˜¦ð˜¹ð˜¤ð˜¦ð˜¦ð˜¥ð˜¦ð˜¥ ð˜‰ð˜Œð˜— ð˜¢ð˜¯ð˜¥ ð˜´ð˜¢ð˜ð˜¦ð˜´ ð˜¢ð˜³ð˜¦ ð˜¢ð˜£ð˜ð˜¦ ð˜µð˜° ð˜¤ð˜°ð˜·ð˜¦ð˜³ ð˜§ð˜ªð˜¹ð˜¦ð˜¥ ð˜¤ð˜°ð˜´ð˜µð˜´ ð˜¸ð˜©ð˜ªð˜¤ð˜© ð˜®ð˜¦ð˜¢ð˜¯ð˜´ ð˜´ð˜¢ð˜ð˜¦ð˜´ ð˜¤ð˜¢ð˜¯ ð˜¨ð˜¦ð˜¯ð˜¦ð˜³ð˜¢ð˜µð˜¦ ð˜±ð˜³ð˜°ð˜§ð˜ªð˜µð˜´. ð˜›ð˜©ð˜¦ð˜´ð˜¦ ð˜³ð˜¦ð˜´ð˜¶ð˜ð˜µð˜´ ð˜¤ð˜¢ð˜¯ ð˜£ð˜¦ ð˜¶ð˜´ð˜¦ð˜¥ ð˜¢ð˜´ ð˜¢ ð˜±ð˜ð˜¢ð˜¯ð˜¯ð˜ªð˜¯ð˜¨ ð˜³ð˜¦ð˜§ð˜¦ð˜³ð˜¦ð˜¯ð˜¤ð˜¦ ð˜§ð˜°ð˜³ ð˜µð˜©ð˜¦ ð˜¯ð˜¦ð˜¹ð˜µ ð˜´ð˜¢ð˜ð˜¦.

Agroindustrial productivity through copra processing partnership mechanisms in Bulukumba, South Sulawesi, Indonesia Firdausi, Ananda Nuril; Bakhtiar, Ary; Agustina, Yohana; Akbar, Adjar Yusriandi
AGROMIX Vol 16 No 1 (2025)
Publisher : Fakultas Pertanian Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/agx.v16i1.4013

Introduction: the expanding demand for copra (the dried flesh of a coconut), the desiccated kernel of the coconut fruit, underscores its promising potential for agroindustrial development. Effective partnership formations emerge as pivotal drivers in this context. This study aims to ascertain the most productive partnership patterns within five distinct mechanisms operating in Bulukumba, South Sulawesi, Indonesia. Methods: the research site was determined using a purposive method, selecting five sub-districts prominent for coconut production, and employing the snowball sampling technique for data collection. Productivity analysis was conducted utilizing efficiency criteria and profit ratios across various partnership patterns. Results: efficiency and profit ratios were calculated for each mechanism as follows: 1) middlemen involvement yielded an efficiency of 107% and a profit ratio of 0.94; 2) engagement with local traders resulted in 77% efficiency and a profit ratio of 1.29; 3) participation in farmers' associations exhibited 36% efficiency and a profit ratio of 2.76; 4) group mechanisms demonstrated 86% efficiency and a profit ratio of 1.17; while 5) subcontract mechanisms displayed 31% efficiency and a profit ratio of 3.24. Conclusion: among the investigated mechanisms, the subcontract mechanisms emerged as the most productive partnership model, while the middlemen mechanism, non-partnership, exhibited the lowest productivity.

The role of agricultural extension workers in digital transformation at the Agricultural Extension Center in Lowokwaru Malang Salsabella, Irene Hanies; Bakhtiar, Ary; Ibrahim, Jabal Tarik
AGROMIX Vol 15 No 2 (2024)
Publisher : Fakultas Pertanian Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/agx.v15i2.4098

Introduction: The pivotal role of the agricultural sector in Indonesia's economic advancement stems from the employment of a significant portion of the Indonesian populace. Central to this sector are agricultural extension workers tasked with fostering motivational shifts, altering operational methodologies, and instilling adaptive practices congruent with technological advancements. This research endeavors to scrutinize the modus operandi of agricultural extension workers amidst the digital metamorphosis era within the Agricultural Extension Center situated in Lowokwaru, Malang, Indonesia. Methods: Employing a Mixed methods approach, this study draws upon primary and secondary data sources. Thirty samples, affiliated with the Farmers Group at the Agricultural Extension Center in Lowokwaru Malang, constitute the study cohort, selected through purposive sampling techniques. Data accrual involves questionnaire administration, employing the Likert scale as the measurement metric. Statistical analysis entails multiple linear regression, facilitated through SPSS 22 software. Results: Simultaneously, variables embodying extension workers' roles as facilitators, innovators, motivators, dynamists, and educators collectively impact the income of registered farmers at the Agricultural Extension Center in Lowokwaru, Malang. Conclusion: This study reveals that the roles of extension workers as facilitators, innovators, and educators significantly enhance farmers' capacity to integrate digital technology into their agricultural practices. Nevertheless, the absence of direct statistical significance in some roles suggests the interplay of other critical factors, such as farmers' readiness to adopt technology and external support mechanisms. These findings highlight the need for targeted interventions to bolster extension workers' capabilities and farmer engagement with digital innovations.

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